# Best Data Preparation Software for Medium-Sized Businesses *By [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)* Products classified in the overall Data Preparation category are similar in many regards and help companies of all sizes solve their business problems. However, medium-sized business features, pricing, setup, and installation differ from businesses of other sizes, which is why we match buyers to the right Medium-Sized Business Data Preparation to fit their needs. Compare product ratings based on reviews from enterprise users or connect with one of G2's buying advisors to find the right solutions within the Medium-Sized Business Data Preparation category. In addition to qualifying for inclusion in the Data Preparation Software category, to qualify for inclusion in the Medium-Sized Business Data Preparation Software category, a product must have at least 10 reviews left by a reviewer from a medium-sized business. ## Top Data Preparation Software at a Glance | # | Product | Rating | Best For | What Users Say | |---|---------|--------|----------|----------------| | 1 | [Tableau](https://www.g2.com/products/tableau/reviews) | 4.4/5.0 (3,574 reviews) | Drag-and-drop data prep for multi-source dashboards | "[Tableau Makes Data Visualization Easy with Strong Integrations](https://www.g2.com/survey_responses/tableau-review-12975791)" | | 2 | [Alteryx](https://www.g2.com/products/alteryx/reviews) | 4.6/5.0 (789 reviews) | No-code multi-source ETL workflow automation | "[Easy, Time-Saving Data Automation with Alteryx’s Drag-and-Drop Workflows](https://www.g2.com/survey_responses/alteryx-review-12594796)" | | 3 | [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews) | 4.3/5.0 (758 reviews) | End-to-end data prep with no-code pipelines | "[Powerful & Transforming Data into Decisions—Effortlessly and Intelligently.](https://www.g2.com/survey_responses/sas-viya-review-12682824)" | | 4 | [Domo](https://www.g2.com/products/domo/reviews) | 4.3/5.0 (989 reviews) | No-code multi-source ETL and transformation | "[All-in-One Platform for Real-Time Analytics and Dashboards](https://www.g2.com/survey_responses/domo-review-12676104)" | | 5 | [HubSpot Data Hub](https://www.g2.com/products/hubspot-data-hub/reviews) | 4.5/5.0 (560 reviews) | HubSpot-native CRM data deduplication and cleansing | "[HubSpot Data Hub Keeps Customer Data Clean and Centralized](https://www.g2.com/survey_responses/hubspot-data-hub-review-12562615)" | | 6 | [dbt](https://www.g2.com/products/dbt/reviews) | 4.7/5.0 (206 reviews) | SQL-based ELT transformation with version-controlled lineage | "[Effortless Data Transformations with dbt](https://www.g2.com/survey_responses/dbt-review-12737111)" | | 7 | [Incorta](https://www.g2.com/products/incorta/reviews) | 4.4/5.0 (55 reviews) | Multi-source ELT with no-code data modeling | "[Facilitating presentation and information access](https://www.g2.com/survey_responses/incorta-review-9467627)" | | 8 | [DemandTools](https://www.g2.com/products/demandtools/reviews) | 4.6/5.0 (275 reviews) | Salesforce-native bulk deduplication and data cleansing | "[The reason I don’t fear CSV files anymore.](https://www.g2.com/survey_responses/demandtools-review-11536972)" | | 9 | [AWS Glue](https://www.g2.com/products/aws-glue/reviews) | 4.3/5.0 (194 reviews) | Serverless ETL pipelines with AWS-native cataloging | "[AWS Glue Makes ETL Simple with Serverless Scalability and Deep AWS Integration](https://www.g2.com/survey_responses/aws-glue-review-12380790)" | | 10 | [Qlik Sense](https://www.g2.com/products/qlik-sense/reviews) | 4.4/5.0 (763 reviews) | Multi-source ETL with associative data modeling | "[Intuitive Data Exploration and Dashboards with Qlik Sense’s Associative Model](https://www.g2.com/survey_responses/qlik-sense-review-12963425)" | --- ## What Are the Most Common Questions About Data Preparation Software? *AI-generated · Last updated: May 26, 2026* ### What top platforms for cleaning and transforming raw data? Based on G2 reviews, buyers evaluating data preparation software for cleaning and transforming raw data consistently mention a few recurring strengths: easy workflow building, support for multiple data sources, and reduced manual cleanup. According to verified users, Alteryx is frequently praised for data cleansing, standardization, joining sources, and automating repetitive prep work. G2 reviewers mention AWS Glue for serverless ETL and schema management when teams are already working in AWS environments. They also mention dbt for organizing transformation logic, testing data quality, and creating maintainable transformation pipelines inside the warehouse. Across recent reviews, the common value is faster preparation of messy data with less spreadsheet work and more repeatable processes. **Here are some of the top-rated products on G2:** - [Alteryx](https://www.g2.com/products/alteryx/reviews) – often used for cleansing, standardizing, and combining data from many sources with low-code workflows - [dbt](https://www.g2.com/products/dbt/reviews) – suited for SQL-based transformations, testing, and documentation for warehouse-centered teams - [AWS Glue](https://www.g2.com/products/aws-glue/reviews) – helpful for serverless ETL, schema discovery, and catalog-driven preparation in AWS ### Which data preparation software integrates with BI platforms? Based on G2 reviews, several data preparation software products are used specifically to feed dashboards, reports, and analytics tools. According to verified users, Alteryx is often used to standardize source data before it reaches visualization templates or recurring reports. G2 reviewers mention AWS Glue integrating smoothly with services like Athena and Redshift, helping prepared data move into downstream analytics environments. Users also describe Domo as combining ETL, data integration, and dashboarding in one cloud platform, which reduces the number of handoffs between prep and reporting. Across recent feedback, the main buying signal is not just connectivity, but whether the product helps teams centralize data, automate transformations, and make prepared data easier to use in BI workflows. ### Which data preparation software offers the fastest processing speeds? Based on G2 reviews, speed is usually described in the context of reducing manual work, handling large files, or accelerating repetitive transformations rather than raw benchmark claims. According to verified users, Alteryx is often highlighted for automating weekly standardization, reconciliation, and large-volume preparation tasks that would otherwise take much longer in SQL or Excel. G2 reviewers mention AWS Glue for scalable serverless processing and automation across multiple sources, while dbt is praised for efficient transformation workflows managed directly in the warehouse. Recent reviews suggest the fastest option often depends on your environment: warehouse-first teams lean toward dbt, AWS-native teams toward Glue, and analyst-heavy teams toward Alteryx for low-code speed and operational efficiency. ### What best software for preparing real-time streaming data? Based on G2 reviews, tools mentioned for fresher or near-real-time data preparation tend to stand out for automated refreshes, real-time ingestion, or continuously updated dashboards. According to verified users, AWS Glue is often selected when teams need automated ETL, schema handling, and scalable processing without managing infrastructure. G2 reviewers also mention Domo for real-time updates, centralized dashboards, and bringing multiple data sources together for faster reporting. Some users reference SAS Viya for keeping dashboards up to date with real-time data while combining analytics and data preparation in one environment. Recent feedback shows that buyers focused on time-sensitive reporting usually value automation, centralized metadata, and reduced operational overhead more than pure transformation depth alone. **Here are some of the top-rated products on G2:** - [AWS Glue](https://www.g2.com/products/aws-glue/reviews) – used for automated, serverless ETL and scalable processing across connected data sources - [Domo](https://www.g2.com/products/domo/reviews) – praised for real-time updates, centralized data, and dashboards that support faster decisions - [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews) – mentioned for combining up-to-date dashboards, analytics, and data preparation in one platform ### What top-rated data preparation tools for large datasets? Based on G2 reviews, buyers working with large datasets tend to prioritize products that can process high volumes reliably while still keeping transformation logic manageable. According to verified users, Alteryx is often praised for handling large amounts of data, automation, and combining sources without relying as heavily on manual spreadsheets. G2 reviewers mention AWS Glue for scalable, serverless ETL and data catalog capabilities that help with large-scale data processing. They also call out dbt for structuring and testing transformations directly in the warehouse, which helps teams manage growing model complexity. Across recent reviews, the strongest signal is that teams want large-scale preparation tools that improve reliability, reduce manual intervention, and support repeatable analytics workflows. **Here are some of the top-rated products on G2:** - [Alteryx](https://www.g2.com/products/alteryx/reviews) – commonly used for high-volume cleansing, reconciliation, and multi-source preparation workflows - [AWS Glue](https://www.g2.com/products/aws-glue/reviews) – suited for scalable ETL, centralized metadata, and large-source processing in AWS - [dbt](https://www.g2.com/products/dbt/reviews) – useful for warehouse-scale transformations, testing, and dependency management on large model sets ### Which is the best data preparation tool for analytics teams? Based on G2 reviews, [Alteryx](https://www.g2.com/products/alteryx/reviews) stands out as the single most broadly referenced option here because recent reviewers repeatedly describe it as easy to use across skill levels, strong for automation, and effective for combining data from multiple sources. According to verified users, analytics teams value how it helps with cleansing, standardization, recurring reporting, and reducing manual prep steps. G2 reviewers mention that it is especially useful when analysts need to move quickly without relying entirely on engineering resources. At the same time, users also note tradeoffs such as crashes, slower performance in some cases, and licensing concerns. For analytics teams prioritizing repeatable workflows and accessible data preparation, Alteryx appears most consistently favored. ### What top platforms for self-service data preparation? Based on G2 reviews, self-service data preparation platforms are usually judged by how quickly non-technical or less technical users can clean, combine, and shape data without heavy engineering help. According to verified users, Alteryx is often praised for intuitive workflows, visual steps, and accessibility for users without deep coding backgrounds. G2 reviewers also describe Domo as approachable for both technical and non-technical teams, especially through features like Magic ETL and centralized dashboards. SAS Viya is another option users mention because it combines low-code and no-code workflows with analytics and data prep in one place. Across recent reviews, self-service success usually comes down to usability, guided workflow design, and the ability to reduce dependence on manual spreadsheet processes. ### What best platforms for combining data preparation with ETL processes? Based on G2 reviews, products that combine data preparation