# Best Machine Learning Data Catalog Software *By [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)* Machine learning data catalogs allow companies to categorize, access, interpret, and collaborate around company data across multiple data sources, while maintaining a high level of governance and access management. Artificial intelligence is key to many features of machine learning data catalogs, enabling functionality such as machine learning recommendations, natural language querying, and dynamic data masking for enhanced security purposes. Companies can utilize machine learning data catalogs to maintain data sets in a single location so that searching for and discovering data is simple for everyday business users and analysts alike. Users have the ability to comment on, share, and recommend data sets so colleagues can have an immediate understanding of what they are querying. Additionally, IT administrators can put into place user provisioning to ensure unauthorized employees are not accessing sensitive data. Machine learning data catalogs are most frequently implemented by companies that have multiple data sources, are searching for one source of truth, and are attempting to scale data usage company-wide. These products are generally administered by IT departments, who can maintain organization and security, but data can be accessed by data scientists or analysts and the average business user. The data can then be transformed, modeled, and visualized either directly in the machine learning data catalog or through an integration with [business intelligence software](https://www.g2.com/categories/business-intelligence). It should be noted that not all machine learning data catalogs provide data preparation capabilities and may require an integration with a [business intelligence platform](https://www.g2.com/categories/business-intelligence-platforms). Additionally, these tools differ from [master data management software](https://www.g2.com/categories/master-data-management-mdm) due to their enhanced governance, collaboration, and machine learning functionality. To qualify for inclusion in the Machine Learning Data Catalog category, a product must: - Organize and consolidate data from all company sources in a single repository - Provide user access management for security and data governance purposes - Allow business users to search and access the data from within the catalog - Offer collaboration features around data sets, including categorizing, commenting, and sharing - Give intelligent recommendations based on machine learning for quicker access to relevant data ## How Many Machine Learning Data Catalog Software Products Does G2 Track? **Total Products under this Category:** 90 ### Category Stats (Jun 2026) - **Average Rating**: 4.38/5 The average rating of products in this category, based on all submitted ratings - **Top Trending Product**: BMC AMI Data (+1.1%) - Among all products in this category, BMC AMI Data recorded the largest rating increase compared to last month *Last updated: June 24, 2026* ## How Does G2 Rank Machine Learning Data Catalog Software Products? **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 1,800+ Authentic Reviews - 90+ Products - Unbiased Rankings G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category. ## Which Machine Learning Data Catalog Software Is Best for Your Use Case? - **Leader:** [Atlan](https://www.g2.com/products/atlan/reviews) - **Highest Performer:** [Collibra](https://www.g2.com/products/collibra/reviews) - **Easiest to Use:** [AWS Glue](https://www.g2.com/products/aws-glue/reviews) - **Top Trending:** [Atlan](https://www.g2.com/products/atlan/reviews) - **Best Free Software:** [Alation](https://www.g2.com/products/alation/reviews) --- **Sponsored** ### Cloudera Cloudera is the only hybrid data and AI platform company that large organizations trust to bring AI to their data anywhere it lives. Unlike other providers, Cloudera delivers a consistent cloud experience that converges public clouds, on-prem data centers, and the edge, leveraging a proven open-source foundation. As the pioneer in big data, Cloudera empowers businesses to apply AI and assert control over 100% of their data, in all forms, improving security, governance, and real-time and predictive insights. The world’s largest brands across all industries rely on Cloudera to transform decision-making and ultimately boost bottom lines, safeguard against threats, and save lives. The Cloudera data and AI platform includes: Cloudera AI: Deploy and scale any AI model, anywhere. Cloudera brings compute to governed data where it lives for Private AI anywhere by design. Complete control, security, and governance of mission-critical data, models, agents, and inference ensure faster sovereign AI deployments. Cloudera Data-in-Motion: Make fast decisions from real-time data anywhere. Move data with any structure from any source to any destination seamlessly across hybrid environments, enabling in-the-moment business-critical decisions by processing and analyzing real-time data anywhere, from the edge to AI, as business happens. Cloudera Open Data Lakehouse: Process any data, anywhere, for actionable insights. Make smart decisions with an open data lakehouse powered by Apache Iceberg that delivers trusted, reliable, and unified data to fuel agents, AI applications, and analytics, improving collaboration, breaking silos, and simplifying sharing. Cloudera Unified Data Fabric: Unify security and governance across the entire data estate. Move beyond fragmented data management: Break down silos and connect disparate data sources intelligently and securely to provide a unified view of all organizational data and centralized end-to-end control across complex hybrid data environments. [Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list&secure%5Bcategory_id%5D=1383&secure%5Bdisplayable_resource_id%5D=1383&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=1383&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=1886&secure%5Bresource_id%5D=1383&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fmachine-learning-data-catalog&secure%5Btoken%5D=305af5b6a7dab4ce261f79d540ff419bea4582ff666cb29ac526c1ad41ade0af&secure%5Burl%5D=https%3A%2F%2Fwww.cloudera.com%2Fproducts%2Fcloudera-data-platform%2Fcdp-demos.html%3Finternal_link%3Dp18%23get-started&secure%5Burl_type%5D=custom_url) --- ## What Are the Top-Rated Machine Learning Data Catalog Software Products in 2026? ### 1. [Atlan](https://www.g2.com/products/atlan/reviews) Atlan is the context layer for enterprise AI. It continuously reads your warehouses, databases, pipelines, BI tools, and business systems to reverse construct an enterprise data graph that captures assets, lineage, entities, metrics, policies, and relationships. On top of that graph, it enriches and curates machine-readable semantics — descriptions, popular joins, KPI and metric definitions, ontologies, and business rules — and organizes them into governed, versioned context repos: bounded bundles of context that reflect how your company defines key concepts and makes decisions. These context repos are then exposed through open interfaces (SQL, APIs, SDKs, OSI/MCP-style protocols) so that agents, copilots, and AI applications can call the same trusted context in real time, rather than each team hard-coding its own logic. Human-on-the-loop governance workflows for conflict resolution, deprecation, feedback, and certification keep that context trustworthy as the business, data, and models evolve. **Average Rating:** 4.5/5.0 **Total Reviews:** 131 **How Do G2 Users Rate Atlan?** - **Ease of Use:** 8.9/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 9.1/10 (Category avg: 8.6/10) - **Metadata Management :** 9.3/10 (Category avg: 8.4/10) - **Data Lineage:** 9.3/10 (Category avg: 8.7/10) **Who Is the Company Behind Atlan?** - **Seller:** [Atlan](https://www.g2.com/sellers/atlan) - **Company Website:** https://www.atlan.com - **Year Founded:** 2019 - **HQ Location:** New York, US - **Twitter:** @AtlanHQ (9,804 Twitter followers) - **LinkedIn® Page:** https://in.linkedin.com/company/atlan-hq (572 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Financial Services, Information Technology and Services - **Company Size:** 52% Mid-Market, 41% Enterprise #### What Are Atlan's Pros and Cons? **Pros:** - Ease of Use (7 reviews) - Features (6 reviews) - Collaboration (5 reviews) - Data Cataloging (5 reviews) - Easy Setup (4 reviews) **Cons:** - Integration Issues (4 reviews) - Dependency Issues (3 reviews) - Limited Customization (3 reviews) - Technical Issues (3 reviews) - User Interface Issues (3 reviews) ### What Do G2 Reviewers Say About Atlan? *AI-generated summary from verified user reviews* **Pros:** - Users value Atlan's **ease of use** , making data collaboration and discovery a seamless experience for everyone. - Users love Atlan for its **great data discovery and collaboration features** , making data management effortless and efficient. - Users value Atlan for its **s seamless data collaboration** , enhancing teamwork and fostering trust in data management. - Users appreciate the **ease of data discovery and collaboration** with Atlan, enhancing their data management experience. - Users value the **easy setup** of Atlan, which streamlines implementation and enhances collaborative data experiences seamlessly. **Cons:** - Users face **integration issues** with Teams and non-native databases, complicating workflows and requiring extra setup. - Users note significant **dependency issues** with Atlan, causing barriers to effective use and integration with other tools. - Users note the **limited customization** options in Atlan, making it challenging to tailor the experience to specific workflows. - Users experience **slow technical support and occasional inaccuracies** , impacting their overall satisfaction with Atlan. - Users face challenges with the **limited customization and technical UI** , resulting in a steeper learning curve for business users. #### What Are Recent G2 Reviews of Atlan? **"[Helpful UI, Flexible Data Model, and Great API](https://www.g2.com/survey_responses/atlan-review-12518328)"** **Rating:** 4.0/5.0 stars *— Verified User in Health, Wellness and Fitness* [Read full review](https://www.g2.com/survey_responses/atlan-review-12518328) --- **"[Outstanding AI Features, Easy UI, and a Truly Responsive Atlan Team](https://www.g2.com/survey_responses/atlan-review-12721177)"** **Rating:** 4.5/5.0 stars *— Verified User in Apparel & Fashion* [Read full review](https://www.g2.com/survey_responses/atlan-review-12721177) --- ### 2. [AWS Glue](https://www.g2.com/products/aws-glue/reviews) AWS Glue is a serverless data integration service that makes it easier for analytics users to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning, and application develop-ment. You can discover and connect to 70+ diverse data sources, manage your data in a centralized data catalog, and visually create, run, and monitor ETL pipelines to load data into your data lakes. You can im-mediately search and query catalogued data using Amazon Athena, Amazon EMR, and Amazon Redshift Spectrum. **Average Rating:** 4.3/5.0 **Total Reviews:** 194 **How Do G2 Users Rate AWS Glue?** - **Ease of Use:** 8.4/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 8.9/10 (Category avg: 8.6/10) - **Metadata Management :** 8.6/10 (Category avg: 8.4/10) - **Data Lineage:** 8.7/10 (Category avg: 8.7/10) **Who Is the Company Behind AWS Glue?** - **Seller:** [Amazon Web Services (AWS)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd) - **Year Founded:** 2006 - **HQ Location:** Seattle, WA - **Twitter:** @awscloud (2,232,483 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/amazon-web-services/ (156,424 employees on LinkedIn®) - **Ownership:** NASDAQ: AMZN **Who Uses This Product?** - **Who Uses This:** Data Engineer, Software Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 49% Enterprise, 29% Mid-Market #### What Are AWS Glue's Pros and Cons? **Pros:** - Ease of Use (6 reviews) - Data Integration (3 reviews) - ETL Solutions (3 reviews) - Features (3 reviews) - Simple (3 reviews) **Cons:** - Slow Performance (3 reviews) - Debugging Difficulty (2 reviews) - Difficult Debugging (2 reviews) - Performance Issues (2 reviews) - Time-Consuming (2 reviews) ### What Do G2 Reviewers Say About AWS Glue? *AI-generated summary from verified user reviews* **Pros:** - Users value the **ease of use** of AWS Glue, finding it straightforward for data preparation and analytics tasks. - Users appreciate the **seamless data integration** capabilities of AWS Glue, enabling efficient data movement and transformation. - Users appreciate the **fully managed ETL service** of AWS Glue, enjoying seamless integration and ease of use. - Users appreciate the **functionality and versatility** of AWS Glue, enabling easy data discovery and job execution. - Users value the **ease of implementation** in AWS Glue, enhancing data integration and error tracing for scripts. **Cons:** - Users experience **slow performance** with AWS Glue, particularly during startup and debugging, which can hinder productivity. - Users find **debugging difficult** in AWS Glue due to unclear error messages and a steep learning curve. - Users often face **difficult debugging** processes in AWS Glue, complicating the troubleshooting experience and prolonging job startups. - Users experience **performance issues** with AWS Glue, including slow start-up times and complex debugging processes. - Users find AWS Glue **time-consuming** due to slow startup times and complex debugging processes, especially for beginners. #### What Are Recent G2 Reviews of AWS Glue? **"[Serverless ETL Made Easy with AWS Glue](https://www.g2.com/survey_responses/aws-glue-review-12864874)"** **Rating:** 5.0/5.0 stars *— mani s.