with ETL tend to be valued for reducing tool sprawl and making it easier to move from ingestion to transformation to reporting. According to verified users, Alteryx is frequently used for end-to-end prep workflows including cleansing, blending, and automation. G2 reviewers mention AWS Glue for serverless ETL, schema discovery, and centralized catalog management, especially in AWS-based stacks. Domo is also cited for bringing ETL, integration, analytics, and dashboards together inside one cloud platform. Recent feedback suggests buyers prefer platforms that do more than transform data: they want repeatable workflows, easier handoffs to reporting, and less need to stitch together separate tools for prep and pipeline management. **Here are some of the top-rated products on G2:** - [Alteryx](https://www.g2.com/products/alteryx/reviews) – supports automated cleansing, joining, and repeatable ETL-style preparation for analysts - [AWS Glue](https://www.g2.com/products/aws-glue/reviews) – combines serverless ETL, cataloging, and automated schema handling for cloud data pipelines - [Domo](https://www.g2.com/products/domo/reviews) – unifies ETL, data integration, and dashboard delivery in one platform ### What best tools for preparing data for machine learning models? Based on G2 reviews, buyers preparing data for machine learning models often look for products that help with transformation, consistency, and handling complex or large datasets before modeling begins. According to verified users, SAS Viya is frequently mentioned for bringing data preparation, analytics, and machine learning into one environment, which can reduce handoffs between prep and modeling. G2 reviewers also describe dbt as useful for creating tested, documented, and reusable transformation layers that support downstream modeling workflows. Alteryx is another product users call out when they need to cleanse, standardize, and automate repetitive preparation tasks before analysis. Across recent reviews, the strongest value comes from improving data quality and making feature-ready datasets easier to produce consistently. **Here are some of the top-rated products on G2:** - [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews) – used for preparing data and moving into machine learning workflows within one platform - [dbt](https://www.g2.com/products/dbt/reviews) – helps teams build tested, documented transformation layers for reliable model inputs - [Alteryx](https://www.g2.com/products/alteryx/reviews) – valued for automating cleansing and preparation steps before advanced analytics ### Which tool offers AI-powered data preparation suggestions? Based on G2 reviews, SAS Viya is the clearest fit for this question because verified users explicitly mention AI-powered insights, AI-powered search, and features that help users work with dashboards and data more easily. According to verified users, the platform combines data preparation, analytics, and model-building workflows in a single environment, which supports more guided analysis. G2 reviewers also mention capabilities like Copilot and automated assistance for tasks such as data cleansing and reporting workflows. While several products in this category reference AI features, SAS Viya has the most direct and recurring review language around AI-supported preparation and insight generation in the recent review set. That makes it the strongest grounded answer for buyers prioritizing AI-assisted preparation. ## How Many Data Preparation Software Products Does G2 Track? **Total Products under this Category:** 107 ### Category Stats (Jun 2026) - **Average Rating**: 4.52/5 (↑0.01 vs May 2026) The average rating of products in this category, based on all submitted ratings - **New Reviews This Quarter**: 258 - **Buyer Segments**: Enterprise 47% │ Mid-Market 31% │ Small-Business 22% Represents the distribution of reviewers across all products in this category. - **Top Trending Product**: Diver Platform (+3.71%) - Among all products in this category, Diver Platform recorded the largest rating increase compared to last month *Last updated: June 18, 2026* ## How Does G2 Rank Data Preparation Software Products? **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 10,700+ Authentic Reviews - 107+ 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. --- **Sponsored** ### Alteryx Alteryx, through it's Alteryx One platform, helps enterprises transform complex, disconnected data into a clean, AI-ready state. Whether you’re creating financial forecasts, analyzing supplier performance, segmenting customer data, analyzing employee retention, or building competitive AI applications from your proprietary data, Alteryx One makes it easy to cleanse, blend, and analyze data to unlock the unique insights that drive impactful decisions. AI-Guided Analytics Alteryx automates and simplifies every stage of data preparation and analysis, from validation and enrichment to predictive analytics and automated insights. Incorporate generative AI directly into your workflows to streamline complex data tasks and generate insights faster. Unmatched flexibility, whether you prefer code-free workflows, natural language commands, or low-code options, Alteryx adapts to your needs. Trusted. Secure. Enterprise-Ready. Alteryx is trusted by over half of the Global 2000 and 19 of the top 20 global banks. With built-in automation, governance, and security, your workflows can scale and maintain compliance while delivering consistent results. And it doesn’t matter if your systems are on-premises, hybrid, or in the cloud; Alteryx fits effortlessly into your infrastructure. Easy to Use. Deeply Connected. What truly sets Alteryx apart is our focus on efficiency and ease of use for analysts and our active community of 700,000 Alteryx users to support you at every step of your journey. With seamless integration to data everywhere including platforms like Databricks, Snowflake, AWS, Google, SAP, and Salesforce, our platform helps unify siloed data and accelerate getting to insights. Visit Alteryx.com for more information, and to start your free trial. [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=1412&secure%5Bdisplayable_resource_id%5D=1412&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=1412&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=989&secure%5Bresource_id%5D=1412&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fdata-preparation&secure%5Btoken%5D=d66f4fd896364210a09ac49e2810fe5694a3a4e1a361c7c8e07068691727b4ae&secure%5Burl%5D=https%3A%2F%2Fwww.alteryx.com%2Ftrial%3Futm_source%3Dg2%26utm_medium%3Dreviewsite%26utm_campaign%3DFY25_Global_AllRegions_AlwaysOn_AllPersonas_IndustryAgnostic%26utm_content%3Dg2_freetrial&secure%5Burl_type%5D=free_trial) --- ## What Are the Top-Rated Data Preparation Software Products in 2026? ### 1. [Tableau](https://www.g2.com/products/tableau/reviews) Tableau is the world’s leading AI-powered analytics platform. Whether you are a business user or an analyst, Tableau turns trusted data into actionable insights. With our flexible, interoperable platform, you can: Turn data into action at scale with human and agent collaboration. Tableau Next delivers agentic AI for faster data-insight-action workflows. It surfaces insights, provides proactive recommendations, and helps you take action in the flow of work. Scale data-driven insights with complete operational confidence. Tableau Cloud enables fully managed analytics at scale. It accelerates your time to value and gives you access to the latest AI-powered innovations. Deploy visual, self-service analytics with unmatched control and flexibility. Tableau Server meets your organization's governance and security needs. It provides enterprise-grade, self-service analytics on-premise or in your private cloud. **Average Rating:** 4.4/5.0 **Total Reviews:** 3,574 **How Do G2 Users Rate Tableau?** - **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 9.0/10) - **Data Workflows:** 8.4/10 (Category avg: 8.8/10) - **Profiling and Classification:** 8.2/10 (Category avg: 8.5/10) - **Data Joining:** 8.5/10 (Category avg: 8.9/10) **Who Is the Company Behind Tableau?** - **Seller:** [Salesforce](https://www.g2.com/sellers/salesforce) - **Company Website:** https://www.salesforce.com/ - **Year Founded:** 1999 - **HQ Location:** San Francisco, CA - **Twitter:** @salesforce (579,511 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/3185/ (83,223 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Analyst, Business Analyst - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 41% Enterprise, 36% Mid-Market #### What Are Tableau's Pros and Cons? **Pros:** - Ease of Use (634 reviews) - Data Visualization (563 reviews) - Visualization (424 reviews) - Features (351 reviews) - Intuitive (317 reviews) **Cons:** - Learning Curve (282 reviews) - Learning Difficulty (240 reviews) - Expensive (225 reviews) - Slow Performance (155 reviews) - Difficulty (139 reviews) ### 2. [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews) SAS Viya is a cloud-native data and AI platform that enables teams to build, deploy and scale explainable AI that drives trusted, confident decisions. It unites the entire data and AI life cycle and empowers teams to innovate quickly while balancing speed, automation and governance by design. Viya unifies data management, advanced analytics and decisioning in a single platform, so organizations can move from experimentation to production with confidence, delivering measurable business impact that is secure, explainable and scalable across any environment. Key capabilities required to deliver trusted decisions include: • End-to-end clarity across the data and AI life cycle, with built-in lineage, auditability and continuous monitoring to support defensible decisions. • Governance by design, enabling consistent oversight across data, models and decisions to reduce risk and accelerate adoption. • Explainable AI at scale, so insights and outcomes can be understood, validated and trusted by business and regulators alike. • Operationalized analytics, ensuring value continues beyond deployment through monitoring, retraining and life cycle management. • Flexible, cloud-native deployment, allowing organizations to start anywhere and scale everywhere while maintaining control. **Average Rating:** 4.3/5.0 **Total Reviews:** 758 **How Do G2 Users Rate SAS Viya?** - **Has the product been a good partner in doing business?:** 8.2/10 (Category avg: 9.0/10) - **Data Workflows:** 8.5/10 (Category avg: 8.8/10) - **Profiling and Classification:** 8.5/10 (Category avg: 8.5/10) - **Data Joining:** 8.8/10 (Category avg: 8.9/10) **Who Is the Company Behind SAS Viya?** - **Seller:** [SAS Institute Inc.](https://www.g2.com/sellers/sas-institute-inc-df6dde22-a5e5-4913-8b21-4fa0c6c5c7c2) - **Company Website:** https://www.sas.com/ - **Year Founded:** 1976 - **HQ Location:** Cary, NC - **Twitter:** @SASsoftware (60,863 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1491/ (18,638 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Student, Statistical Programmer - **Top Industries:** Pharmaceuticals, Banking - **Company Size:** 33% Enterprise, 33% Small-Business #### What Are SAS Viya's Pros and Cons? **Pros:** - Ease of Use (234 reviews) - Features (218 reviews) - Analytics (196 reviews) - Data Analysis (166 reviews) - Intuitive (145 reviews) **Cons:** - Learning Difficulty (151 reviews) - Learning Curve (144 reviews) - Complexity (143 reviews) - Difficult Learning (117 reviews) - Expensive (108 reviews) ### 3. [Domo](https://www.g2.com/products/domo/reviews) Domo's AI and Data Products Platform empowers organizations to turn data into actionable insights and solutions. It allows users to seamlessly connect diverse data sources, prepare data for use, and generate dynamic reports and visualizations—all within a single interface. With built-in AI and automation capabilities, teams can easily build and use AI agents, streamline workflows, and create tailored solutions. **Average Rating:** 4.3/5.0 **Total Reviews:** 989 **How Do G2 Users Rate Domo?** - **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 9.0/10) - **Data Workflows:** 8.1/10 (Category avg: 8.8/10) - **Profiling and Classification:** 7.6/10 (Category avg: 8.5/10) - **Data Joining:** 8.9/10 (Category avg: 8.9/10) **Who Is the Company Behind Domo?** - **Seller:** [Domo](https://www.g2.com/sellers/domo) - **Company Website:** https://www.domo.com - **Year Founded:** 2010 - **HQ Location:** American Fork, UT - **Twitter:** @Domotalk (63,526 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/25237/ (1,305 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Analyst, Business Analyst - **Top Industries:** Computer Software, Marketing and Advertising - **Company Size:** 49% Mid-Market, 29% Enterprise #### What Are Domo's Pros and Cons? **Pros:** - Ease of Use (248 reviews) - Data Visualization (116 reviews) - Intuitive (95 reviews) - Easy Integrations (93 reviews) - Integrations (88 reviews) **Cons:** - Learning Curve (66 reviews) - Missing Features (59 reviews) - Data Management Issues (55 reviews) - Expensive (45 reviews) - Complexity (43 reviews) ### 4. [HubSpot Data Hub](https://www.g2.com/products/hubspot-data-hub/reviews) Operations Hub connects, cleanses, and automates customer data across the HubSpot CRM, providing operations teams with tools to maintain data quality, ensure system integration, and streamline business processes. Core Value Proposition: Operations Hub addresses critical operational challenges: disconnected data across applications, manual data entry consuming team time, data quality issues undermining business decisions, and complex automation requirements existing tools cannot handle. The platform offers native integrations with other applications to create a more efficient, aligned, and agile business. Key Capabilities: Data Integration: Operations Hub connects contacts, leads, and company data between HubSpot and external applications bidirectionally and in real-time. This creates a unified customer data foundation rather than requiring manual data transfer. Data Quality Management: The platform includes tools that maintain a clean database, allowing operations teams to save hours of manual data validation and correction work. Process Automation: Operations Hub enables complex business process automation across systems, connecting trigger events in one application to automated actions in another. This streamlines internal workflows and reduces manual coordination. Unified Customer View: By connecting all customer data sources to the HubSpot CRM platform, Operations Hub creates a single source of truth that sales, marketing, and service teams can reference for customer interactions. Operations Hub vs. Alternatives: Unlike standalone integration platforms (iPaaS) requiring technical expertise to configure and maintain, Operations Hub provides native HubSpot integration with a visual interface designed for operations professionals rather than developers. This reduces implementation time and ongoing maintenance requirements. Operations Hub eliminates manual data entry and data validation by automating these workflows. The platform guarantees up-to-date data and maintains a clean database without constant manual intervention. Who Should Use Operations Hub: Operations Hub serves operations teams managing data across multiple systems, organizations experiencing data quality issues affecting business decisions, and companies needing to automate complex cross-system workflows without extensive technical resources. The platform enables business agility as organizations grow. Outcome: Operations Hub supercharges your HubSpot CRM with a complete toolkit to connect, clean, and automate customer data, uniting all customer data into one connected platform that results in a friction-free customer experience. **Average Rating:** 4.5/5.0 **Total Reviews:** 560 **How Do G2 Users Rate HubSpot Data Hub?** - **Has the product been a good partner in doing business?:** 9.1/10 (Category avg: 9.0/10) - **Data Workflows:** 9.8/10 (Category avg: 8.8/10) - **Profiling and Classification:** 9.6/10 (Category avg: 8.5/10) - **Data Joining:** 9.2/10 (Category avg: 8.9/10) **Who Is the Company Behind HubSpot Data Hub?** - **Seller:** [HubSpot](https://www.g2.com/sellers/hubspot) - **Company Website:** https://hubspot.com - **Year Founded:** 2006 - **HQ Location:** Cambridge, Massachusetts, United States - **Twitter:** @HubSpot (784,409 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/68529/ (12,158 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** CEO, Owner - **Top Industries:** Information Technology and Services, Marketing and Advertising - **Company Size:** 67% Small-Business, 30% Mid-Market #### What Are HubSpot Data Hub's Pros and Cons? **Pros:** - Ease of Use (113 reviews) - Data Management (88 reviews) - Automation (86 reviews) - Integrations (59 reviews) - Efficiency (48 reviews) **Cons:** - Limitations (53 reviews) - Missing Features (36 reviews) - Learning Curve (34 reviews) - Expensive (31 reviews) - Complexity (24 reviews) ### 5. [Alteryx](https://www.g2.com/products/alteryx/reviews) Alteryx, through it's Alteryx One platform, helps enterprises transform complex, disconnected data into a clean, AI-ready state. Whether you’re creating financial forecasts, analyzing supplier performance, segmenting customer data, analyzing employee retention, or building competitive AI applications from your proprietary data, Alteryx One makes it easy to cleanse, blend, and analyze data to unlock the unique insights that drive impactful decisions. AI-Guided Analytics Alteryx automates and simplifies every stage of data preparation and analysis, from validation and enrichment to predictive analytics and automated insights. Incorporate generative AI directly into your workflows to streamline complex data tasks and generate insights faster. Unmatched flexibility, whether you prefer code-free workflows, natural language commands, or low-code options, Alteryx adapts to your needs. Trusted. Secure. Enterprise-Ready. Alteryx is trusted by over half of the Global 2000 and 19 of the top 20 global banks. With built-in automation, governance, and security, your workflows can scale and maintain compliance while delivering consistent results. And it doesn’t matter if your systems are on-premises, hybrid, or in the cloud; Alteryx fits effortlessly into your infrastructure. Easy to Use. Deeply Connected. What truly sets Alteryx apart is our focus on efficiency and ease of use for analysts and our active community of 700,000 Alteryx users to support you at every step of your journey. With seamless integration to data everywhere including platforms like Databricks, Snowflake, AWS, Google, SAP, and Salesforce, our platform helps unify siloed data and accelerate getting to insights. Visit Alteryx.com for more information, and to start your free trial. **Average Rating:** 4.6/5.0 **Total Reviews:** 789 **How Do G2 Users Rate Alteryx?** - **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 9.0/10) - **Data Workflows:** 9.2/10 (Category avg: 8.8/10) - **Profiling and Classification:** 8.5/10 (Category avg: 8.5/10) - **Data Joining:** 9.1/10 (Category avg: 8.9/10) **Who Is the Company Behind Alteryx?** - **Seller:** [Alteryx](https://www.g2.com/sellers/alteryx) - **Company Website:** https://www.alteryx.com - **Year Founded:** 1997 - **HQ Location:** Irvine, CA - **Twitter:** @alteryx (26,153 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/903031/ (2,304 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Analyst, Analyst - **Top Industries:** Financial Services, Accounting - **Company Size:** 64% Enterprise, 21% Mid-Market #### What Are Alteryx's Pros and Cons? **Pros:** - Ease of Use (333 reviews) - Automation (148 reviews) - Intuitive (132 reviews) - Easy Learning (102 reviews) - Efficiency (102 reviews) **Cons:** - Expensive (88 reviews) - Learning Curve (80 reviews) - Missing Features (62 reviews) - Learning Difficulty (55 reviews) - Slow Performance (41 reviews) ### 6. [dbt](https://www.g2.com/products/dbt/reviews) dbt is a transformation workflow that lets data teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone who knows SQL can build production-grade data pipelines. **Average Rating:** 4.7/5.0 **Total Reviews:** 206 **How Do G2 Users Rate dbt?** - **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 9.0/10) - **Data Workflows:** 9.1/10 (Category avg: 8.8/10) - **Profiling and Classification:** 8.3/10 (Category avg: 8.5/10) - **Data Joining:** 9.1/10 (Category avg: 8.9/10) **Who Is the Company Behind dbt?** - **Seller:** [dbt Labs](https://www.g2.com/sellers/dbt-labs) - **Year Founded:** 2016 - **HQ Location:** Philadelphia, US - **Twitter:** @getdbt (14,758 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/dbtlabs/ (874 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Data Engineer, Analytics Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 57% Mid-Market, 27% Small-Business #### What Are dbt's Pros and Cons? **Pros:** - Ease of Use (38 reviews) - Features (22 reviews) - Automation (19 reviews) - Transformation (17 reviews) - Integrations (15 reviews) **Cons:** - Limited Functionality (14 reviews) - Dependency Issues (12 reviews) - Steep Learning Curve (10 reviews) - Error Handling (9 reviews) - Error Reporting (9 reviews) ### 7. [DemandTools](https://www.g2.com/products/demandtools/reviews) DemandTools is the secure data quality platform that ensures your data remains your most valuable asset. With DemandTools, you manage your CRM data in minutes, not months, so you always have accurate, report-ready data enabling everyone to do their job more effectively, efficiently, and profitably. By fixing common data problems, automating data quality routines, and working within your specific processes and customizations, DemandTools gives stakeholders accurate insights and reporting, improves business efficiency, and gets you clean data faster, with less effort. DemandTools has 12 modules making it the most versatile and adaptable data quality solution for CRM. Data Quality Assessment Understand how strong or weak your data is and know where to focus remediation efforts. Module: Assess Duplicate Management Detect, eliminate, and prevent duplicate records from misleading your sales and marketing teams and causing friction in your customer journey. Modules: Dedupe, Convert, DupeBlocker, Match Data Migration Management Maintain data integrity while moving data into and out of Salesforce. Modules: Import, Export, Delete, Match Standardization, mass modification, and business insights. Apply record changes en masse and standardize data to get trustworthy insights in every report. Modules: Modify, Tune, Reassign Email Verification Verify email addresses in CRM to keep communication flowing with your customers. Module: Verify Get clean data and strengthen your business with DemandTools. DemandTools is part of the Validity portfolio, alongside BriteVerify for contact data validation and Litmus for email testing and deliverability — giving enterprise revenue and marketing teams a connected solution for data integrity, email performance, and program execution. **Average Rating:** 4.6/5.0 **Total Reviews:** 275 **How Do G2 Users Rate DemandTools?