* [Read full review](https://www.g2.com/survey_responses/aws-glue-review-12864874) --- **"[AWS Glue Makes ETL Simple with Serverless Scalability and Deep AWS Integration](https://www.g2.com/survey_responses/aws-glue-review-12380790)"** **Rating:** 4.5/5.0 stars *— Pradip G.* [Read full review](https://www.g2.com/survey_responses/aws-glue-review-12380790) --- #### What Are G2 Users Discussing About AWS Glue? - [What is AWS Glue and how it works?](https://www.g2.com/discussions/what-is-aws-glue-and-how-it-works) - 1 comment - [What does AWS Glue do?](https://www.g2.com/discussions/what-does-aws-glue-do) - 2 comments - [What are the main components of AWS Glue?](https://www.g2.com/discussions/what-are-the-main-components-of-aws-glue) - 2 comments - [What are the features of glue?](https://www.g2.com/discussions/what-are-the-features-of-glue) - 1 comment ### 3. [Alation](https://www.g2.com/products/alation/reviews) Alation is the data intelligence company. Founded in 2012 and headquartered in Redwood City, California—with global offices in London and Sydney—Alation serves more than 650 enterprise customers across 34 industries. The company pioneered the modern data catalog by combining machine learning with human insight to connect people with questions to people with answers. Today, more than 40% of the Fortune 100 rely on Alation to power data and AI initiatives at scale. Alation’s platform unifies cataloging, governance, and data quality with new AI-native capabilities built on one essential foundation: metadata. Metadata provides the context AI models lack, delivering outputs that are accurate, explainable, and trustworthy. With capabilities like Agent Studio, CDE Manager, and Data Quality Agent, organizations can build agents that understand their unique definitions, rules, and quality standards. Embedded readiness checks and continuous evaluation ensure every AI workflow is grounded in the right metadata context, making enterprise AI reliable enough for real production use. **Average Rating:** 4.4/5.0 **Total Reviews:** 89 **How Do G2 Users Rate Alation?** - **Ease of Use:** 8.3/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 8.7/10 (Category avg: 8.6/10) - **Metadata Management :** 7.9/10 (Category avg: 8.4/10) - **Data Lineage:** 7.2/10 (Category avg: 8.7/10) **Who Is the Company Behind Alation?** - **Seller:** [Alation](https://www.g2.com/sellers/alation) - **Company Website:** https://alation.com - **Year Founded:** 2012 - **HQ Location:** Redwood City, CA - **Twitter:** @Alation (3,567 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/3231829/ (621 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Information Technology and Services, Financial Services - **Company Size:** 57% Enterprise, 27% Mid-Market #### What Are Alation's Pros and Cons? **Pros:** - Ease of Use (16 reviews) - Data Discovery (10 reviews) - User Experience (10 reviews) - Data Cataloging (9 reviews) - User Interface (9 reviews) **Cons:** - Slow Performance (8 reviews) - Missing Features (6 reviews) - Limited Functionality (4 reviews) - Lineage Limitations (4 reviews) - User Interface Issues (4 reviews) ### What Do G2 Reviewers Say About Alation? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of navigation** in Alation, making information retrieval swift and intuitively organized. - Users value the **user-friendly data discovery** experience in Alation, enhancing collaboration and understanding across data sources. - Users appreciate Alation's **user-friendly interface** , enabling efficient navigation and seamless connections between project documents. - Users value the **user-friendly interface** and governance workflows of Alation, simplifying data discovery and collaboration. - Users appreciate Alation's **intuitive user interface** , enhancing navigation and productivity while simplifying data discovery and documentation. **Cons:** - Users report **slow performance** issues with Alation, particularly during search and data ingestion, impacting overall efficiency. - Users identify **missing features** in Alation, particularly regarding Data Quality and enhanced AI capabilities. - Users note the **limited functionality** of Alation, particularly lacking in features like Data Quality and essential integrations. - Users express frustration with **lineage limitations** , citing bugs, inconsistent support, and a lack of reliable UI features. - Users find the **user interface lacking** , indicating a need for simplification and improved intuitiveness for better navigation. #### What Are Recent G2 Reviews of Alation? **"[Exceptional Tool and Team, Expanding Our Data Governance](https://www.g2.com/survey_responses/alation-review-12007948)"** **Rating:** 5.0/5.0 stars *— Eric N.* [Read full review](https://www.g2.com/survey_responses/alation-review-12007948) --- **"[A Solid Product With Areas for Refinement](https://www.g2.com/survey_responses/alation-review-11980120)"** **Rating:** 5.0/5.0 stars *— Melissa B.* [Read full review](https://www.g2.com/survey_responses/alation-review-11980120) --- #### What Are G2 Users Discussing About Alation? - [Is Alation a database?](https://www.g2.com/discussions/is-alation-a-database) - [Which three are capabilities of Oracle Cloud Infrastructure data catalog service?](https://www.g2.com/discussions/which-three-are-capabilities-of-oracle-cloud-infrastructure-data-catalog-service) - 1 comment - [Is Alation good?](https://www.g2.com/discussions/is-alation-good) - [What does Alation software do?](https://www.g2.com/discussions/what-does-alation-software-do) ### 4. [Google Cloud Data Catalog](https://www.g2.com/products/google-cloud-data-catalog/reviews) A fully managed and highly scalable data discovery and metadata management service. **Average Rating:** 4.4/5.0 **Total Reviews:** 25 **How Do G2 Users Rate Google Cloud Data Catalog?** - **Ease of Use:** 8.7/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 8.5/10 (Category avg: 8.6/10) - **Metadata Management :** 9.1/10 (Category avg: 8.4/10) - **Data Lineage:** 7.8/10 (Category avg: 8.7/10) **Who Is the Company Behind Google Cloud Data Catalog?** - **Seller:** [Google](https://www.g2.com/sellers/google) - **Year Founded:** 1998 - **HQ Location:** Mountain View, CA - **Twitter:** @google (31,899,995 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1441/ (341,888 employees on LinkedIn®) - **Ownership:** NASDAQ:GOOG **Who Uses This Product?** - **Top Industries:** Computer Software - **Company Size:** 46% Small-Business, 29% Mid-Market #### What Are Recent G2 Reviews of Google Cloud Data Catalog? **"[Best centralised approach for GCP Projects](https://www.g2.com/survey_responses/google-cloud-data-catalog-review-7589215)"** **Rating:** 4.5/5.0 stars *— Nirav D.* [Read full review](https://www.g2.com/survey_responses/google-cloud-data-catalog-review-7589215) --- **"[The Google Cloud Data Catalog is a fantastic offering.](https://www.g2.com/survey_responses/google-cloud-data-catalog-review-7586462)"** **Rating:** 5.0/5.0 stars *— Pranav R.* [Read full review](https://www.g2.com/survey_responses/google-cloud-data-catalog-review-7586462) --- ### 5. [Appen](https://www.g2.com/products/appen/reviews) Appen collects and labels images, text, speech, audio, video, and other data to create training data used to build and continuously improve the world’s most innovative artificial intelligence systems. We offer a state of the art, licensable data annotation platform to annotate training data use cases in computer vision and natural language processing. Our platform enhances accuracy and efficiency through our Smart Labeling and Pre-Labeling features which use Machine Learning to ease human annotations. You choose the level of service and security you want for data collection and annotation, from white-glove managed service to flexible self-service. Our expertise includes having a global crowd of over 1 million skilled contractors who speak over 235 languages and dialects, in over 70,000 locations and 170 countries, and the industry’s most advanced AI-assisted data annotation platform. Our reliable training data gives leaders in technology, automotive, financial services, retail, healthcare, and governments the confidence to deploy world-class AI products. Founded in 1996, Appen has customers and offices globally. **Average Rating:** 4.2/5.0 **Total Reviews:** 33 **How Do G2 Users Rate Appen?** - **Ease of Use:** 8.2/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 8.2/10 (Category avg: 8.6/10) - **Metadata Management :** 8.0/10 (Category avg: 8.4/10) - **Data Lineage:** 7.8/10 (Category avg: 8.7/10) **Who Is the Company Behind Appen?** - **Seller:** [Appen](https://www.g2.com/sellers/appen) - **Year Founded:** 1996 - **HQ Location:** Kirkland, Washington, United States - **LinkedIn® Page:** https://www.linkedin.com/company/appen (20,647 employees on LinkedIn®) - **Ownership:** ASX:APX - **Total Revenue (USD mm):** $244,900 **Who Uses This Product?** - **Top Industries:** Information Technology and Services - **Company Size:** 54% Small-Business, 26% Enterprise #### What Are Appen's Pros and Cons? **Pros:** - Useful (2 reviews) - Ease of Use (1 reviews) - Flexibility (1 reviews) **Cons:** - Work Interruptions (3 reviews) - Low Compensation (2 reviews) - Complexity (1 reviews) - Connectivity Issues (1 reviews) - User Interface Issues (1 reviews) ### What Do G2 Reviewers Say About Appen? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **flexibility and variety** that Appen offers, making tasks engaging and enjoyable to complete. - Users value the **ease of use** of Appen, enabling task completion effortlessly via their cell phones. - Users appreciate the **flexibility** of Appen, enabling engagement with diverse and interesting projects for a more enjoyable experience. **Cons:** - Users experience **work interruptions** due to inconsistent availability and lengthy qualification processes that hinder project selection. - Users find the **low compensation** and inconsistent work availability makes it hard to rely on Appen for a steady income. - Users find the **navigation confusing** and frequently experience issues like being kicked out of the app. - Users experience **connectivity issues** with Appen, leading to confusion and being frequently disconnected. - Users find Appen's interface to be **confusing and prone to crashes** , affecting their overall user experience. #### What Are Recent G2 Reviews of Appen? **"[Robust Crowdsourcing Platform for AI and Language Tasks](https://www.g2.com/survey_responses/appen-review-12769449)"** **Rating:** 4.0/5.0 stars *— Sina A.* [Read full review](https://www.g2.com/survey_responses/appen-review-12769449) --- **"[Ideal for Freelancers, Simplicity with Room for Support Improvement](https://www.g2.com/survey_responses/appen-review-12550258)"** **Rating:** 5.0/5.0 stars *— Ashish S.* [Read full review](https://www.g2.com/survey_responses/appen-review-12550258) --- ### 6. [erwin Data Modeler](https://www.g2.com/products/quest-software-erwin-data-modeler/reviews) Part of the Quest erwin Data Management Platform, delivering industry-leading enterprise data modeling. erwin Data Modeler provides the blueprints for trusted data. Integrated with erwin Data Intelligence, it connects models to governed metadata and business context - ensuring that what’s delivered in production matches the design, so data products are accurate, governed, and AI-ready. **Average Rating:** 4.2/5.0 **Total Reviews:** 92 **How Do G2 Users Rate erwin Data Modeler?** - **Ease of Use:** 8.5/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 8.3/10 (Category avg: 8.6/10) - **Metadata Management :** 8.3/10 (Category avg: 8.4/10) - **Data Lineage:** 8.1/10 (Category avg: 8.7/10) **Who Is the Company Behind erwin Data Modeler?** - **Seller:** [Quest Software](https://www.g2.com/sellers/quest-software) - **Company Website:** https://www.quest.com - **Year Founded:** 1987 - **HQ Location:** Austin, TX - **Twitter:** @Quest (17,109 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/2880/ (3,569 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 38% Mid-Market, 38% Small-Business #### What Are erwin Data Modeler's Pros and Cons? **Pros:** - Ease of Use (3 reviews) - Collaboration (2 reviews) - Data Discovery (1 reviews) - Data Governance (1 reviews) - Data Management (1 reviews) **Cons:** - Expensive (2 reviews) - Complexity (1 reviews) - Difficult Interface (1 reviews) - Limited Customization (1 reviews) - Outdated Design (1 reviews) ### What Do G2 Reviewers Say About erwin Data Modeler? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of erwin Data Modeler, facilitating clear and structured data visualization and collaboration. - Users praise the **collaboration features** of erwin Data Modeler, enhancing teamwork between technical and business teams effectively. - Users appreciate the **clarity in data visualization** offered by erwin Data Modeler, simplifying database design and collaboration. - Users value the **ease of data governance** with erwin Data Modeler, enhancing collaboration and clarity for teams. - Users value the **versatile data management** capabilities of erwin Data Modeler for both on-premises and cloud environments. **Cons:** - Users are concerned about the **high cost** of erwin Data Modeler, which limits its accessibility for many. - Users find the **complexity of the interface** challenging, particularly for newcomers and when handling large models. - Users find the **difficult interface** of erwin Data Modeler challenging, especially for those unfamiliar with data modeling. - Users find the **limited customization options** of erwin Data Modeler restricts their ability to tailor the tool to their needs. - Users find the **outdated design** of erwin Data Modeler makes it challenging for new users to adapt effectively. #### What Are Recent G2 Reviews of erwin Data Modeler? **"[A Serious, Professional Data Modeling Tool That Keeps Docs and Design Aligned](https://www.g2.com/survey_responses/erwin-data-modeler-review-12949097)"** **Rating:** 4.5/5.0 stars *— Dmitry A.* [Read full review](https://www.g2.com/survey_responses/erwin-data-modeler-review-12949097) --- **"[Powerful Reverse/Forward Engineering for Clear Database Models and Clean DDL](https://www.g2.com/survey_responses/erwin-data-modeler-review-12975392)"** **Rating:** 4.0/5.0 stars *— Animesh B.* [Read full review](https://www.g2.com/survey_responses/erwin-data-modeler-review-12975392) --- #### What Are G2 Users Discussing About erwin Data Modeler? - [How much does Erwin Data Modeler cost?](https://www.g2.com/discussions/how-much-does-erwin-data-modeler-cost) - [What software is used for data Modelling?](https://www.g2.com/discussions/what-software-is-used-for-data-modelling) - [What does a data modeler program do?](https://www.g2.com/discussions/what-does-a-data-modeler-program-do) - [What is Erwin Data Modeler used for?](https://www.g2.com/discussions/what-is-erwin-data-modeler-used-for) ### 7. [Collibra](https://www.g2.com/products/collibra/reviews) Try Collibra for free @ Collibra.com/tour Collibra is for organizations with complex data challenges, hybrid data ecosystems—and big ambitions for data and AI. We help organizations who are trying to accelerate data and AI use cases while ensuring compliance, but are struggling with fragmented governance and visibility across the whole hybrid data ecosystem. Collibra unifies governance for data and AI across every system, data source and user—to create safe autonomy and a foundation for scaling AI and data use cases. With Collibra, you can accelerate all your data and AI use cases, safely and with well–understood data. That’s Data Confidence. **Average Rating:** 4.2/5.0 **Total Reviews:** 99 **How Do G2 Users Rate Collibra?** - **Ease of Use:** 8.0/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 8.3/10 (Category avg: 8.6/10) - **Metadata Management :** 8.0/10 (Category avg: 8.4/10) - **Data Lineage:** 8.0/10 (Category avg: 8.7/10) **Who Is the Company Behind Collibra?** - **Seller:** [Collibra](https://www.g2.com/sellers/collibra) - **Company Website:** https://www.collibra.com - **Year Founded:** 2008 - **HQ Location:** New York, New York - **Twitter:** @collibra (5,756 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/288365/ (1,082 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Financial Services, Banking - **Company Size:** 72% Enterprise, 19% Mid-Market #### What Are Collibra's Pros and Cons? **Pros:** - Features (10 reviews) - Data Management (9 reviews) - Collaboration (7 reviews) - Ease of Use (7 reviews) - Integrations (7 reviews) **Cons:** - Complexity Issues (7 reviews) - Limited Functionality (6 reviews) - Complexity (5 reviews) - Integration Issues (5 reviews) - User Interface Issues (5 reviews) ### What Do G2 Reviewers Say About Collibra? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **unified data intelligence platform** of Collibra, which enhances collaboration between Business and IT. - Users value Collibra for its **comprehensive data management** capabilities, enhancing alignment between Business and IT teams. - Users appreciate the **collaboration features** of Collibra, enhancing alignment between Business and IT on a unified platform. - Users find Collibra to be **intuitive and easy to configure** , enhancing their data governance experience significantly. - Users value the **seamless integration capabilities** of Collibra, enhancing data ecosystem efficiency and governance. **Cons:** - Users experience **complexity issues** with Collibra, making onboarding and system navigation challenging and frustrating. - Users experience **limited functionality** in Collibra due to complex navigation and unintuitive language, hindering effective use. - Users find the **complexity of Collibra** overwhelming, hindering productivity and complicating crucial processes like approvals and onboarding. - Users face **integration issues** with Collibra, leading to cumbersome workflows and inconsistent connections with other tools. - Users experience **navigation and accessibility issues** with Collibra, which hinder user engagement and complicate the workflow. #### What Are Recent G2 Reviews of Collibra? **"[Collibra Data Quality Module](https://www.g2.com/survey_responses/collibra-review-7563210)"** **Rating:** 5.0/5.0 stars *— Frank L.* [Read full review](https://www.g2.com/survey_responses/collibra-review-7563210) --- **"[Powerful Data Governance and Quality Platform](https://www.g2.com/survey_responses/collibra-review-12128662)"** **Rating:** 5.0/5.0 stars *— Katerina V.* [Read full review](https://www.g2.com/survey_responses/collibra-review-12128662) --- #### What Are G2 Users Discussing About Collibra? - [What is Collibra data governance tool?](https://www.g2.com/discussions/what-is-collibra-data-governance-tool) - [Is Collibra a good tool?](https://www.g2.com/discussions/is-collibra-a-good-tool) - [What can Collibra do?](https://www.g2.com/discussions/what-can-collibra-do) - [What are the features of Collibra?](https://www.g2.com/discussions/what-are-the-features-of-collibra) ### 8. [decube](https://www.g2.com/products/decube/reviews) Decube is a Context Layer platform specifically designed for the AI era, providing organizations with the ability to give their data meaning, memory, and trust. This innovative system integrates various components such as metadata management, automated lineage tracking, data quality assurance, and observability to create a comprehensive real-time map of data dynamics. By understanding how data operates, flows, and its reliability, Decube empowers enterprises to make informed decisions and effectively manage AI workloads. Targeted primarily at enterprises that rely heavily on data-driven decision-making, Decube addresses a critical challenge faced by many organizations: the lack of contextual understanding of their data. In an age where data is abundant, the real issue lies in the ability to interpret and utilize that data effectively. Decube provides a connected understanding of the entire data ecosystem, which helps eliminate blind spots and enhances governance. This contextual awareness is essential for organizations looking to leverage AI technologies and ensure that their models, dashboards, and agents operate with greater intelligence and safety. Key features of Decube include its robust metadata management capabilities, which allow users to track and manage data lineage effortlessly. This feature ensures that organizations can trace the origins and transformations of their data, thereby enhancing transparency and accountability. Additionally, Decube’s focus on data quality means that users can trust the information they are working with, reducing the risk of errors in critical decision-making processes. The observability aspect of the platform further enables organizations to monitor data flows in real-time, ensuring that any issues can be identified and addressed promptly. The benefits of using Decube extend beyond mere data management. By providing a living, interconnected understanding of data, Decube enhances the overall operational confidence of organizations. This platform not only strengthens governance but also facilitates smarter decision-making by ensuring that all data-driven models are built on a foundation of reliable and contextualized information. As businesses increasingly depend on trustworthy data and AI-ready infrastructure, Decube stands out as a vital tool that equips them with the necessary context to navigate the complexities of the modern data landscape. **Average Rating:** 4.6/5.0 **Total Reviews:** 23 **How Do G2 Users Rate decube?** - **Ease of Use:** 9.4/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 9.6/10 (Category avg: 8.6/10) - **Metadata Management :** 9.6/10 (Category avg: 8.4/10) - **Data Lineage:** 9.6/10 (Category avg: 8.7/10) **Who Is the Company Behind decube?** - **Seller:** [Decube Data](https://www.g2.com/sellers/decube-data) - **Company Website:** https://decube.io - **Year Founded:** 2022 - **HQ Location:** Kuala Lumpur - **Twitter:** @decube_data (113 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/decube-data/ (44 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Information Technology and Services - **Company Size:** 39% Mid-Market, 35% Small-Business #### What Are decube's Pros and Cons? **Pros:** - User Interface (8 reviews) - Ease of Use (7 reviews) - Features (7 reviews) - Data Quality (6 reviews) - Insights (6 reviews) **Cons:** - Limited Functionality (3 reviews) - Complex Setup (2 reviews) - Limited Features (2 reviews) - Missing Features (2 reviews) - Poor Customer Support (2 reviews) ### What Do G2 Reviewers Say About decube? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **intuitive and simplified UI** of Decube, enabling easy data monitoring and insights. - Users find Decube's interface **easy to use** , with a simple dashboard and intuitive setup for data monitoring. - Users appreciate the **comprehensive data governance features** of Decube, enhancing reliability and discoverability for teams. - Users value Decube for its **exceptional data quality maintenance** , ensuring accurate and reliable data for informed decision-making. - Users value Decube for its **intuitive design and transparency** , enhancing data quality and collaboration across teams. **Cons:** - Users find **limited functionality** in decube, requiring extra effort for advanced insights and manual configurations. - Users find the **complex setup** of Decube challenging, requiring significant time and effort for initial configuration. - Users find **limited features** in Decube, requiring extra effort to access deeper data insights and integrations. - Users find the **missing features** like API-based monitoring and group-by options limiting their experience with Decube. - Users often face **poor customer support** , making it difficult to get timely and accurate assistance when needed. #### What Are Recent G2 Reviews of decube? **"[Effortless Data Quality and Trust with Decube](https://www.g2.com/survey_responses/decube-review-11920093)"** **Rating:** 4.5/5.0 stars *— Ahsan Y.* [Read full review](https://www.g2.com/survey_responses/decube-review-11920093) --- **"[Comprehensive Data Trust Platform with Powerful Features, but Support Needs Improvement](https://www.g2.com/survey_responses/decube-review-11833181)"** **Rating:** 5.0/5.0 stars *— Sivani V.* [Read full review](https://www.g2.com/survey_responses/decube-review-11833181) --- ### 9. [Cloudera](https://www.g2.com/products/cloudera/reviews) Cloudera is the only hybrid data and AI platform company that large organizations trust to bring AI to their data anywhere it lives. Unlike other providers, Cloudera delivers a consistent cloud experience that converges public clouds, on-prem data centers, and the edge, leveraging a proven open-source foundation. As the pioneer in big data, Cloudera empowers businesses to apply AI and assert control over 100% of their data, in all forms, improving security, governance, and real-time and predictive insights. The world’s largest brands across all industries rely on Cloudera to transform decision-making and ultimately boost bottom lines, safeguard against threats, and save lives. The Cloudera data and AI platform includes: Cloudera AI: Deploy and scale any AI model, anywhere. Cloudera brings compute to governed data where it lives for Private AI anywhere by design. Complete control, security, and governance of mission-critical data, models, agents, and inference ensure faster sovereign AI deployments. Cloudera Data-in-Motion: Make fast decisions from real-time data anywhere. Move data with any structure from any source to any destination seamlessly across hybrid environments, enabling in-the-moment business-critical decisions by processing and analyzing real-time data anywhere, from the edge to AI, as business happens. Cloudera Open Data Lakehouse: Process any data, anywhere, for actionable insights. Make smart decisions with an open data lakehouse powered by Apache Iceberg that delivers trusted, reliable, and unified data to fuel agents, AI applications, and analytics, improving collaboration, breaking silos, and simplifying sharing. Cloudera Unified Data Fabric: Unify security and governance across the entire data estate. Move beyond fragmented data management: Break down silos and connect disparate data sources intelligently and securely to provide a unified view of all organizational data and centralized end-to-end control across complex hybrid data environments. **Average Rating:** 4.1/5.0 **Total Reviews:** 131 **How Do G2 Users Rate Cloudera?