** - **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 9.0/10) - **Data Workflows:** 9.1/10 (Category avg: 8.8/10) - **Profiling and Classification:** 8.8/10 (Category avg: 8.5/10) - **Data Joining:** 9.2/10 (Category avg: 8.9/10) **Who Is the Company Behind DemandTools?** - **Seller:** [Validity Inc](https://www.g2.com/sellers/validity-inc) - **Company Website:** https://www.validity.com - **Year Founded:** 2018 - **HQ Location:** Boston, Massachusetts - **Twitter:** @TrustValidity (1,151 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/11679353/ (349 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Salesforce Administrator - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 48% Mid-Market, 33% Enterprise #### What Are DemandTools's Pros and Cons? **Pros:** - Ease of Use (14 reviews) - Duplicate Management (8 reviews) - Time-saving (8 reviews) - Efficiency (5 reviews) - Salesforce Integration (5 reviews) **Cons:** - Limited Functionality (3 reviews) - Missing Features (3 reviews) - Learning Curve (2 reviews) - Poor Interface Design (2 reviews) - Slow Loading (2 reviews) ### 8. [Qlik Sense](https://www.g2.com/products/qlik-sense/reviews) Qlik Sense empowers people to make better data-driven decisions and take action. The solution provides augmented analytics for every business need from visualization and dashboards to natural language analytics, custom and embedded analytics, reporting and alerting. Our unique associative technology enhances human intuition with AI-powered insights, offering unmatched capabilities for combining data and exploring information. It indexes the associations in your data, and exposes related and unrelated values as you click, revealing hidden insights that would be missed by query-based tools. And it performs calculations as fast as you can think. Qlik Sense helps users move from passive to active analytics for real-time collaboration and action. And you get robust data integration, application automation and the convenience of SaaS with hybrid multi-cloud capabilities. See why we’ve been named a Gartner Magic Quadrant Leader for Analytics and BI platforms for 11 years in a row. Visit us at [https://www.qlik.com/us/](- https://www.qlik.com/us/products/qlik-sense?utm_medium=referral&utm_source=G2&utm_team=DIG&utm_term=QlikSense&utm_mpt_id=CKMP5D) **Average Rating:** 4.4/5.0 **Total Reviews:** 763 **How Do G2 Users Rate Qlik Sense?** - **Has the product been a good partner in doing business?:** 8.5/10 (Category avg: 9.0/10) - **Data Joining:** 10.0/10 (Category avg: 8.9/10) **Who Is the Company Behind Qlik Sense?** - **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?** - **Who Uses This:** Consultant, Analyst - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 41% Enterprise, 41% Mid-Market #### What Are Qlik Sense's Pros and Cons? **Pros:** - Ease of Use (55 reviews) - Data Visualization (31 reviews) - Analytics (28 reviews) - Insights Discovery (24 reviews) - Features (22 reviews) **Cons:** - Limited Features (17 reviews) - Missing Features (16 reviews) - Expensive (14 reviews) - Data Management (13 reviews) - Learning Curve (13 reviews) ### 9. [Gathr.ai](https://www.g2.com/products/gathr-ai/reviews) Gathr.ai powers AI with complete data context for higher quality intelligence. With day-zero, high-fidelity data discourse, users can get data-backed answers to the ‘why’, ‘what-if’, and ‘how do I’ questions that drive business KPIs forward. This intelligence is delivered natively on top of the organization’s existing data estate — including data warehouses, databases, federated SQL engines, and operational systems. Leading businesses across industries also rely on Gathr.ai to build high-performance data pipelines, bespoke Data+AI solutions, and action-driven analytics experiences. Built for builders, Gathr.ai delivers agility, performance, and control. It snaps into the existing stack — integrating upstream and downstream systems with no extra plumbing. It gives developers starter-kit speed and full extension freedom. **Average Rating:** 4.8/5.0 **Total Reviews:** 33 **How Do G2 Users Rate Gathr.ai?** - **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 9.0/10) - **Data Workflows:** 8.3/10 (Category avg: 8.8/10) - **Profiling and Classification:** 10.0/10 (Category avg: 8.5/10) - **Data Joining:** 8.3/10 (Category avg: 8.9/10) **Who Is the Company Behind Gathr.ai?** - **Seller:** [Gathr.ai](https://www.g2.com/sellers/gathr-ai) - **Year Founded:** 2022 - **HQ Location:** Los Gatos, CA, US - **LinkedIn® Page:** https://www.linkedin.com/company/gathr-one (57 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Associate Software Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 79% Mid-Market, 21% Enterprise #### What Are Gathr.ai's Pros and Cons? **Pros:** - Integrations (9 reviews) - Data Management (7 reviews) - Drag (6 reviews) - Ease of Use (6 reviews) - Easy Integrations (6 reviews) **Cons:** - Access Issues (1 reviews) - Connection Issues (1 reviews) - Difficult Setup (1 reviews) - Lack of Real-Time Data (1 reviews) - Performance Optimization (1 reviews) ### 10. [DataGroomr](https://www.g2.com/products/datagroomr/reviews) DataGroomr is a modern, AI-powered platform purpose-built to ensure exceptional data quality in Salesforce. For organizations that rely on Salesforce to drive sales, marketing, customer support, operations, and finance, clean and reliable data is not optional - it is foundational. Yet traditional data cleansing tools are often complex, brittle, and time-consuming to configure. DataGroomr changes that paradigm. Duplicate records are one of the most common and damaging data quality issues in Salesforce. They distort reporting, frustrate users, degrade customer experiences, and undermine downstream systems. DataGroomr addresses this challenge with advanced artificial intelligence that accurately identifies duplicates across Accounts, Contacts, Leads, and other objects - without requiring filters, rules, or manual tuning. Using state-of-the-art AI matching techniques, DataGroomr detects more duplicates with greater precision than traditional rule-based approaches. The platform requires no upfront configuration and continuously improves over time by learning from your data patterns and user decisions. This adaptive intelligence ensures long-term accuracy as your Salesforce org evolves. Beyond detection, DataGroomr provides powerful, flexible tools to safely merge records at scale. Teams can merge multiple records at once while maintaining full control over how fields are handled, ensuring data integrity and compliance with internal processes. DataGroomr also helps prevent data issues before they happen by deduplicating import files prior to loading them into Salesforce. Data quality goes beyond duplicates alone. DataGroomr offers built-in verification for global email, address, and phone data, helping organizations maintain trusted, enriched records across regions and use cases. A single, intuitive interface provides clear insights into data health, trends, and improvement over time—making data quality visible and actionable. Designed for ease of use, DataGroomr fits seamlessly into Salesforce workflows and is trusted by teams of all sizes. Backed by a responsive and knowledgeable support team, customers can confidently scale their data quality initiatives without added complexity. Discover why DataGroomr consistently earns 5-star reviews on the Salesforce AppExchange - and experience a smarter, simpler approach to Salesforce data quality. Start your free trial at: http://www.datagroomr.com **Average Rating:** 4.8/5.0 **Total Reviews:** 35 **How Do G2 Users Rate DataGroomr?** - **Has the product been a good partner in doing business?:** 9.8/10 (Category avg: 9.0/10) - **Data Workflows:** 8.9/10 (Category avg: 8.8/10) - **Profiling and Classification:** 9.1/10 (Category avg: 8.5/10) - **Data Joining:** 8.3/10 (Category avg: 8.9/10) **Who Is the Company Behind DataGroomr?** - **Seller:** [DataGroomr](https://www.g2.com/sellers/datagroomr) - **Year Founded:** 2018 - **HQ Location:** Philadelphia, PA - **LinkedIn® Page:** https://www.linkedin.com/company/datagroomr/ (6 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Non-Profit Organization Management - **Company Size:** 63% Mid-Market, 20% Small-Business #### What Are DataGroomr's Pros and Cons? **Pros:** - Duplicate Management (21 reviews) - Ease of Use (21 reviews) - Customer Support (17 reviews) - Intuitive (12 reviews) - Salesforce Integration (12 reviews) **Cons:** - Learning Curve (6 reviews) - Complexity (4 reviews) - Difficult Learning Curve (3 reviews) - Difficult Setup (3 reviews) - Learning Difficulty (3 reviews) ### 11. [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?** - **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 9.0/10) - **Data Workflows:** 8.4/10 (Category avg: 8.8/10) - **Profiling and Classification:** 8.4/10 (Category avg: 8.5/10) - **Data Joining:** 8.8/10 (Category avg: 8.9/10) **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 (2,231,239 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) ### 12. [Incorta](https://www.g2.com/products/incorta/reviews) Incorta is the first and only open data delivery platform that enables real-time analysis of live, detailed data across all systems of record—without the need for complex ETL processes. By enabling direct analysis on raw, source-identical data, Incorta provides faster, more accurate insights while removing barriers to exploration. With intuitive low-code/no-code tools, AI-powered querying through Nexus, and prebuilt business data applications, enterprise teams can quickly surface insights, break down technical roadblocks, and make smarter decisions without heavy engineering effort. For more information, please visit www.incorta.com. **Average Rating:** 4.4/5.0 **Total Reviews:** 55 **How Do G2 Users Rate Incorta?** - **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 9.0/10) - **Data Workflows:** 8.7/10 (Category avg: 8.8/10) - **Profiling and Classification:** 8.6/10 (Category avg: 8.5/10) - **Data Joining:** 8.6/10 (Category avg: 8.9/10) **Who Is the Company Behind Incorta?** - **Seller:** [Incorta](https://www.g2.com/sellers/incorta) - **Company Website:** https://www.incorta.com/ - **Year Founded:** 2013 - **HQ Location:** San Mateo, CA - **LinkedIn® Page:** https://www.linkedin.com/company/incorta/ (348 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 56% Enterprise, 29% Mid-Market #### What Are Incorta's Pros and Cons? **Pros:** - Data Integration (1 reviews) - Easy Integrations (1 reviews) - Integrations (1 reviews) **Cons:** - Bugs (1 reviews) ### 13. [OWOX](https://www.g2.com/products/owox/reviews) OWOX Data Marts is a Free Forever Self-Service Analytics Platform that brings live, trusted data to spreadsheets and dashboards of decision-makers. Ask in plain English or click to build – your trusted reports update in real time with no analyst in the loop. With OWOX Data Marts, companies grow revenue as fast as they collect new data by enabling self-service reporting for everyone. Trusted by 165,000+ users in data teams, but also in marketing, finance, and product teams: from fast-scaling startups to global enterprises, OWOX products powers decisions across every department with data people actually trust. ‍ Self-hosted and Cloud Deployment are available to suit any data stack. Imagine a world where exploring data is as easy as driving a car, without the limitations of public transport (traditional BI dashboards) or the cost of a private driver (data analysts). That's exactly what we assure you! **Average Rating:** 4.9/5.0 **Total Reviews:** 290 **How Do G2 Users Rate OWOX?** - **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 9.0/10) **Who Is the Company Behind OWOX?** - **Seller:** [OWOX](https://www.g2.com/sellers/owox) - **Year Founded:** 2002 - **HQ Location:** WALNUT, California - **Twitter:** @owox (435 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1721152/ (68 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Chief Marketing Officer, CEO - **Top Industries:** Marketing and Advertising, Information Technology and Services - **Company Size:** 48% Small-Business, 43% Mid-Market #### What Are OWOX's Pros and Cons? **Pros:** - Ease of Use (21 reviews) - Helpful (15 reviews) - Data Management (14 reviews) - Customer Support (13 reviews) - Analytics (7 reviews) **Cons:** - Data Management Issues (4 reviews) - Error Handling (3 reviews) - Expensive (2 reviews) - Integration Issues (2 reviews) - Lack of Information (2 reviews) ### 14. [SAS Data Management](https://www.g2.com/products/sas-data-management/reviews) SAS Data Management is a comprehensive solution designed to transform raw data into a valuable business asset by improving, integrating, managing, and governing data across an organization. It enables users to access data from various sources, create rules, collaborate with teams, and manage metadata, thereby preparing data for analytics and informed decision-making. Key Features and Functionality: - Data Access and Integration: Seamlessly access data from diverse sources, including legacy systems and modern platforms like Hadoop, ensuring comprehensive data integration. - Data Quality and Cleansing: Utilize embedded tools to automatically identify and rectify data quality issues, reducing errors and inconsistencies. - Data Preparation: Prepare data for analytics and reporting in a self-service environment without the need for coding or IT assistance, enhancing productivity. - Data Governance: Implement consistent policies and processes to ensure data conforms to established standards and regulatory requirements. - Personal Data Protection: Identify and monitor personal data sources to comply with privacy regulations such as GDPR. - Data Federation and Stewardship: Simplify data integration complexities with a virtual data environment that delivers a complete data picture in a user-friendly format. Primary Value and Solutions Provided: SAS Data Management addresses the critical need for organizations to manage their data effectively, turning it into a strategic asset. By providing a unified platform for data access, integration, quality, governance, and master data management, it eliminates the need for multiple, overlapping tools. This consolidation leads to improved data accuracy, streamlined operations, and enhanced decision-making capabilities. Organizations can ensure that all internal and third-party data remains clean and well-managed, facilitating compliance with regulatory standards and enabling more efficient and effective business processes. **Average Rating:** 4.1/5.0 **Total Reviews:** 97 **How Do G2 Users Rate SAS Data Management?** - **Has the product been a good partner in doing business?:** 8.1/10 (Category avg: 9.0/10) - **Data Workflows:** 9.8/10 (Category avg: 8.8/10) - **Profiling and Classification:** 9.6/10 (Category avg: 8.5/10) - **Data Joining:** 9.6/10 (Category avg: 8.9/10) **Who Is the Company Behind SAS Data Management?** - **Seller:** [SAS Institute Inc.](https://www.g2.com/sellers/sas-institute-inc-df6dde22-a5e5-4913-8b21-4fa0c6c5c7c2) - **Year Founded:** 1976 - **HQ Location:** Cary, NC - **Twitter:** @SASsoftware (60,863 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1491/ (18,638 employees on LinkedIn®) - **Phone:** 1-800-727-0025 **Who Uses This Product?** - **Top Industries:** Higher Education, Research - **Company Size:** 51% Enterprise, 26% Small-Business #### What Are SAS Data Management's Pros and Cons? **Pros:** - Ease of Use (12 reviews) - Analytics (5 reviews) - Data Cleaning (4 reviews) - Data Quality (4 reviews) - Data Management (3 reviews) **Cons:** - Expensive (7 reviews) - Not User-Friendly (3 reviews) - Slow Performance (3 reviews) - Training Required (3 reviews) - Complexity (2 reviews) ### 15. [Savant Labs](https://www.g2.com/products/savant-labs/reviews) Savant is an AI automation platform built for enterprise finance, tax, and accounting teams. It turns messy, manual data work like extraction, preparation, reconciliation, and reporting into centrally governed workflows, so teams can be more efficient without sacrificing accuracy, control, or compliance. Trusted by Fortune 500 enterprises, Savant catches errors before they're filed, ensures audit readiness without the scramble, and gives finance teams their time back. WHAT SETS SAVANT APART Unlike general-purpose AI tools or legacy analytics platforms, Savant was built specifically for finance workflows where 99% accuracy isn't good enough — because 1% errors at scale become audit findings, restatements, and compliance exposure. Three things make Savant different - Deterministic, not probabilistic: Savant uses rule-based AI agents, not LLM guesses. Consistent inputs produce consistent outputs. - Governance is built in, not bolted on: Audit trail, data lineage, SOX controls, and role-based access are standard, not add-ons. - Handles the data other tools can't: Native processing for PDFs, scanned documents, and invoices — the unstructured data that breaks legacy workflows. KEY FEATURES - AI-powered data automation: Automate any data task end to end — prep, blending, transformation, publishing, and alerting. Works with structured and unstructured data, including PDFs, scanned documents, and ERP extracts. - Deterministic workflow engine: AI agents follow step-by-step logic with validation at each stage. Same inputs produce the same outputs, every time — no black boxes, no probabilistic guesses. - Built-in audit trail and data lineage: Every workflow step is logged automatically. Complete data lineage from source to output. No manual documentation, no reconstructing steps across email chains. - SOX compliance by design: Segregation of duties, version control, approval management, and user activity history are built in from day one. - Human-in-the-loop exception handling: Savant proactively flags exceptions for human review, allowing analysts to catch errors before they reach a filing. The AI learns from human judgments over time. - 500+ enterprise connectors: Connect to your existing ERPs, CRMs, BI platforms, file systems, email, and more out of the box. - User-friendly interface: No SQL, no code, no IT tickets. If your team can use Excel, they can build and run workflows in Savant. - Enterprise-grade security: SOC 2 Type II, SOC 1 Type II, ISO 27001. SSO/SAML, role-based access control, private cloud and VPC deployment available. USE CASES - Month-end and year-end close automation - Financial reconciliations and tie-outs - Tax provision preparation - State apportionment calculations - Sales and use tax reconciliation - Data extraction from PDFs, invoices, and scanned documents - ERP data consolidation across multiple systems - Intercompany accounting and multi-entity reporting - Audit evidence package preparation - Recurring reporting and dashboard publishing **Average Rating:** 4.7/5.0 **Total Reviews:** 50 **How Do G2 Users Rate Savant Labs?** - **Has the product been a good partner in doing business?:** 9.8/10 (Category avg: 9.0/10) - **Data Workflows:** 9.3/10 (Category avg: 8.8/10) - **Profiling and Classification:** 8.0/10 (Category avg: 8.5/10) - **Data Joining:** 9.4/10 (Category avg: 8.9/10) **Who Is the Company Behind Savant Labs?** - **Seller:** [Savant Labs](https://www.g2.com/sellers/savant-labs) - **Company Website:** https://www.savantlabs.io - **Year Founded:** 2021 - **HQ Location:** San Francisco, California - **LinkedIn® Page:** https://www.linkedin.com/company/savant-labs (61 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software, Logistics and Supply Chain - **Company Size:** 43% Enterprise, 39% Mid-Market #### What Are Savant Labs's Pros and Cons? **Pros:** - Ease of Use (17 reviews) - Customer Support (11 reviews) - User Interface (9 reviews) - Integrations (8 reviews) - Easy Integrations (6 reviews) **Cons:** - Learning Curve (7 reviews) - Learning Difficulty (6 reviews) - Integration Issues (3 reviews) - Access Issues (2 reviews) - Data Management (2 reviews) ### 16. [IBM Watson Studio](https://www.g2.com/products/ibm-watson-studio/reviews) IBM Watson Studio on IBM Cloud Pak for Data is a leading data science and machine learning solution that helps enterprises accelerate AI-powered digital transformation. It allows businesses to scale trustworthy AI and optimize decisions. Build, run, and manage AI models on any cloud through an automated end-to-end AI lifecycle--simplifying experimentation and deployment, speeding up data exploration and preparation, and improving model development and training. Govern and monitor models to mitigate drift and bias, and manage model risk. Build a ModelOps practice that synchronizes application and model pipelines to operationalize responsible, explainable AI across your enterprise. As a key offering of IBM Cloud Pak for Data, a unified data and AI platform, Watson Studio integrates seamlessly with data management services, data privacy and security capabilities, AI application tooling, open source frameworks, and a robust technology ecosystem. It unites teams and empowers businesses to build the modern information architecture that AI requires and infuse it across the organization. IBM Watson Studio is code-optional, allowing both data scientists and business analysts to work on the same platform by providing the best of open source tools along with visual, drag-and-drop capabilities. It enables organizations to tap into data assets and inject predictions into business processes and modern applications—helping them maximize their business value. It's suited for hybrid multicloud environments that demand mission-critical performance, security, and governance. Features include: • AutoAI that eliminates time-consuming, repetitive tasks by automating data preparation, model development, feature engineering and hyperparameter optimization. • Text Analytics for uncovering insights from unstructured data • Drag-and-drop visual model-building with SPSS Modeler • Broad data access – flat files, spreadsheets, major relational databases • Sophisticated graphics engine for building stunning visualizations • Support for Python 3 Notebooks Watson Studio is available via several deployment options: • IBM Cloud Pak for Data – An open, extensible data and AI platform that runs on any cloud • IBM Cloud Pak for Data System – A hybrid cloud, on-premises platform-in-a-box • IBM Cloud Pak for Data as a Service – A set of IBM Cloud Pak for Data platform services fully managed on the IBM Cloud **Average Rating:** 4.2/5.0 **Total Reviews:** 161 **How Do G2 Users Rate IBM Watson Studio?** - **Has the product been a good partner in doing business?:** 8.0/10 (Category avg: 9.0/10) - **Data Workflows:** 9.2/10 (Category avg: 8.8/10) - **Profiling and Classification:** 9.0/10 (Category avg: 8.5/10) - **Data Joining:** 9.1/10 (Category avg: 8.9/10) **Who Is the Company Behind IBM Watson Studio?** - **Seller:** [IBM](https://www.g2.com/sellers/ibm) - **Year Founded:** 1911 - **HQ Location:** Armonk, New York, United States - **Twitter:** @IBMSecurity (74,679 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (328,202 employees on LinkedIn®) - **Ownership:** SWX:IBM **Who Uses This Product?