** - **Ease of Use:** 8.3/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 8.9/10 (Category avg: 8.6/10) - **Metadata Management :** 9.1/10 (Category avg: 8.4/10) - **Data Lineage:** 8.8/10 (Category avg: 8.7/10) **Who Is the Company Behind Cloudera?** - **Seller:** [Cloudera](https://www.g2.com/sellers/cloudera) - **Company Website:** https://www.cloudera.com - **Year Founded:** 2008 - **HQ Location:** Santa Clara, CA - **Twitter:** @cloudera (106,442 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/229433/ (3,446 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Engineer, Software Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 42% Enterprise, 32% Small-Business #### What Are Cloudera's Pros and Cons? **Pros:** - Ease of Use (22 reviews) - Scalability (17 reviews) - Security (9 reviews) - Data Management (8 reviews) - Features (8 reviews) **Cons:** - Expensive (16 reviews) - Complexity (7 reviews) - Difficult Learning (5 reviews) - Poor Documentation (4 reviews) - Access Issues (3 reviews) ### What Do G2 Reviewers Say About Cloudera? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **brilliant user interface** of Cloudera, highlighting its ease of use for big data management. - Users praise Cloudera for its **easy scalability** , effectively managing large data volumes with seamless performance. - Users value the **robust security** features of Cloudera, ensuring dependable and safe data management for their analytics needs. - Users appreciate the **comprehensive tools** of Cloudera, enhancing their experience in big data management and analytics. - Users value the **scalability and ease of use** of Cloudera, enhancing data processing and administration efficiency. **Cons:** - Users note that Cloudera is quite **expensive** , with high costs and a small team required for effective management. - Users find Cloudera's DB to be **highly complex** , making SQL queries and customization challenging, especially for beginners. - Users find Cloudera's setup a bit **difficult to learn** , especially for beginners needing clearer guidance and tutorials. - Users find the **poor documentation** of Cloudera challenging, impacting their ability to navigate and troubleshoot effectively. - Users experience **access issues** with Cloudera, facing unauthorized errors and limited documentation support, affecting usability. #### What Are Recent G2 Reviews of Cloudera? **"[Reliable Platform for Managing Large-Scale Data Pipelines](https://www.g2.com/survey_responses/cloudera-review-11455117)"** **Rating:** 4.5/5.0 stars *— Paritosh C.* [Read full review](https://www.g2.com/survey_responses/cloudera-review-11455117) --- **"[Easy to Use, Reliable, and Great for Team Collaboration](https://www.g2.com/survey_responses/cloudera-review-12695378)"** **Rating:** 4.0/5.0 stars *— Verified User in Computer Software* [Read full review](https://www.g2.com/survey_responses/cloudera-review-12695378) --- #### What Are G2 Users Discussing About Cloudera? - [What is Cloudera used for?](https://www.g2.com/discussions/what-is-cloudera-used-for) - 1 comment - [What is Hortonworks Data Platform used for?](https://www.g2.com/discussions/what-is-hortonworks-data-platform-used-for) - [What is Cloudera Data Flow used for?](https://www.g2.com/discussions/what-is-cloudera-data-flow-used-for) - [What is Cloudera Navigator used for?](https://www.g2.com/discussions/what-is-cloudera-navigator-used-for) - [What is Cloudera Data Engineering used for?](https://www.g2.com/discussions/what-is-cloudera-data-engineering-used-for) ### 10. [Select Star](https://www.g2.com/products/select-star/reviews) Select Star is a modern data governance platform that helps organizations manage and understand their data at scale, enabling AI, analytics, and self-service across the business. It automatically catalogs datasets, traces end-to-end lineage, and builds a shared business glossary and semantic layer, so teams can confidently work with trusted data. With a user-friendly data portal and built-in automation, Select Star supports use cases including data democratization, data governance, semantic layers, and cloud data migrations serving as a foundational layer for enterprise AI and data initiatives. **Average Rating:** 4.5/5.0 **Total Reviews:** 55 **How Do G2 Users Rate Select Star?** - **Ease of Use:** 8.9/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 8.2/10 (Category avg: 8.6/10) - **Metadata Management :** 8.7/10 (Category avg: 8.4/10) - **Data Lineage:** 8.9/10 (Category avg: 8.7/10) **Who Is the Company Behind Select Star?** - **Seller:** [Select Star](https://www.g2.com/sellers/select-star) - **Year Founded:** 2020 - **HQ Location:** San Francisco, CA - **Twitter:** @selectstarhq (389 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/selectstarhq/ (17 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Information Technology and Services, Real Estate - **Company Size:** 51% Mid-Market, 38% Enterprise #### What Are Select Star's Pros and Cons? **Pros:** - Ease of Use (10 reviews) - Data Lineage (9 reviews) - User Interface (7 reviews) - Data Discovery (5 reviews) - Data Cataloging (4 reviews) **Cons:** - Limited Functionality (2 reviews) - Lineage Limitations (2 reviews) - Complex Setup (1 reviews) - Difficult Learning (1 reviews) - Expertise Required (1 reviews) ### What Do G2 Reviewers Say About Select Star? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of Select Star, finding it straightforward to search and access necessary data. - Users value the **powerful column-level lineage** of Select Star, enhancing data precision and quality effortlessly. - Users appreciate the **clean and intuitive interface** of Select Star, enhancing data discovery and collaboration. - Users appreciate the **intuitive data discovery** of Select Star, enabling easy navigation and understanding of complex datasets. - Users praise Select Star for its **intuitive data cataloging** , streamlining data discovery and enhancing team collaboration. **Cons:** - Users feel the **limited functionality** of Select Star restricts vital insights like popularity and advanced reporting features. - Users find that **lineage limitations** in Select Star can complicate visualisation and access to necessary data. - Users find the **complex setup** for a dbt mesh ecosystem requires significant effort to unify projects for data feeding. - Users find the **difficult learning curve** of Select Star slows down their ability to gain value from it. - Users feel the need for **more straightforward guidance** to quickly derive value from Select Star without SQL expertise. #### What Are Recent G2 Reviews of Select Star? **"[Intuitive Data Discovery Made Effortless](https://www.g2.com/survey_responses/select-star-review-11919348)"** **Rating:** 5.0/5.0 stars *— Clara C.* [Read full review](https://www.g2.com/survey_responses/select-star-review-11919348) --- **"[Seamless Integration, Solid Support](https://www.g2.com/survey_responses/select-star-review-11904733)"** **Rating:** 5.0/5.0 stars *— Steve K.* [Read full review](https://www.g2.com/survey_responses/select-star-review-11904733) --- ### 11. [Secoda](https://www.g2.com/products/secoda/reviews) Secoda is an AI-powered data governance platform designed to help organizations explore, understand, and utilize their data effectively. By providing a comprehensive platform that connects to 75+ data sources, pipelines, warehouses, and visualization tools, Secoda aims to create a unified source of truth for businesses. This functionality is particularly valuable for organizations looking to enhance their self-serve analytics, streamline operations, and improve decision-making. Targeted at data teams, business stakeholders, and organizations of all sizes, Secoda serves as an essential tool for those who need to manage and interpret large volumes of data. Its user-friendly interface ensures that individuals with varying levels of technical expertise can leverage the platform to gain actionable insights. Companies such as Vanta, Cardinal Health, ID.me, and Dialpad have adopted Secoda to monitor the health of their data ecosystems, enhance the efficiency of their data teams, and scale AI readiness. One of Secoda’s core advantages is its ability to unify data cataloging, enterprise governance, and observability into a single, streamlined platform. This consolidation not only reduces the overhead of managing multiple tools but also powers Secoda AI with rich, connected context, enabling teams to focus on insights instead of infrastructure. Secoda automates key data management tasks including documentation, tagging, glossary term creation, and policy creation. This automation enables users to quickly discover and access relevant data and insights without extensive manual effort. By streamlining these processes, Secoda not only saves valuable time but also empowers teams to make confident, data-driven decisions based on current, well-organized information, ultimately driving better business outcomes. Overall, Secoda stands out in the data management landscape by offering a comprehensive, AI-driven solution that caters to the needs of both technical and non-technical users. Its ability to create a single source of truth, coupled with its integration of multiple functionalities into one platform, positions it as a valuable asset for organizations aiming to harness the full potential of their data. **Average Rating:** 4.5/5.0 **Total Reviews:** 55 **How Do G2 Users Rate Secoda?** - **Ease of Use:** 8.2/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 9.3/10 (Category avg: 8.6/10) - **Metadata Management :** 9.5/10 (Category avg: 8.4/10) - **Data Lineage:** 8.9/10 (Category avg: 8.7/10) **Who Is the Company Behind Secoda?** - **Seller:** [Secoda](https://www.g2.com/sellers/secoda) - **Year Founded:** 2021 - **HQ Location:** Toronto, CA - **Twitter:** @SecodaHQ (923 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/secodahq/about (19 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software, Financial Services - **Company Size:** 65% Mid-Market, 18% Small-Business #### What Are Secoda's Pros and Cons? **Pros:** - Data Lineage (7 reviews) - Onboarding (7 reviews) - Integration Capabilities (6 reviews) - Learning (6 reviews) - Data Management (5 reviews) **Cons:** - Learning Difficulty (4 reviews) - Product Immaturity (4 reviews) - Improvement Needed (3 reviews) - Limited Functionality (3 reviews) - Performance Issues (3 reviews) ### What Do G2 Reviewers Say About Secoda? *AI-generated summary from verified user reviews* **Pros:** - Users value the **effective data lineage** of Secoda, enhancing asset structure and facilitating discovery for teams. - Users appreciate the **easy onboarding process** of Secoda, empowering teams with effective data governance and support. - Users appreciate the **integration capabilities** of Secoda, seamlessly connecting with various platforms for enhanced data management. - Users value the **ease of learning** Secoda due to its intuitive design and comprehensive documentation features. - Users appreciate the **data management features** of Secoda, enabling effective collaboration and centralized knowledge sharing. **Cons:** - Users often face **learning difficulties** with Secoda's complex settings and team sharing, particularly affecting nontechnical users. - Users experience **product immaturity** with occasional bugs and the challenge of keeping up with frequent updates. - Users indicated that **improvement is needed** in usability and filtering options of Secoda for better adoption and value. - Users find Secoda's **limited functionality** disappointing, as it fails to provide clear value or support for large datasets. - Users report **performance issues** with Secoda due to bugs and syncing challenges that hinder usability and reliability. #### What Are Recent G2 Reviews of Secoda? **"[Secoda offers great integration with Snowflake, dbt, Tableau for Data Cataloging and AI assistance](https://www.g2.com/survey_responses/secoda-review-11049626)"** **Rating:** 5.0/5.0 stars *— Surya Kant M.* [Read full review](https://www.g2.com/survey_responses/secoda-review-11049626) --- **"[Making real progress with metadata, lineage, documentation and AI use cases](https://www.g2.com/survey_responses/secoda-review-11392959)"** **Rating:** 4.5/5.0 stars *— Verified User in Financial Services* [Read full review](https://www.g2.com/survey_responses/secoda-review-11392959) --- ### 12. [Coalesce Catalog (formerly CastorDoc)](https://www.g2.com/products/castor-doc/reviews) Coalesce Catalog is a collaborative, automated data discovery & catalog tool. We believe that data people spend way too much time trying to find and understand their data. Coalesce Catalog redesigns how data people collaborate. It provides a single source of truth to reference and document all the knowledge related to data within your company. If you are looking for a table related to your customers, just look for it as you would in Google, and Coalesce Catalog provides you with all the context you will need for your analysis. Inspired by internal tools developed by Uber, Airbnb, Lyft, and Spotify, Coalesce Catalog has developed a plug-and-play solution that deploys in minutes to drive value for companies of all sizes. Discover and catalog your data today with Coalesce Catalog. **Average Rating:** 4.7/5.0 **Total Reviews:** 63 **How Do G2 Users Rate Coalesce Catalog (formerly CastorDoc)?