** - **Who Uses This:** Software Engineer, CEO - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 50% Enterprise, 31% Small-Business #### What Are IBM Watson Studio's Pros and Cons? **Pros:** - AI Capabilities (4 reviews) - AI Technology (4 reviews) - Ease of Use (4 reviews) - Machine Learning (4 reviews) - AI Integration (3 reviews) **Cons:** - Expensive (3 reviews) - Learning Curve (3 reviews) - Steep Learning Curve (3 reviews) - Complex Interface (1 reviews) - Complexity (1 reviews) ### 17. [Plauti](https://www.g2.com/products/plauti/reviews) Plauti keeps your CRM data accurate, complete, and ready for business. Verify, deduplicate, manipulate, and assign records automatically so your teams can trust their data and act fast. Because when data is right, actions are right. And when actions are right, trust follows. - Verify: validate and format addresses, emails and phone numbers - Plauti Agentforce: power agents with data management actions - Deduplicate: find, prevent and merge duplicate records - Assign: route and assign any record instantly - Manipulate: handle data in single-action execution - Restore: Restore record changes across your data within Salesforce Whether you're improving customer experience, achieving AI readiness, improving data governance or driving operational efficiency, the solutions work together to turn scattered data into a trusted resource that fuels confident decision-making and business growth. \> 100% Native to Salesforce - No external processing, full data control. \> Enterprise security -Salesforce compliance, no third-party risks. \> No-Code customization - Adapt workflows easily, without IT reliance. \> Scalable & efficient - Automate processes and manage data at scale. **Average Rating:** 4.5/5.0 **Total Reviews:** 114 **How Do G2 Users Rate Plauti?** - **Has the product been a good partner in doing business?:** 9.2/10 (Category avg: 9.0/10) **Who Is the Company Behind Plauti?** - **Seller:** [Plauti](https://www.g2.com/sellers/plauti) - **Company Website:** https://plauti.com/ - **Year Founded:** 2011 - **HQ Location:** Arnhem, Netherlands - **LinkedIn® Page:** https://www.linkedin.com/company/plauti-b-v-/ (58 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Non-Profit Organization Management, Computer Software - **Company Size:** 55% Mid-Market, 35% Small-Business #### What Are Plauti's Pros and Cons? **Pros:** - Ease of Use (30 reviews) - Duplicate Management (29 reviews) - Customer Support (19 reviews) - Merging Leads (16 reviews) - Customization (10 reviews) **Cons:** - Learning Curve (8 reviews) - Complexity (7 reviews) - Data Management Issues (6 reviews) - Limitations (6 reviews) - Limited Functionality (6 reviews) ### 18. [Solvexia](https://www.g2.com/products/solvexia/reviews) Solvexia is the reconciliation platform built for complex, high-volume finance operations. It is used by finance and accounting teams that have outgrown spreadsheets and basic reconciliation tools, and need a platform that handles the scale, complexity, and data fragmentation that standard solutions cannot. Most reconciliation tools work well for simple, structured data. Solvexia is designed for environments where matching is difficult, data comes from multiple disconnected sources, and manual workarounds have become the norm. In high-volume environments, that gap between what standard tools can do and what the business actually requires is where Solvexia operates. Who uses Solvexia? Solvexia is typically used by mid-sized and enterprise finance teams running high-volume reconciliation processes across multiple data sources and entities. Common users include financial controllers, reconciliation managers, and finance operations teams responsible for transaction reconciliation, regulatory reporting, financial close activities, and data validation at scale. It is commonly adopted when ERP reconciliation breaks down under the weight of non-standard matching rules or unexpected data volumes, when spreadsheet workarounds have become unmanageable, or when the reconciliation process itself — not just the management of it — is the bottleneck. Core capabilities: 1. Matching intelligence that handles what others can't Solvexia automates reconciliation at a level of complexity where other tools break down. It supports one-to-many and many-to-many matching, partial matches, and timing differences across fragmented, multi-source data. Exceptions are handled automatically, without manual workarounds, and match rates are maintained even as data complexity and transaction volumes increase. Across finance teams dealing with high transaction volumes and non-standard matching requirements, Solvexia is known for maintaining high match rates where other platforms require manual intervention to fill the gaps. 2. Data connectivity across every source Solvexia connects every data source into a single automated reconciliation workflow. ERPs, bank files, payment processors like Stripe and PayPal, Excel, APIs, and databases all feed into one process, regardless of format or volume. There is no need to normalize data before it enters the platform or build custom pipelines to make sources compatible. In high-volume environments where data is spread across multiple systems with inconsistent formats, Solvexia centralizes the entire process without requiring technical resources to maintain the connections. 3. Built to scale with transaction volume, not against it Unlike tools that slow down or produce degraded match rates as data volumes grow, Solvexia is built for it. The platform handles thousands to millions of transactions without performance trade-offs, making it suitable for organizations where transaction volumes fluctuate significantly or are expected to grow. Solvexia is often used when finance teams have hit the ceiling of what their current reconciliation tool or spreadsheet process can handle, and need a platform that scales with the business rather than requiring a rebuild every time volume increases. 4. Finance-led automation, no IT dependency Workflows in Solvexia are built and maintained by finance teams, not developers. Matching logic, workflow rules, and data connections are all configurable without custom code or technical resources. There is no IT backlog standing between a finance team and a working reconciliation process, and no dependency on development resources to make changes when business requirements evolve. This matters in practice: finance teams can implement, adjust, and maintain their own processes independently, which reduces time-to-value and keeps the platform responsive to how the business actually works. 5. Workflow control and process governance Solvexia provides configurable workflows that support approvals, reviews, commentary, and audit trails. These controls allow finance teams to enforce consistent process execution, manage exceptions, and maintain the documentation required for audit and compliance purposes, without relying on manual tracking or email-based sign-off processes. How Solvexia compares Solvexia is faster to implement than enterprise compliance platforms, which are built around audit infrastructure and require significant upfront configuration. For finance teams that need matching intelligence and workflow flexibility without the enterprise overhead, Solvexia delivers the core reconciliation capability at a fraction of the cost and implementation timeline, typically 90 days. Unlike close management tools that focus on visibility into the month-end close process, Solvexia is built for teams where the reconciliation work itself is the hard problem. If the bottleneck is inside the close, not the coordination of it, Solvexia goes deeper. Compared to ERP-native reconciliation functionality, Solvexia handles the scenarios where standard tools break down: non-standard matching rules, data sources that do not conform to expected formats, and transaction volumes that exceed what the ERP was designed to support. Finance teams can configure Solvexia to adapt to the business, rather than adapting the business to fit the tool. Typical use cases: Solvexia is typically used for transaction and account reconciliation, intercompany reconciliation, payment reconciliation across processors and banks, regulatory and management reporting, rebate and incentive calculations, financial close support, and ongoing data quality monitoring across multiple entities and systems. **Average Rating:** 4.7/5.0 **Total Reviews:** 30 **How Do G2 Users Rate Solvexia?** - **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 9.0/10) - **Data Workflows:** 8.7/10 (Category avg: 8.8/10) - **Profiling and Classification:** 8.4/10 (Category avg: 8.5/10) - **Data Joining:** 9.1/10 (Category avg: 8.9/10) **Who Is the Company Behind Solvexia?** - **Seller:** [Solvexia](https://www.g2.com/sellers/solvexia) - **Year Founded:** 2008 - **HQ Location:** Sydney, AU - **Twitter:** @solvexia (1,105 Twitter followers) - **LinkedIn® Page:** https://au.linkedin.com/company/solvexia-automation (15 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Financial Services, Staffing and Recruiting - **Company Size:** 45% Small-Business, 42% Mid-Market #### What Are Solvexia's Pros and Cons? **Pros:** - Automation (1 reviews) - Ease of Use (1 reviews) - Integrations (1 reviews) - Platform Integration (1 reviews) - Time-saving (1 reviews) **Cons:** - Limited Functionality (1 reviews) - Missing Features (1 reviews) ### 19. [Altair Monarch](https://www.g2.com/products/altair-monarch/reviews) An industry leader with over 30 years of experience in data discovery and transformation, Altair Monarch offers the fastest and easiest way to extract data from any source. Simple to construct workflows that require no coding enable users to collaborate as they transform difficult data such as PDFs spreadsheets, text files, as well as from big data and other structured sources, into rows and columns. Whether data is on premises or in the cloud, Altair can automate preparation tasks for expedited results and deliver data you trust for smart business decision making. To learn more about Altair Monarch or download a free version of its enterprise software, please click the links below. **Average Rating:** 4.5/5.0 **Total Reviews:** 91 **How Do G2 Users Rate Altair Monarch?** - **Has the product been a good partner in doing business?:** 8.4/10 (Category avg: 9.0/10) - **Data Workflows:** 9.2/10 (Category avg: 8.8/10) - **Profiling and Classification:** 9.0/10 (Category avg: 8.5/10) - **Data Joining:** 9.1/10 (Category avg: 8.9/10) **Who Is the Company Behind Altair Monarch?** - **Seller:** [Altair](https://www.g2.com/sellers/altair-186799f5-3238-493f-b3ad-b8cac484afd7) - **Year Founded:** 1985 - **HQ Location:** Troy, MI - **LinkedIn® Page:** https://www.linkedin.com/company/8323/ (2,774 employees on LinkedIn®) - **Ownership:** NASDAQ:ALTR - **Total Revenue (USD mm):** $458 **Who Uses This Product?** - **Top Industries:** Financial Services, Hospital & Health Care - **Company Size:** 54% Enterprise, 27% Mid-Market ### 20. [Alteryx Designer Cloud](https://www.g2.com/products/alteryx-alteryx-designer-cloud/reviews) Designer Cloud powered by Trifacta is part of the Alteryx Analytics Cloud platform. Designer Cloud democratizes data analytics across the organization with an open and interactive cloud platform for anyone who works with data to collaboratively profile, prepare, and pipeline data for analytics and machine learning. Organizations can connect to any data source, across all major cloud data platforms, and integrate Alteryx Analytics Cloud seamlessly into the existing data stack. Designer Cloud provides an interactive, visual user experience with AI/ML-based suggestions to guide users through the exploration and transformation of any dataset. **Average Rating:** 4.4/5.0 **Total Reviews:** 151 **How Do G2 Users Rate Alteryx Designer Cloud?** - **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 9.0/10) - **Data Workflows:** 8.6/10 (Category avg: 8.8/10) - **Profiling and Classification:** 8.4/10 (Category avg: 8.5/10) - **Data Joining:** 8.8/10 (Category avg: 8.9/10) **Who Is the Company Behind Alteryx Designer Cloud?** - **Seller:** [Alteryx](https://www.g2.com/sellers/alteryx) - **Year Founded:** 1997 - **HQ Location:** Irvine, CA - **Twitter:** @alteryx (26,153 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/903031/ (2,304 employees on LinkedIn®) - **Ownership:** Private **Who Uses This Product?** - **Top Industries:** Information Technology and Services, Hospital & Health Care - **Company Size:** 35% Small-Business, 35% Enterprise ### 21. [KNIME](https://www.g2.com/products/knime-analytics-platform/reviews) KNIME helps everybody make sense of data. Its free and open source KNIME Analytics Platform enables anyone — whether they come from a business, technical or data background — to intuitively work with data, every day. KNIME Business Hub is the commercial complement to KNIME Analytics Platform and enables users to collaborate on data science and share insights across the organization. Together, the products support the complete data science lifecycle, allowing teams at all levels of analytics readiness to support the operationalization of data and to build a scalable data science practice. **Average Rating:** 4.4/5.0 **Total Reviews:** 86 **How Do G2 Users Rate KNIME?** - **Has the product been a good partner in doing business?:** 8.2/10 (Category avg: 9.0/10) **Who Is the Company Behind KNIME?** - **Seller:** [KNIME](https://www.g2.com/sellers/knime) - **Company Website:** https://knime.com - **Year Founded:** 2008 - **HQ Location:** Zurich, Switzerland - **Twitter:** @knime (8,001 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/692207?trk=tyah&trkInfo=clickedVertical%3Acompany%2CclickedEntityId%3A692207%2Cidx%3A2-1-4%2CtarId%3A1454002156993%2Ctas%3Aknime (241 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Information Technology and Services, Higher Education - **Company Size:** 45% Enterprise, 34% Mid-Market #### What Are KNIME's Pros and Cons? **Pros:** - Ease of Use (7 reviews) - Coding Ease (4 reviews) - Ease of Learning (4 reviews) - Learning (4 reviews) - Data Visualization (3 reviews) **Cons:** - Learning Difficulty (3 reviews) - Memory Usage (3 reviews) - Storage Limitations (3 reviews) - Data Management Issues (2 reviews) - Insufficient Learning Resources (2 reviews) ### 22. [TIMi](https://www.g2.com/products/timi/reviews) TIMi is the most efficient Data Science and Data Processing Platform. Since 2007, we have been creating and improving the most powerful framework to push the barriers of analytics, predictive analytics, AI and Big Data, while offering a helpful, fast and friendly environment. The TIMi Suite consists of four tools: 1. Anatella (Analytical ETL, Data Prep & Big Data), 2. Modeler (Auto-ML / Automated Predictive Modelling / Automated-AI), 3. StarDust (3D Segmentation) 4. Kibella (BI Dashboarding solution). TIMi dominates the Data Science market: In the "Summer 2022 - Momentum Report” from G2, in the “Data Science” category, TIMi has the #1 rank: TIMi is the Data Science solution with both the highest market growth and the highest customer-satisfaction! More about this subject here: https://timi.eu/blog/timi-the-number-one-data-science-platform/ **Average Rating:** 4.8/5.0 **Total Reviews:** 50 **How Do G2 Users Rate TIMi?** - **Has the product been a good partner in doing business?:** 9.1/10 (Category avg: 9.0/10) - **Data Workflows:** 9.0/10 (Category avg: 8.8/10) - **Profiling and Classification:** 8.5/10 (Category avg: 8.5/10) - **Data Joining:** 9.3/10 (Category avg: 8.9/10) **Who Is the Company Behind TIMi?** - **Seller:** [TIMi SPRL](https://www.g2.com/sellers/timi-sprl) - **Year Founded:** 2007 - **HQ Location:** Brussels - **Twitter:** @TIMiSuite (3,532 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/timisuite/ (86 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Information Technology and Services, Banking - **Company Size:** 40% Small-Business, 32% Enterprise #### What Are TIMi's Pros and Cons? **Pros:** - Customer Support (2 reviews) - Ease of Use (2 reviews) - Features (2 reviews) - Automation (1 reviews) - Charting Features (1 reviews) ### 23. [OneSchema](https://www.g2.com/products/oneschema/reviews) OneSchema automates CSV & PDF workflows with AI. Enterprise operations, IT, and data engineering teams use OneSchema to replace brittle scripts and save countless hours of time manually cleaning messy files. Features like our schema builder prevent data quality issues and guarantee bad data never enters your business systems. AI-powered transforms in our no-code workflow builder are flexible and fast to configure on any file, empowering the entire operations team to work like data engineers. Companies like Toast, Ramp, Hippocratic AI, and Huron Consulting Group rely on OneSchema to run their most critical file integrations, with thousands of files processed every hour. **Average Rating:** 4.6/5.0 **Total Reviews:** 47 **How Do G2 Users Rate OneSchema?** - **Has the product been a good partner in doing business?:** 9.0/10 (Category avg: 9.0/10) - **Data Workflows:** 9.2/10 (Category avg: 8.8/10) - **Profiling and Classification:** 8.4/10 (Category avg: 8.5/10) - **Data Joining:** 8.8/10 (Category avg: 8.9/10) **Who Is the Company Behind OneSchema?** - **Seller:** [OneSchema](https://www.g2.com/sellers/oneschema) - **Year Founded:** 2021 - **HQ Location:** San Francisco, California - **Twitter:** @oneschema_co (218 Twitter followers) - **LinkedIn® Page:** http://www.linkedin.com/company/oneschema (18 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 50% Small-Business, 44% Mid-Market #### What Are OneSchema's Pros and Cons? **Pros:** - Community Support (1 reviews) - Customer Support (1 reviews) - Customization (1 reviews) - Ease of Use (1 reviews) - Helpful (1 reviews) **Cons:** - Limited Customization (1 reviews) - Poor Interface Design (1 reviews) - Poor User Experience (1 reviews) - UX Improvement (1 reviews) ### 24. [IBM Databand](https://www.g2.com/products/ibm-databand/reviews) Detect and resolve your data issues faster than ever with Databand. The only continuous data observability platform that catches bad data before it impacts your business. Book a demo today --\> https://www.ibm.com/account/reg/us-en/signup?formid=DEMO-dataaidataband CORE CAPABILITIES Incident Management Improve data reliability and quality under one roof with a single pane of glass for all your data incidents. Data Reliability Monitoring Monitor data pipeline errors such as failed runs, longer than expected durations, missing data operations, and unexpected schema changes. Data Quality Metrics Continuously validate data quality with dataset metrics for SLAs, column changes, and null records. Anomaly Detection Eliminate the unknown by seeing trends & detecting anomalies from your metadata in real time. DataOps Alerting and Routing Customize incident alerts and route notifications to impacted DataOps teams for faster resolution. End-to-end Lineage Visualize how data incidents impact upstream and downstream components of your data stack. Website www.ibm.com/products/databand **Average Rating:** 4.3/5.0 **Total Reviews:** 65 **How Do G2 Users Rate IBM Databand?** - **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 9.0/10) - **Data Workflows:** 8.8/10 (Category avg: 8.8/10) - **Profiling and Classification:** 8.3/10 (Category avg: 8.5/10) - **Data Joining:** 8.8/10 (Category avg: 8.9/10) **Who Is the Company Behind IBM Databand?** - **Seller:** [IBM](https://www.g2.com/sellers/ibm) - **Year Founded:** 1911 - **HQ Location:** Armonk, New York, United States - **Twitter:** @IBMSecurity (74,679 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (328,202 employees on LinkedIn®) - **Ownership:** SWX:IBM **Who Uses This Product?** - **Who Uses This:** Software Engineer, Data Analyst - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 44% Mid-Market, 33% Enterprise #### What Are IBM Databand's Pros and Cons? **Pros:** - Anomaly Detection (2 reviews) - Monitoring (2 reviews) - Automation (1 reviews) - Dashboard Customization (1 reviews) - Data Management (1 reviews) **Cons:** - Limited Features (3 reviews) - Expensive (2 reviews) - Integration Issues (2 reviews) - Learning Difficulty (2 reviews) - Missing Features (2 reviews) ### 25. [Visier](https://www.g2.com/products/visier/reviews) Visier gives organizations a Workforce AI Edge: a set of AI-powered capabilities that help leaders understand the relationship between people and work, elevate employee productivity, and win by adapting to change faster. The company is the global leader in AI-powered people analytics, workforce planning, and compensation allocation. All Visier technology is underpinned by its Real-time People Data Platform, which uses AI to unlock the business-transforming potential of people data, work data, and the fusion of both. Founded in 2010 by the pioneers of business intelligence, Visier has over 60,000 customers in 75 countries—including enterprises like BASF, Panasonic, Experian, Amgen, eBay, Ford Motor Company, and more. To learn more about Visier, visit www.visier.com. **Average Rating:** 4.6/5.0 **Total Reviews:** 219 **How Do G2 Users Rate Visier?** - **Has the product been a good partner in doing business?:** 9.1/10 (Category avg: 9.0/10) - **Data Workflows:** 8.1/10 (Category avg: 8.8/10) - **Profiling and Classification:** 7.9/10 (Category avg: 8.5/10) - **Data Joining:** 7.7/10 (Category avg: 8.9/10) **Who Is the Company Behind Visier?** - **Seller:** [Visier](https://www.g2.com/sellers/visier-8c589666-edc0-409b-b9fb-0df31e55c335) - **Year Founded:** 2010 - **HQ Location:** Vancouver, British Columbia - **Twitter:** @visier (6,164 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/visier-analytics/ (555 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Hospital & Health Care, Information Technology and Services - **Company Size:** 82% Enterprise, 17% Mid-Market #### What Are Visier's Pros and Cons? **Pros:** - Ease of Use (25 reviews) - Data Analysis (22 reviews) - Insights (19 reviews) - Data Visualization (18 reviews) - Time-saving (18 reviews) **Cons:** - Learning Difficulty (12 reviews) - Expensive (11 reviews) - Learning Curve (8 reviews) - Complexity (7 reviews) - Limited Customization (7 reviews) ## What Is Data Preparation Software? [IT Infrastructure Software](https://www.g2.com/categories/it-infrastructure) ## What Software Categories Are Similar to Data Preparation Software? - [Data Quality Tools](https://www.g2.com/categories/data-quality) - [Analytics Platforms](https://www.g2.com/categories/analytics-platforms) - [ETL Tools](https://www.g2.com/categories/etl-tools) --- ## How Do You Choose the Right Data Preparation Software? ### What You Should Know About Data Preparation Software ### What are data preparation tools and software? The amount of data companies collect is staggering. Even a mid-sized business can quickly generate millions of raw data points about its customers, business, and technology performance. As a company’s analytics multiply, proper data management can become insurmountable for even the most seasoned data prep expert — not to mention companies without a specialist on hand. Data prep tools are designed to rummage through this pile of data and aggregate relevant insights for users. These tools are increasingly valuable and necessary for businesses with an endless influx of large data sets. These tools help draw valuable conclusions about important data points through the noise of excess information. A popular term for this process is called data wrangling. Data wrangling evokes the full