** - **Ease of Use:** 9.6/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 9.9/10 (Category avg: 8.6/10) - **Metadata Management :** 9.9/10 (Category avg: 8.4/10) - **Data Lineage:** 9.9/10 (Category avg: 8.7/10) **Who Is the Company Behind Coalesce Catalog (formerly CastorDoc)?** - **Seller:** [Coalesce](https://www.g2.com/sellers/coalesce) - **Company Website:** https://coalesce.io/ - **Year Founded:** 2020 - **HQ Location:** San Francisco, CA - **LinkedIn® Page:** https://www.linkedin.com/company/coalesceio/ (118 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Information Technology and Services, Financial Services - **Company Size:** 59% Mid-Market, 27% Enterprise #### What Are Coalesce Catalog (formerly CastorDoc)'s Pros and Cons? **Pros:** - Ease of Use (3 reviews) - Collaboration (2 reviews) - Connectivity (2 reviews) - Data Lineage (2 reviews) - Useful (2 reviews) **Cons:** - Connector Issues (1 reviews) - Integration Issues (1 reviews) - Limitations (1 reviews) ### What Do G2 Reviewers Say About Coalesce Catalog (formerly CastorDoc)? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of Coalesce Catalog, finding it simple and intuitive for data discovery and management. - Users value the **collaborative integration** with Slack, enhancing data sharing and onboarding for teams effectively. - Users appreciate the **easy connectivity** of Coalesce Catalog, allowing seamless integration and efficient data discovery. - Users value the **data lineage feature** of Coalesce Catalog for simplifying data discovery and enhancing onboarding. - Users find the **lineage feature** invaluable for simplifying data discovery and enhancing collaboration across teams. **Cons:** - Users find the **connector issues** limiting, as direct connections to other AI agents are unavailable. - Users experience **integration issues** as connecting other AI agents to the Coalesce Catalog knowledge is currently impossible. - Users face the **limitation of not connecting other AI agents** directly to the Coalesce Catalog knowledge base. #### What Are Recent G2 Reviews of Coalesce Catalog (formerly CastorDoc)? **"[User-friendly & easy adoption for all of our data users](https://www.g2.com/survey_responses/coalesce-catalog-formerly-castordoc-review-11753164)"** **Rating:** 4.5/5.0 stars *— Théo C.* [Read full review](https://www.g2.com/survey_responses/coalesce-catalog-formerly-castordoc-review-11753164) --- **"[A great tool to organize and explain your data hub](https://www.g2.com/survey_responses/coalesce-catalog-formerly-castordoc-review-10622007)"** **Rating:** 4.5/5.0 stars *— Verified User in Computer Software* [Read full review](https://www.g2.com/survey_responses/coalesce-catalog-formerly-castordoc-review-10622007) --- ### 13. [IBM InfoSphere Information Governance Catalog](https://www.g2.com/products/ibm-infosphere-information-governance-catalog/reviews) IBM® Information Governance Catalog is an interactive, web-based tool that allows users to explore, understand and analyze information. Users can create, manage and share a common business language, document and enact policies and rules and track the usage and consumption of data within a lineage report providing trusted information for compliance and insights. Learn More: https://ibm.co/2xmfLsK **Average Rating:** 4.0/5.0 **Total Reviews:** 16 **How Do G2 Users Rate IBM InfoSphere Information Governance Catalog?** - **Ease of Use:** 7.6/10 (Category avg: 8.6/10) **Who Is the Company Behind IBM InfoSphere Information Governance Catalog?** - **Seller:** [IBM](https://www.g2.com/sellers/ibm) - **Year Founded:** 1911 - **HQ Location:** Armonk, New York, United States - **Twitter:** @IBMSecurity (74,660 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (328,202 employees on LinkedIn®) - **Ownership:** SWX:IBM **Who Uses This Product?** - **Company Size:** 53% Enterprise, 26% Mid-Market #### What Are Recent G2 Reviews of IBM InfoSphere Information Governance Catalog? **"[Searching for assets inside Information Governance Catalog is easy](https://www.g2.com/survey_responses/ibm-infosphere-information-governance-catalog-review-4368588)"** **Rating:** 4.5/5.0 stars *— Gyuzel Z.* [Read full review](https://www.g2.com/survey_responses/ibm-infosphere-information-governance-catalog-review-4368588) --- **"[Using IGC to build our Business Metadata Glossary](https://www.g2.com/survey_responses/ibm-infosphere-information-governance-catalog-review-1744120)"** **Rating:** 5.0/5.0 stars *— Verified User in Banking* [Read full review](https://www.g2.com/survey_responses/ibm-infosphere-information-governance-catalog-review-1744120) --- ### 14. [data.world](https://www.g2.com/products/data-world/reviews) data.world is the most-adopted data catalog and governance platform on the market. Built on a unique knowledge graph foundation, data.world seamlessly integrates with your existing systems. We set the standard for swift, people-centric governance. We don't just manage data; we unlock its potential, paving the way for responsible AI adoption and data-driven decision-making at scale. data.world is a Certified B Corporation and public benefit corporation and home to the world’s largest collaborative open data community with more than two million members, including ninety percent of the Fortune 500. **Average Rating:** 4.2/5.0 **Total Reviews:** 12 **How Do G2 Users Rate data.world?** - **Ease of Use:** 8.8/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 9.2/10 (Category avg: 8.6/10) - **Metadata Management :** 8.8/10 (Category avg: 8.4/10) - **Data Lineage:** 9.3/10 (Category avg: 8.7/10) **Who Is the Company Behind data.world?** - **Seller:** [data.world](https://www.g2.com/sellers/data-world) - **Year Founded:** 2016 - **HQ Location:** Austin, Texas - **Twitter:** @datadotworld (5,498 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/data.world/ (100 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 67% Small-Business, 25% Mid-Market #### What Are data.world's Pros and Cons? **Pros:** - Analytics (1 reviews) - Data Discovery (1 reviews) - Data Management (1 reviews) - Data Visualization (1 reviews) - Ease of Use (1 reviews) **Cons:** - Poor Customer Support (1 reviews) - Poor Support Services (1 reviews) ### What Do G2 Reviewers Say About data.world? *AI-generated summary from verified user reviews* **Pros:** - Users enjoy the **ease of use in data discovery and analytics** with data.world, enhancing their overall experience. - Users enjoy the **easy-to-use data discovery** features of data.world, enhancing their data analysis experience significantly. - Users appreciate the **ease of use** and enjoy **discovering data analytics** with data.world's platform. - Users enjoy the **ease of use and data discovery** capabilities of data.world, enhancing their analytics experience. - Users love the **ease of use** of data.world, making data discovery and analytics seamless and enjoyable. **Cons:** - Users often face **poor customer support** , leaving them struggling with issues and lack of assistance for their queries. - Users experience **poor support services** when facing issues, leaving them without timely help for their queries. #### What Are Recent G2 Reviews of data.world? **"[One of the most mind-blowing venture information index](https://www.g2.com/survey_responses/data-world-review-8236137)"** **Rating:** 5.0/5.0 stars *— Rahul V.* [Read full review](https://www.g2.com/survey_responses/data-world-review-8236137) --- **"[Very attractive and informative](https://www.g2.com/survey_responses/data-world-review-9974366)"** **Rating:** 4.5/5.0 stars *— AASIM I.* [Read full review](https://www.g2.com/survey_responses/data-world-review-9974366) --- #### What Are G2 Users Discussing About data.world? - [What is data.world used for?](https://www.g2.com/discussions/what-is-data-world-used-for) - 1 comment ### 15. [IBM watsonx.data intelligence](https://www.g2.com/products/ibm-watsonx-data-intelligence/reviews) IBM watsonx.data intelligence revolutionizes the way organizations curate, manage, and utilize data by leveraging the power of AI to simplify data delivery across hybrid ecosystems. IBM watsonx.data intelligence is a comprehensive solution that integrates capabilities such as data governance (formerly IBM Knowledge Catalog), data lineage (formerly IBM Manta Data Lineage), data sharing, and data quality management. It empowers organizations to discover, trust, and access meaningful data, providing consumers with reliable data products. Explore Demo Library - https://www.ibm.com/products/watsonx-data-intelligence/demo-library Start your free trial - https://dataplatform.cloud.ibm.com/registration/stepone?context=df&apps=all&uucid=1227cc9e37cb9292&preselect\_region=true **Average Rating:** 4.2/5.0 **Total Reviews:** 24 **How Do G2 Users Rate IBM watsonx.data intelligence?** - **Ease of Use:** 8.4/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 7.5/10 (Category avg: 8.6/10) - **Metadata Management :** 7.5/10 (Category avg: 8.4/10) - **Data Lineage:** 8.3/10 (Category avg: 8.7/10) **Who Is the Company Behind IBM watsonx.data intelligence?** - **Seller:** [IBM](https://www.g2.com/sellers/ibm) - **Year Founded:** 1911 - **HQ Location:** Armonk, New York, United States - **Twitter:** @IBMSecurity (74,660 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (328,202 employees on LinkedIn®) - **Ownership:** SWX:IBM **Who Uses This Product?** - **Company Size:** 38% Small-Business, 34% Enterprise #### What Are IBM watsonx.data intelligence's Pros and Cons? **Pros:** - Automation (3 reviews) - Data Lineage (3 reviews) - Data Quality (2 reviews) - Ease of Use (2 reviews) - Efficiency (2 reviews) **Cons:** - Complex Implementation (3 reviews) - Complexity (2 reviews) - Expensive (2 reviews) - Expertise Required (2 reviews) - Extra Costs (2 reviews) ### What Do G2 Reviewers Say About IBM watsonx.data intelligence? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **automation features** of IBM watsonx.data intelligence, simplifying data flow understanding and governance. - Users value the **automated data lineage visualization** of IBM Manta, enhancing understanding and governance of complex data flows. - Users value the **easy view of data flows** provided by IBM Watsonx.data intelligence, enhancing understanding and governance. - Users highlight the **ease of use** of IBM Manta Data Lineage, simplifying data flow visualization and governance. - Users value the **efficiency** of IBM watsonx.data intelligence in automating data lineage, enhancing governance and decision-making. **Cons:** - Users face **complex implementation** challenges with IBM watsonx.data intelligence, requiring specialized expertise and significant effort. - Users find the **setup complexity** of IBM watsonx.data intelligence challenging, often requiring specialized expertise for proper implementation. - Users find the **high cost** of IBM watsonx.data intelligence challenging, making it less accessible for many. - Users note that **specialized expertise is required** for proper setup and implementation of IBM watsonx.data intelligence. - Users find the **extra costs** associated with IBM watsonx.data intelligence to be a significant barrier to entry. #### What Are Recent G2 Reviews of IBM watsonx.data intelligence? **"[Intuitive Data Lineage Solution](https://www.g2.com/survey_responses/ibm-watsonx-data-intelligence-review-10653356)"** **Rating:** 4.5/5.0 stars *— srikanth c.* [Read full review](https://www.g2.com/survey_responses/ibm-watsonx-data-intelligence-review-10653356) --- **"[Good Data Management Tool !](https://www.g2.com/survey_responses/ibm-watsonx-data-intelligence-review-10711565)"** **Rating:** 4.0/5.0 stars *— Rahul C.* [Read full review](https://www.g2.com/survey_responses/ibm-watsonx-data-intelligence-review-10711565) --- ### 16. [Sifflet](https://www.g2.com/products/sifflet/reviews) Sifflet is the control plane for Data and AI. Data teams spend too much time firefighting — bad data reaches the business before anyone catches it, root cause takes days, and the fix is invisible to the stakeholders who were burned. The result is a slow erosion of trust in every dashboard, report, and AI output the company relies on. We give data teams one layer that catches issues across the full stack, explains exactly where they came from, and shows how to resolve them — before the CFO sees the wrong number. Teams like BBC, Saint-Gobain, Euronext, and CMA-CGM use Sifflet to run reliable data infrastructure at enterprise scale — with coverage from legacy systems to modern cloud stacks. The result: fewer incidents, faster root cause, and data that can be defended in any meeting. **Average Rating:** 4.3/5.0 **Total Reviews:** 53 **How Do G2 Users Rate Sifflet?** - **Ease of Use:** 8.4/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 8.3/10 (Category avg: 8.6/10) **Who Is the Company Behind Sifflet?** - **Seller:** [Sifflet](https://www.g2.com/sellers/sifflet) - **Year Founded:** 2021 - **HQ Location:** Paris, Ile-de-France - **Twitter:** @Siffletdata (389 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/sifflet/ (50 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 76% Mid-Market, 24% Enterprise #### What Are Sifflet's Pros and Cons? **Pros:** - Efficiency Improvement (37 reviews) - Ease of Use (36 reviews) - Monitoring (36 reviews) - Data Lineage (32 reviews) - Alerting System (31 reviews) **Cons:** - Limited Customization (17 reviews) - Complex Setup (11 reviews) - Alert Management (10 reviews) - Limited Integration (10 reviews) - Lineage Issues (10 reviews) ### What Do G2 Reviewers Say About Sifflet? *AI-generated summary from verified user reviews* **Pros:** - Users value the **efficiency improvement** from Sifflet's ability to reduce noise and streamline data monitoring. - Users find Sifflet to be **intuitive and quick to implement** , enhancing productivity and facilitating seamless technology integration. - Users value **proactive monitoring** with Sifflet, leading to quicker issue resolution and enhanced data trust across teams. - Users appreciate the **full visibility of data lineage** in Sifflet, enabling efficient monitoring and tracking of data dependencies. - Users appreciate the **intelligent alerting system** of Sifflet, which effectively reduces noise and highlights real problems. **Cons:** - Users find the **limited customization options** frustrating, wishing for more bulk editing capabilities for monitors. - Users find the **complex setup** of Sifflet challenging, requiring significant onboarding effort and ongoing maintenance. - Users find the **alert management features lacking** in Sifflet, hoping for improvements in message delivery and auto-resolution. - Users find **limited integration options** a significant drawback for major data loads despite overall satisfaction with Sifflet. - Users find **lineage tracking confusing** in complex data warehouse architectures, needing simpler solutions for large models. #### What Are Recent G2 Reviews of Sifflet? **"[Sifflet’s AI-Powered Data Observability with Strong Lineage and Seamless Integrations](https://www.g2.com/survey_responses/sifflet-review-12802515)"** **Rating:** 4.5/5.0 stars *— Rinalon E.* [Read full review](https://www.g2.com/survey_responses/sifflet-review-12802515) --- **"[Sifflet Delivers Fast, Seamless Data Observability with Clear Dashboards](https://www.g2.com/survey_responses/sifflet-review-12817611)"** **Rating:** 4.5/5.0 stars *— Luciana S.* [Read full review](https://www.g2.com/survey_responses/sifflet-review-12817611) --- ### 17. [Common Voice dataset](https://www.g2.com/products/common-voice-dataset/reviews) Each entry in the dataset consists of a unique MP3 and corresponding text file. Many of the 1,368 recorded hours in the dataset also include demographic metadata like age, sex, and accent that can help train the accuracy of speech recognition engines. The dataset currently consists of 1,087 validated hours in 18 languages, but we're always adding more voices and languages. **Average Rating:** 4.5/5.0 **Total Reviews:** 11 **How Do G2 Users Rate Common Voice dataset?** - **Ease of Use:** 8.2/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 6.8/10 (Category avg: 8.6/10) - **Metadata Management :** 8.2/10 (Category avg: 8.4/10) - **Data Lineage:** 6.8/10 (Category avg: 8.7/10) **Who Is the Company Behind Common Voice dataset?** - **Seller:** [Mozilla](https://www.g2.com/sellers/mozilla) - **Year Founded:** 2005 - **HQ Location:** San Francisco, CA - **Twitter:** @mozilla (261,861 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/13948/ (1,751 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 64% Small-Business, 27% Mid-Market #### What Are Recent G2 Reviews of Common Voice dataset? **"[Best experience with Common Voice dataset](https://www.g2.com/survey_responses/common-voice-dataset-review-8643797)"** **Rating:** 5.0/5.0 stars *— Neelu P.* [Read full review](https://www.g2.com/survey_responses/common-voice-dataset-review-8643797) --- **"[review of common voice dataset](https://www.g2.com/survey_responses/common-voice-dataset-review-8982626)"** **Rating:** 4.0/5.0 stars *— Hirday J.* [Read full review](https://www.g2.com/survey_responses/common-voice-dataset-review-8982626) --- #### What Are G2 Users Discussing About Common Voice dataset? - [What is Common Voice dataset used for?](https://www.g2.com/discussions/what-is-common-voice-dataset-used-for) ### 18. [Oracle Enterprise Metadata Management](https://www.g2.com/products/oracle-enterprise-metadata-management/reviews) Oracle Enterprise Metadata Management (OEMM) is a comprehensive metadata management platform. OEMM can harvest and catalog metadata from virtually any metadata provider, including relational, Hadoop, ETL, BI, data modeling, and many more. **Average Rating:** 3.7/5.0 **Total Reviews:** 16 **How Do G2 Users Rate Oracle Enterprise Metadata Management?** - **Ease of Use:** 5.6/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 5.7/10 (Category avg: 8.6/10) - **Metadata Management :** 6.0/10 (Category avg: 8.4/10) - **Data Lineage:** 5.7/10 (Category avg: 8.7/10) **Who Is the Company Behind Oracle Enterprise Metadata Management?** - **Seller:** [Oracle](https://www.g2.com/sellers/oracle) - **Year Founded:** 1977 - **HQ Location:** Austin, TX - **Twitter:** @Oracle (827,997 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1028/ (208,078 employees on LinkedIn®) - **Ownership:** NYSE:ORCL **Who Uses This Product?** - **Company Size:** 44% Enterprise, 38% Small-Business #### What Are Recent G2 Reviews of Oracle Enterprise Metadata Management? **"[Best Data migration tool.](https://www.g2.com/survey_responses/oracle-enterprise-metadata-management-review-7229510)"** **Rating:** 4.5/5.0 stars *— Pravin T.* [Read full review](https://www.g2.com/survey_responses/oracle-enterprise-metadata-management-review-7229510) --- **"[Good management of Metadata](https://www.g2.com/survey_responses/oracle-enterprise-metadata-management-review-7238927)"** **Rating:** 4.5/5.0 stars *— David C.* [Read full review](https://www.g2.com/survey_responses/oracle-enterprise-metadata-management-review-7238927) --- ### 19. [Informatica Enterprise Data Catalog](https://www.g2.com/products/informatica-enterprise-data-catalog/reviews) A machine-learning-based data catalog that allows to classify and organize data assets across cloud, on-premises, and big data. It provides maximum value and reuse of data across enterprise. **Average Rating:** 4.3/5.0 **Total Reviews:** 19 **How Do G2 Users Rate Informatica Enterprise Data Catalog?** - **Ease of Use:** 7.8/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 7.7/10 (Category avg: 8.6/10) - **Metadata Management :** 8.0/10 (Category avg: 8.4/10) - **Data Lineage:** 8.3/10 (Category avg: 8.7/10) **Who Is the Company Behind Informatica Enterprise Data Catalog?** - **Seller:** [Informatica](https://www.g2.com/sellers/informatica) - **Year Founded:** 1993 - **HQ Location:** Redwood City, CA - **Twitter:** @Informatica (99,643 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/3858/ (2,802 employees on LinkedIn®) - **Ownership:** NYSE: INFA **Who Uses This Product?** - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 53% Enterprise, 26% Mid-Market #### What Are Recent G2 Reviews of Informatica Enterprise Data Catalog? **"[Absolute product for cloud data integration](https://www.g2.com/survey_responses/informatica-enterprise-data-catalog-review-7703992)"** **Rating:** 4.0/5.0 stars *— Sonali G.* [Read full review](https://www.g2.com/survey_responses/informatica-enterprise-data-catalog-review-7703992) --- **"[Informatica EDC - must have tool for Data catalog use case](https://www.g2.com/survey_responses/informatica-enterprise-data-catalog-review-9083881)"** **Rating:** 4.5/5.0 stars *— Sumeet J.* [Read full review](https://www.g2.com/survey_responses/informatica-enterprise-data-catalog-review-9083881) --- #### What Are G2 Users Discussing About Informatica Enterprise Data Catalog? - [What is Informatica Enterprise Data Catalog used for?](https://www.g2.com/discussions/what-is-informatica-enterprise-data-catalog-used-for) ### 20. [Coginiti](https://www.g2.com/products/coginiti/reviews) Coginiti is a SQL-first collaborative data operations platform that empowers teams to build, publish, and consume quality data products, streamlining the data analytics lifecycle from inception to insights. Integrating with the widest variety of data platforms and tools, Coginiti enables analysts, engineers, and data scientists to collaborate in real-time, breaking down silos and fostering innovation. Its intuitive interface simplifies managing complex data workflows, ensuring governance and consistency across projects. Key Features: - Realtime Collaboration - Flexible Data Modeling - Data Quality Testing - Visualize Data Lineage - Native Scheduling - Powerful APIs - AI Assistant Coginiti facilitates a seamless transition from data preparation to actionable intelligence. It’s not just about refining your data strategy or scaling your analytics capabilities; it’s about empowering your organization to harness the full potential of data for informed decision-making. Discover the power of Coginiti and transform your data operations. Coginiti offers products for individual analysts, data teams, and enterprises. **Average Rating:** 4.5/5.0 **Total Reviews:** 29 **How Do G2 Users Rate Coginiti?** - **Ease of Use:** 9.4/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 8.9/10 (Category avg: 8.6/10) - **Metadata Management :** 8.8/10 (Category avg: 8.4/10) - **Data Lineage:** 8.7/10 (Category avg: 8.7/10) **Who Is the Company Behind Coginiti?** - **Seller:** [Coginiti Corp](https://www.g2.com/sellers/coginiti-corp) - **Year Founded:** 2020 - **HQ Location:** Atlanta , GA - **Twitter:** @coginiti (71 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/coginiti (35 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 66% Enterprise, 28% Mid-Market #### What Are Recent G2 Reviews of Coginiti? **"[A functional app to maintain and work on all your databases](https://www.g2.com/survey_responses/coginiti-review-9002344)"** **Rating:** 5.0/5.0 stars *— Puteri P.* [Read full review](https://www.g2.com/survey_responses/coginiti-review-9002344) --- **"[Very user friendly tool to write and run queries needed to do my job](https://www.g2.com/survey_responses/coginiti-review-8657704)"** **Rating:** 5.0/5.0 stars *— Lori-Jo D.* [Read full review](https://www.g2.com/survey_responses/coginiti-review-8657704) --- #### What Are G2 Users Discussing About Coginiti? - [What is Coginiti used for?](https://www.g2.com/discussions/what-is-coginiti-used-for) - [What is Aginity Workbench for puredata system for analytics?](https://www.g2.com/discussions/what-is-aginity-workbench-for-puredata-system-for-analytics) - [What is Aginity Workbench for Netezza?](https://www.g2.com/discussions/what-is-aginity-workbench-for-netezza) - [How much does Aginity pro cost?](https://www.g2.com/discussions/how-much-does-aginity-pro-cost) ### 21. [BMC AMI Data](https://www.g2.com/products/bmc-ami-data/reviews) BMC AMI Data is an intelligent data management and optimization solution for IBM Z environments. It helps enterprises manage, protect, and optimize mission-critical mainframe data while reducing operational complexity, cost, and risk. BMC AMI Data leverages automation, advanced analytics, and predictive insights to streamline data maintenance, improve performance, and ensure the availability of critical workloads across Db2, IMS, VSAM, and related systems. The solution enables data teams to move from reactive management to proactive, insights-driven operations. Key capabilities include: - Automated data management and maintenance to reduce manual effort and improve operational efficiency - Real-time analytics and predictive insights to optimize performance and anticipate issues before they impact workloads - CPU and resource optimization to control costs and improve system efficiency at scale - Data protection and risk reduction to safeguard critical information and maintain data integrity - Support for modernization initiatives by simplifying how mainframe data is managed and integrated with evolving business needs - On-platform processing that keeps data secure and managed directly within the IBM Z environment By modernizing mainframe data management with automation and intelligence, BMC AMI Data helps organizations control data growth, reduce operational risk, and ensure high-performance delivery of always-on, business-critical applications. **Average Rating:** 4.3/5.0 **Total Reviews:** 31 **How Do G2 Users Rate BMC AMI Data?** - **Ease of Use:** 8.5/10 (Category avg: 8.6/10) **Who Is the Company Behind BMC AMI Data?** - **Seller:** [BMC Software](https://www.g2.com/sellers/bmc-software) - **Company Website:** https://www.bmc.com - **Year Founded:** 1980 - **HQ Location:** Houston, TX - **Twitter:** @BMCSoftware (47,946 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1597/ (8,877 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software - **Company Size:** 52% Small-Business, 26% Enterprise #### What Are BMC AMI Data's Pros and Cons? **Pros:** - Analytics (1 reviews) - Automation (1 reviews) - Ease of Use (1 reviews) - Easy Integrations (1 reviews) - Features (1 reviews) **Cons:** - Expensive (1 reviews) - Installation Difficulty (1 reviews) - Learning Curve (1 reviews) - Limited Compatibility (1 reviews) - Limited Customization (1 reviews) ### What Do G2 Reviewers Say About BMC AMI Data? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **analytics capabilities** of BMC AMI Data, enhancing their database management efficiency and effectiveness. - Users value the **seamless integration and automation** features of BMC AMI Data, enhancing quality assurance and preventing issues. - Users appreciate the **ease of use** of BMC AMI Data, benefiting from its streamlined and intuitive interface. - Users highlight the **easy integrations** with tools like Jenkins and UrbanCode, enhancing their automation and quality assurance processes. - Users appreciate the **robust features** of BMC AMI Data, enhancing database management with automation and proactive monitoring. **Cons:** - Users find the **expensive costs** of BMC AMI Data a significant drawback, impacting overall satisfaction and accessibility. - Users find **installation difficulty** with BMC AMI Data, noting challenges in setup and administration that impact usability. - Users report a significant **learning curve** with BMC AMI Data, making initial setup and usage challenging. - Users note the **limited compatibility** with older Db2 systems, affecting the overall integration experience with BMC AMI Data. - Users express concerns over **limited customization** , feeling restricted in tailoring BMC AMI Data to their specific needs. #### What Are Recent G2 Reviews of BMC AMI Data? **"[Simplifies Mainframe Data Management with Powerful Automation and Analytics](https://www.g2.com/survey_responses/bmc-ami-data-review-12955744)"** **Rating:** 5.0/5.0 stars *— Bharti K.* [Read full review](https://www.g2.com/survey_responses/bmc-ami-data-review-12955744) --- **"[Powerful Mainframe Data Management and Analytics Solution](https://www.g2.com/survey_responses/bmc-ami-data-review-12986188)"** **Rating:** 4.0/5.0 stars *— Shreyash R.* [Read full review](https://www.g2.com/survey_responses/bmc-ami-data-review-12986188) --- #### What Are G2 Users Discussing About BMC AMI Data? - [What is BMC AMI Database Administration for Db2 used for?](https://www.g2.com/discussions/what-is-bmc-ami-database-administration-for-db2-used-for) - [What is BMC Compuware Hiperstation used for?](https://www.g2.com/discussions/what-is-bmc-compuware-hiperstation-used-for) - [What is BMC AMI Application Restart and VSAM Recovery used for?](https://www.g2.com/discussions/what-is-bmc-ami-application-restart-and-vsam-recovery-used-for) ### 22. [DataHub](https://www.g2.com/products/datahub/reviews) DataHub is an event-driven AI and Data Context Platform designed to unify discovery, governance, and observability across an organization’s entire data estate. Unlike traditional data catalogs, DataHub Cloud offers real-time updates, automatic policy enforcement, and seamless integration with over 100 data sources. This ensures that organizations can maintain data quality, compliance, and AI-readiness at scale, addressing the complexities of modern data management. Targeted at data teams, governance professionals, and AI practitioners, DataHub serves a diverse audience that includes data engineers, analysts, data stewards, and compliance officers. The platform is particularly beneficial for organizations that require a centralized source of truth for all metadata across various environments, such as data warehouses, lakes, business intelligence platforms, machine learning systems, and AI agents. By consolidating data management processes, DataHub enhances collaboration and efficiency within data teams, enabling them to work more effectively. One of the standout features of DataHub is its automated data lineage tracking, which operates down to the column level. This capability allows teams to quickly assess the impact of any upstream changes, facilitating faster debugging of quality issues and helping to avert costly incidents before they escalate to production. Additionally, the platform employs AI-powered functionalities to manage repetitive tasks associated with metadata, such as documentation generation, intelligent glossary classification, and sensitive data tagging. This automation empowers data professionals to concentrate on higher-value activities, thereby increasing overall productivity. For data governance and compliance teams, DataHub offers robust tools for continuous policy enforcement, role-based access controls, and personally identifiable information (PII) detection. The platform is designed to support regulatory standards such as GDPR, HIPAA, and PCI, all while minimizing manual oversight. This ensures that organizations can maintain compliance without the burden of extensive manual processes. Furthermore, for AI and ML teams, DataHub provides the reliable data context essential for developing trustworthy AI agents and models, fostering innovation and improving outcomes. With backing from prominent investors like Bessemer Venture Partners, LinkedIn, and 8VC, DataHub has gained the trust of leading organizations, including Netflix, Visa, Slack, and Pinterest. This widespread adoption underscores the platform's effectiveness in transforming data operations and enhancing the overall data management landscape. For more information, visit datahub.com. **Average Rating:** 4.4/5.0 **Total Reviews:** 8 **How Do G2 Users Rate DataHub?** - **Ease of Use:** 8.5/10 (Category avg: 8.6/10) **Who Is the Company Behind DataHub?** - **Seller:** [DataHub](https://www.g2.com/sellers/datahub) - **Company Website:** https://datahub.com/ - **Year Founded:** 2013 - **HQ Location:** Palo Alto, California - **Twitter:** @DataHubCloud (720 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/datahub-cloud/ (18 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 63% Mid-Market, 25% Enterprise #### What Are DataHub's Pros and Cons? **Pros:** - Ease of Use (3 reviews) - Connectivity (2 reviews) - Open Source (2 reviews) - Accuracy (1 reviews) - Affordable (1 reviews) **Cons:** - Integration Issues (2 reviews) - Dependency Issues (1 reviews) - Difficult Interface (1 reviews) - Lack of Features (1 reviews) - Large Data Management (1 reviews) ### What Do G2 Reviewers Say About DataHub? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **ease of use** of DataHub, finding it excellent for organizing and managing datasets effortlessly. - Users value the **connectivity** of DataHub with numerous tools, enhancing integration and workflow efficiency. - Users appreciate the **ease of use** of DataHub as an open source data catalog tool that simplifies data lineage. - Users value the **accuracy** of DataHub, noting its effectiveness in simplifying complex data lineage. - Users value the **affordability** of DataHub, especially as it's free to use and open source. **Cons:** - Users face **integration issues** with DataHub, particularly lacking support for DBT and data quality tests. - Users find **dependency issues** challenging with DataHub, as data owners may lack motivation to put in necessary effort. - Users find the interface **difficult to navigate** , acknowledging the challenges in supporting diverse data sources. - Users are disappointed by the **lack of features** in DataHub, particularly missing integrations and dbt support. - Users experience **slowed performance with large datasets** , making data management more cumbersome than anticipated. #### What Are Recent G2 Reviews of DataHub? **"[Easy to use data Catalog tool](https://www.g2.com/survey_responses/datahub-review-10768422)"** **Rating:** 4.0/5.0 stars *— Siddharth N.* [Read full review](https://www.g2.com/survey_responses/datahub-review-10768422) --- **"[Easy and Efficient Tool!](https://www.g2.com/survey_responses/datahub-review-10781084)"** **Rating:** 4.5/5.0 stars *— Kessie M.* [Read full review](https://www.g2.com/survey_responses/datahub-review-10781084) --- ### 23. [ServiceNow Workflow Data Fabric](https://www.g2.com/products/servicenow-workflow-data-fabric/reviews) Workflow Data Fabric is the AI‑ready data foundation of the ServiceNow AI Platform. It connects to any data—structured, unstructured, and streaming—contextualizes it with business meaning and governance, and controls it with lineage and policies so employees and AI agents can confidently act on real‑time information to prevent disruptions, resolve requests faster, and optimize operations—all on one platform. How Workflow Data Fabric turns data into instant action Connect Unify data from systems like Salesforce, SAP, Workday, data lakes, and event streams in real time without duplication or fragile point‑to‑point integrations. With Zero Copy Connectors, Stream Connect, External Content Connectors, and Integration Hub, WDF simplifies architecture and cuts integration cost and time. Contextualize Give data business meaning and make it trustworthy with an active Data Catalog, embedded governance, and lineage. Use Knowledge Graph to map relationships (e.g., customers, assets, orders) so AI agents and workflows understand context and make accurate decisions in the flow of work. Control Apply policies, permissions, and compliance guards across connected sources so the right people and AI agents access the right data, at the right time, with full auditability and traceability—no more shadow copies or opaque pipelines. **Average Rating:** 4.3/5.0 **Total Reviews:** 138 **How Do G2 Users Rate ServiceNow Workflow Data Fabric?** - **Ease of Use:** 8.0/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 8.3/10 (Category avg: 8.6/10) - **Metadata Management :** 5.0/10 (Category avg: 8.4/10) - **Data Lineage:** 7.1/10 (Category avg: 8.7/10) **Who Is the Company Behind ServiceNow Workflow Data Fabric?** - **Seller:** [ServiceNow](https://www.g2.com/sellers/servicenow) - **Company Website:** https://www.servicenow.com/ - **Year Founded:** 2004 - **HQ Location:** Santa Clara, CA - **Twitter:** @servicenow (55,548 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/29352/ (35,081 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Software Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 45% Enterprise, 27% Mid-Market #### What Are ServiceNow Workflow Data Fabric's Pros and Cons? **Pros:** - Ease of Use (37 reviews) - Integrations (34 reviews) - Automation (30 reviews) - Efficiency Improvement (26 reviews) - Data Management (25 reviews) **Cons:** - Complex Setup (23 reviews) - Difficult Setup (17 reviews) - Expensive (15 reviews) - Slow Performance (14 reviews) - Complexity (13 reviews) ### What Do G2 Reviewers Say About ServiceNow Workflow Data Fabric? *AI-generated summary from verified user reviews* **Pros:** - Users value the **ease of use** of ServiceNow Workflow Data Fabric, noting its simplicity and seamless integration with other services. - Users value the **seamless integration** of ServiceNow Workflow Data Fabric, enhancing coordination and efficiency across departments. - Users value the **automation capabilities** of ServiceNow Workflow Data Fabric for streamlining workflows and enhancing insights. - Users appreciate the **efficiency improvement** of ServiceNow Workflow Data Fabric, streamlining workflows and enhancing data accessibility. - Users value the **data consolidation** capabilities of ServiceNow Workflow Data Fabric, enhancing accessibility and decision-making efficiency. **Cons:** - Users note that the **complex setup** of ServiceNow Workflow Data Fabric can be challenging, requiring technical expertise for implementation. - Users find the **difficult setup** of ServiceNow Workflow Data Fabric to be complex and a barrier to adoption. - Users find the **licensing and costs can be expensive** , particularly for smaller organizations or those with limited budgets. - Users experience **slow performance** during data synchronization and setup, which complicates integration and affects collaboration speed. - Users find **learning and implementing ServiceNow Workflow Data Fabric complex** , especially for new users without strong data governance. #### What Are Recent G2 Reviews of ServiceNow Workflow Data Fabric? **"[Zero-Copy, Real-Time Intelligence with ServiceNow Workflow Data Fabric](https://www.g2.com/survey_responses/servicenow-workflow-data-fabric-review-12543653)"** **Rating:** 4.5/5.0 stars *— Younesse H.* [Read full review](https://www.g2.com/survey_responses/servicenow-workflow-data-fabric-review-12543653) --- **"[Keeps ServiceNow Workflows in Sync with Current, Unified Data](https://www.g2.com/survey_responses/servicenow-workflow-data-fabric-review-12541512)"** **Rating:** 4.5/5.0 stars *— Youssef N.* [Read full review](https://www.g2.com/survey_responses/servicenow-workflow-data-fabric-review-12541512) --- ### 24. [Talend Data Catalog](https://www.g2.com/products/talend-data-catalog/reviews) Data Catalog automatically crawls, profiles, organizes, links, and enriches all your metadata. Up to 80% of the information associated with the data is documented automatically and kept up-to-date through smart relationships and machine learning, continually delivering the most meaningful data to the user. **Average Rating:** 4.2/5.0 **Total Reviews:** 12 **How Do G2 Users Rate Talend Data Catalog?** - **Ease of Use:** 8.0/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 6.7/10 (Category avg: 8.6/10) - **Metadata Management :** 9.4/10 (Category avg: 8.4/10) - **Data Lineage:** 9.4/10 (Category avg: 8.7/10) **Who Is the Company Behind Talend Data Catalog?** - **Seller:** [Qlik](https://www.g2.com/sellers/qlik) - **Year Founded:** 1993 - **HQ Location:** Radnor, PA - **Twitter:** @qlik (64,130 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/10162/ (4,551 employees on LinkedIn®) - **Phone:** 1 (888) 994-9854 **Who Uses This Product?