capabilities of these tools. They can mine useful, relevant analytics from an overwhelming stream of different data sources. Modern businesses must make timely, critical decisions in response to the diverse insights generated by these data wrangling tools. These tools compile real-time analytics about product users, sales numbers, system performance, and more. The tools in this emerging space help streamline the data preparation process, gleaning precise information from large data sets. As a business’s data piles up, data prep tools enable users to find important data points with the push of a button. This way, companies can leverage actionable insights immediately without sorting through hours of data. ### Key benefits of using data preparation tools - Performing comprehensive scans of large data sets from disparate data sources - Profiling relevant data based on custom workflows and filters - Blending actionable data from large, distributed sets into a clean, optimized file - Enabling faster, more accurate analysis of relevant information without the need for manual combing of databases ### Why use data preparation solutions? In the early days of analytics, a small team would be responsible for manually preparing data — managing quality assurance for an entire company’s database, and pulling together actionable insights. This is still the case for thousands of organizations across multiple industries. As technology advances, the volume of unstructured data has grown immensely. People generate more data than businesses know what to do with, creating a unique and unprecedented challenge for data science experts and executives trying to make sense of the analytics. Data prep technology was created out of this growing necessity, with the ability to pick through massive amounts of unstructured data and present only the data points that matter for a given scenario. This relieves IT specialists of this strenuous task and makes an impossible amount of data more digestible. In addition to finding, profiling, and combining data based on user specifications, certain solutions in this category assist with data transformation or converting data types into different forms or structures for analysis purposes. This creates a unified view of the most relevant analytics for convenient analysis and eventual exporting into external systems. Just as the amount of data has increased in recent years, so has the variety of data types, formats, and sources. Data preparation platforms work to identify or profile the most valuable data across these various types and deliver it in the most useful way for each new scenario. These advanced tools can save employees time while creating opportunities with previously unattainable data, especially if a business has an extensive portfolio of data sources. ### Who uses data prep tools? The solutions in this category benefit companies with a substantial pool of data and a complex network of data sources. For smaller companies in certain industries, data prep may still be a manual process that does not require new technology. However, since many organizations utilize various types of software and third-party partnerships, they generate mountains of data on a daily basis. As a result, more and more businesses are eligible for these tools. The following teams or individuals will most likely use these solutions in a given organization. **IT specialists —** If a company has an IT department, these employees are the most logical choice for general data and test data preparation. IT specialists already have a comprehensive view of the computer systems and software platforms used across an organization. They may already be the primary owners of analytics tasks such as data enrichment and data cleaning. The analytics platforms featured in this category empower IT specialists to expedite the quality assurance process and create clean data sets for internal use or to be shared across their organization. **Data analysts and engineers —** As the data realm has swelled in size, tech-forward companies have started to seek designated employees to collect and draw conclusions from company analytics. These data analyst roles are typical in organizational structures and third-party agency settings, such as [data governance services providers](https://www.g2.com/categories/data-governance-services). Whether employed with one of these firms or on a company’s full-time staff, data specialists benefit from one of the tools in this space. In some cases, data prep will be a daily responsibility in this line of work. Pulling various data sets for additional analysis or tests and using the results to influence business outcomes emphasizes the impact this technology can have on a given organization. The correct data prep solution can be an indispensable asset for data engineers, analytics executives, and others with a strong focus on data work. ### Features of data preparation software solutions The robust tools in this software category offer a diverse range of functionalities related to the process of data preparation. The following are some prominent features of these unique offerings. **Workflow scheduling and monitoring —** Depending on the intended use of these tools, employees may want to map out an automated query to prepare certain groupings of data regularly. This might involve a custom data flow builder or a similar user interface for customization. Using these tools, administrators can adjust the specific details of each workflow, including analytics filters, which sources to pull from, and the schedule for executing the query. A company may be able to adjust other components of the process, such as validation details and the destination for exporting finished data sets. Dashboards on some tools can help display analytics related to data prep workflows, including general efficiency and results summaries. As a company creates data prep queries, whether for one-off events or routine workflows, a company may be able to configure the data blending and joining process as it relates to each function. Data blending is another common term used to describe the merging of analytics from separate sets into a cohesive group to draw conclusions and continued analysis. When configuring the intelligent algorithms on these platforms, companies can specify how they want the data joined together and presented, for instance, which data type they prefer and how the data should be ordered. Whether called data preparation, data wrangling, or data blending, the solutions in this category can assist with this increasingly popular business strategy to help bring divergent analytics together for a unified purpose. **Data profiling —** Once the intended analytics are pulled and organized using these tools, certain platforms can assess the data and help determine the additional purposes it can be used for. This is also known as data profiling. Some tools in this category offer more powerful profiling features than others, allowing for rich analytics and summaries about prepared data sets as they are constructed. If data profiling features are not present, a company might assign certain data analysts or other specialists to profile the finished data sets and determine the best course of action to take as the results are delivered. ### Software and services related to data preparation software Depending on the value an organization places on data and the scope of an organization’s technology infrastructure, the analytics lifecycle can be complex and demanding. The following solutions go hand in hand with data preparation tools in collecting, studying, and using company data. They can help an organization make data analysis both practical and rewarding. [**Data visualization software**](https://www.g2.com/categories/data-visualization) **—** Data visualization is the process of turning valuable analytics into visuals that can be studied and shared as needed. Data visualization software lets users import database files and create eye-catching charts and graphs displaying certain findings or data selections in an accessible format. Data preparation platforms often integrate with certain data visualization tools, allowing for prepared data to be quickly and seamlessly converted into dashboards, interactive graphs, or other visual files. Whether a department is presenting company-wide KPIs or complex insights for specific teams or business partners, these solutions are a practical way to make data presentable for others, allowing a company to highlight its findings as desired. [**Business intelligence software**](https://www.g2.com/categories/business-intelligence) **—** Business intelligence software, or BI software, includes data visualization platforms and related technology for analyzing data and revealing the actionable insights scattered across giant pools of information. BI tools are increasingly essential for companies seeking to shape their business strategy around a steady data flow. Many of the tools in these categories require IT assistance for implementation and connecting disparate sources into a functional analytics architecture. Once this information network is established, businesses can leverage it in several ways, including self-service analytics and embedded analytics within business applications. BI tools can create a sturdy foundation of valuable data from multiple sources to build a data preparation strategy and utilize a solution from the data preparation category. [**Data warehouse software**](https://www.g2.com/categories/data-warehouse) **—** Data warehouse software provides a reliable storage hub for the collective data generated across an organization, from the sales department to the software testing team. Analytics tools such as data prep software often sync with an internal data warehouse to analyze large data sets without providing separate storage for these large, critical files. A data infrastructure may require several solutions for companies with many moving parts, each with its specific function. Data warehouses provide secure storage for these massive data files as they expand, freeing up other data platforms to perform their respective functions with little interruption. ### How to choose the best data preparation tool When selecting a data preparation tool, consider a few key factors to ensure it aligns with your unique data needs and organizational resources. First, assess your data's complexity and your team's technical skill level. Some tools are better suited for advanced technical users with programming knowledge, while others are designed for ease of use, making them accessible to non-technical team members. Look for a tool that strikes the right balance between functionality and usability for your team. Next, think about performance and scalability. As your data grows, your tool should be able to handle increased volumes without a dip in efficiency. Make sure the tool integrates smoothly with your existing infrastructure, such as cloud storage, data lakes, or on-premises systems, to avoid compatibility issues down the line. Don’t overlook the specific needs of your data workflows. Consider how often your data is updated and whether you need real-time processing capabilities. Advanced features like data profiling, which helps uncover patterns and quality issues, or specialized data transformation options might be essential for more complex datasets. Evaluate these aspects carefully to ensure the tool meets your immediate and long-term data preparation needs. By evaluating these factors, you’ll be well on your way to choosing a data preparation tool that meets your current requirements and can scale as your organization grows.