** - **Company Size:** 42% Mid-Market, 33% Enterprise #### What Are Talend Data Catalog's Pros and Cons? **Pros:** - Data Cataloging (1 reviews) - Data Discovery (1 reviews) - Ease of Use (1 reviews) - Intuitive (1 reviews) - Intuitive Use (1 reviews) **Cons:** - Interface Complexity (1 reviews) - Poor Interface Design (1 reviews) - Poor UI Design (1 reviews) - User Interface Issues (1 reviews) - UX Design (1 reviews) ### What Do G2 Reviewers Say About Talend Data Catalog? *AI-generated summary from verified user reviews* **Pros:** - Users appreciate the **intuitive data viewing** of Talend Data Catalog, likening it to an e-commerce platform for ease of use. - Users find the **intuitive data view** of Talend Data Catalog similar to an e-commerce platform, enhancing usability. - Users appreciate the **intuitive interface** of Talend Data Catalog, making data management easy and streamlined. - Users find Talend Data Catalog **easy and intuitive to use** , likening it to a user-friendly e-commerce platform. - Users find Talend Data Catalog's **intuitive use** makes data viewing and interaction effortless, resembling an e-commerce platform. **Cons:** - Users feel the **interface complexity** of Talend Data Catalog can hinder usability and requires fine-tuning for better experience. - Users note the **poor interface design** requires improvements to enhance usability and overall appeal. - Users recognize that the UI is on the right track but highlight the need for **significant improvements** to enhance usability. - Users note the **UI needs improvement** to enhance appeal and usability for a better experience. - Users feel the UX design has **scope for improvement** and needs fine-tuning for better appeal and usability. #### What Are Recent G2 Reviews of Talend Data Catalog? **"[Qlik for Business Reporting & Analytics](https://www.g2.com/survey_responses/talend-data-catalog-review-6640048)"** **Rating:** 4.5/5.0 stars *— Wajeeh R.* [Read full review](https://www.g2.com/survey_responses/talend-data-catalog-review-6640048) --- **"[Using Qlik Catalog to enhance your data reach](https://www.g2.com/survey_responses/talend-data-catalog-review-5417913)"** **Rating:** 4.5/5.0 stars *— Fernando G.* [Read full review](https://www.g2.com/survey_responses/talend-data-catalog-review-5417913) --- #### What Are G2 Users Discussing About Talend Data Catalog? - [What is Talend Data Catalog used for?](https://www.g2.com/discussions/what-is-talend-data-catalog-used-for) ### 25. [Zeenea](https://www.g2.com/products/zeenea/reviews) "Zeenea is the Data Discovery Platform built for everyone to find, trust, and unlock the value of enterprise data. The cloud platform features two modern user experiences: Zeenea Studio is the application designed for data experts to save time managing, documenting, and governing data with maximum automation; while Zeenea Explorer enables business users to gain productivity by finding the data assets they need across all enterprise information. Zeenea’s built-in scanners and APIs enable organizations to automatically collect, consolidate, and link metadata from their data ecosystem. With a powerful knowledge graph and smart search engine, data teams can activate all enterprise metadata through a single source of truth. Zeenea helps dozens of organizations worldwide democratize data, including BPCE Group, Club Med, Generali, Renault, Société Générale, Solactive and Stellantis. Zeenea's SOC 2 Type II-certified solutions include a Data Catalog, a Business Glossary, Data Lineage, Data Quality, Data Governance, Data Stewardship, Data Privacy, Regulatory Compliance, Cloud Transformation." **Average Rating:** 4.4/5.0 **Total Reviews:** 12 **How Do G2 Users Rate Zeenea?** - **Ease of Use:** 8.3/10 (Category avg: 8.6/10) - **Business and Data Glossary:** 8.3/10 (Category avg: 8.6/10) - **Metadata Management :** 8.8/10 (Category avg: 8.4/10) - **Data Lineage:** 7.5/10 (Category avg: 8.7/10) **Who Is the Company Behind Zeenea?** - **Seller:** [Zeenea](https://www.g2.com/sellers/zeenea) - **Year Founded:** 2017 - **HQ Location:** Paris, √éle-de-France - **Twitter:** @ZeeneaSoftware (248 Twitter followers) - **LinkedIn® Page:** http://www.linkedin.com/company/zeenea (26 employees on LinkedIn®) **Who Uses This Product?** - **Company Size:** 50% Mid-Market, 25% Enterprise #### What Are Recent G2 Reviews of Zeenea? **"[Innovation](https://www.g2.com/survey_responses/zeenea-review-7309996)"** **Rating:** 5.0/5.0 stars *— Shahzad A.* [Read full review](https://www.g2.com/survey_responses/zeenea-review-7309996) --- **"[Efficient functionality](https://www.g2.com/survey_responses/zeenea-review-7441352)"** **Rating:** 5.0/5.0 stars *— Gilbert W.* [Read full review](https://www.g2.com/survey_responses/zeenea-review-7441352) --- ## What Is Machine Learning Data Catalog Software? [IT Infrastructure Software](https://www.g2.com/categories/it-infrastructure) ## What Software Categories Are Similar to Machine Learning Data Catalog Software? - [Data Governance Tools](https://www.g2.com/categories/data-governance-tools) - [DataOps Platforms](https://www.g2.com/categories/dataops-platforms) - [Active Metadata Management Software](https://www.g2.com/categories/active-metadata-management) --- ## How Do You Choose the Right Machine Learning Data Catalog Software? ### What You Should Know About Healthcare Claims Management Software ### What is a Machine Learning Data Catalog? Machine learning data catalog (MLDC) is an automated data catalog that carries out tasks like crawling metadata, cataloging, and classifying personally identifiable information (PII) data. Machine learning data catalogs organize the dataset inventory using metadata. Data catalogs help companies know where the data is stored, thus reducing the time taken to identify data and making it easily accessible for analytics. They are inventories of assets like tables, schema, files, and charts in organizations, aiding in solving a company's data discovery, quality, and governance challenges. ### What does MLDC Stand For? MLDC is an acronym for Machine Learning Data Catalog.  ### What are the Common Features of Machine Learning Data Catalogs? Machine learning data catalogs simplify the manual functions of a data catalog. A data catalog is an essential part of the data management strategy of any organization. Some of the features of machine learning data catalogs are: **Data ingestion and discovery:** Machine learning data catalogs must have prebuilt adapters to connect to different company systems like applications, databases, files, and external APIs. These adapters help in discovering metadata from systems. Metadata can be table names, attribute names, and constraints. The feature helps build native connectivity like integrations for data sources, business intelligence (BI) solutions, and data science tools. **Business glossary:** Although a good amount of data is stored in the repository, it is also essential for the users to understand what the stored data means. The glossary feature links this data to business terms giving it more meaning.  **Automated data labeling:** Data labeling is a prerequisite for machine learning algorithms. Automated data labeling is more accurate than manual since it eliminates human errors. Data labeling usually involves annotators identifying objects in images to build quality artificial intelligence (AI) training data. Automated labeling eliminates the challenges posed by the tedious annotation cycles. **Data lineage:** Data lineage is the process that helps the users know who, why, when, and where changes are made to the data. It is a part of metadata management. MLDCs automate the data lineage process. Data lineage helps determine when new or changed data require retraining machine learning models. MLDCs usually parse through query logs into data lakes and other data sources automatically to create a data lineage map. **Data quality monitoring and anomaly detection:** Data quality monitoring helps users understand if the data came from a trusted source. The machine learning data catalog also has a feature to identify sudden changes in data using machine learning algorithms. The users are immediately alerted to any changes or anomalies that are detected.  **Semantic search for data sets:** Machine learning data catalogs provide users with visual and intuitive searches like search engines. Almost every user in any organization is a data user, but not everyone can use SQL queries to use data. The semantic search feature makes it easier for all users to discover data sets. **Compliance capabilities:** This feature ensures that sensitive data is not exposed and that the user can trust the data. It further helps keep data governance policies in place and strengthen data management in the organization. Data stewards can identify low-quality data and restrict access to sensitive data, thus helping comply with regulations such as the General Data Protection Regulation (GDPR). **Data profiling:** Data profiling helps check the data from the data source and collects information about it. This process helps in knowing data quality issues much better, thus making the data management process more efficient. ### What are the Benefits of Machine Learning Data Catalogs? A machine learning data catalog provides several benefits to different types of users in the organization. These include: **Ease in data curation:** Data curation is a process of collecting, organizing, labeling, and cleaning data. Machine learning data catalogs validate metadata and organize insights into correct repositories using machine learning algorithms. **Ease of search:** Because of semantic search, it becomes easier for non-technical users to search and discover data for use since they do not have to use SQL queries every time to access data. **Ease in data collaboration:** Machine learning data catalogs help the users collaborate, use, and share data sets because machine learning data catalogs ease finding and storing siloed data. ### Who Uses Machine Learning Data Catalogs? Machine learning data catalogs centralize metadata for various data assets. By organizing the metadata, MLDCs help organizations to govern data access. **Data analysts:** Data analysts use MLDC to discover, classify, and manipulate data for their analytics processes. They can also discover AI or machine learning models, understand how they work, and import them into their BI tools. Data catalogs help data analysts make companies into self-service organizations. Self-service analytics is important for any organization that wants to be driven by insights. Machine learning data catalogs help the users know the means to find, understand, and trust data. **Marketers:** Marketing teams use the machine learning data catalog more commercially. They obtain insights for making better decisions using data catalogs. **Data scientists:** Data scientists usually publish their models for reuse. Data scientists always look for one platform that centralizes data for different projects.  ### Challenges with Machine Learning Data Catalogs Although machine learning data catalogs help solve major challenges in traditional data catalogs like data discovery and data lineage, MLDCs also come with challenges.   **Scalability:** It is tricky for all MLDCs to support a huge metadata volume. Sometimes, the data catalogs break down due to performance issues when overloaded with enormous amounts of metadata. Initially, data used to be stored in the company's mainframe data center. However, due to today's big data, machine learning data catalogs must keep track of data in both cloud and data lakes. **Fragmentation in evaluating a product:** If a data catalog is too bulky, it causes fragmentation in the user's journey of evaluating a product. Too much data makes users use too many tools, thus breaking a seamless experience into fragments. ### How to Buy Machine Learning Data Catalogs #### Requirements Gathering (RFI/RFP) for Machine Learning Data Catalogs The machine learning data catalog offers many features to help users identify usable data. A buyer can choose the right MLDC software depending on the organization's needs. RFP/RFIs help the organization look for pricing, product features, and guidelines. #### Compare Machine Learning Data Catalog Products **Create a long list** The first step is to look for all the possible players in the space. This gives an advantage of evaluating the vendors for the price, product features, and customer service.  **Create a short list** After evaluating the potential vendors, the company can narrow the list to those who check all their boxes. **Conduct demos** Demos help in understanding the product as a whole. A team of IT professionals and data scientists should join these demos to understand the product's functionality, whereas the marketing team can join in to analyze the business use of the software in the projects. #### Selection of Machine Learning Data Catalogs **Choose a selection team** A team of marketing professionals with data scientists and IT professionals can communicate any queries related to the MLDC product with the vendors. A data scientist would be more interested in knowing the technical features of the software. A marketing manager would be curious to know how the marketing team could use MLDC for any project. An IT professional would want to understand the software installation procedure. **Negotiation** Once the vendor quotes the price, the negotiations begin. The price is fixed based on the cost of other similar products available in the market and the extent to which the product can solve the challenges. **Final decision** The final decision is based on agreements between the vendor and the buyer.