# Best Enterprise Data Quality Tools

## How Many Data Quality Tools Products Does G2 Track?

**Total Products under this Category:** 251

### Category Stats (Aug 2026)

- **Average Rating:** 4.48/5 The average rating of products in this category, based on all submitted ratings
- **Top Trending Product:** Data Quality Navigator (+3.87%) - Among all products in this category, Data Quality Navigator recorded the largest rating increase compared to last month

_Last updated: August 01, 2026_

## How Does G2 Rank Data Quality Tools Products?

**Why You Can Trust G2's Software Rankings:**

- 30 Analysts and Data Experts
- 12,200+ Authentic Reviews
- 251+ 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.

## G2 Grid® for Data Quality Tools
 ![G2 Grid® for Data Quality Tools plotting products by satisfaction and market presence](https://www.g2.com/categories/data-quality/grids.png?focus%5B%5D=142449&focus%5B%5D=1613254&focus%5B%5D=444&focus%5B%5D=1327283&focus%5B%5D=108031&focus%5B%5D=135441&focus%5B%5D=39669&focus%5B%5D=148877)

Highlighted products: Monte Carlo, Data Quality Navigator, D&B Connect, SAS Viya, Atlan, GTM Studio - Powered by ZoomInfo, Collibra, and dbt.

Underlying data: [Grid® JSON](https://www.g2.com/categories/data-quality/grids.json?focus%5B%5D=monte-carlo&focus%5B%5D=data-quality-navigator&focus%5B%5D=d-b-connect&focus%5B%5D=sas-sas-viya&focus%5B%5D=atlan&focus%5B%5D=gtm-studio-powered-by-zoominfo&focus%5B%5D=collibra&focus%5B%5D=dbt&segment=enterprise)

**Sponsored**

### DataGroomr

DataGroomr is the leading AI-powered Salesforce data quality platform, helping organizations identify duplicates, merge records, standardize data, enrich information, verify accuracy, and automate ongoing data maintenance all from a single, easy-to-use solution. Clean, reliable data is essential for sales, marketing, customer support, operations, and finance teams. Yet duplicate records, incomplete information, inconsistent formats, and outdated data continue to create costly challenges that impact productivity, reporting accuracy, customer experiences, and business decisions. DataGroomr solves these challenges with advanced artificial intelligence that continuously monitors and improves Salesforce data quality. Unlike traditional tools that depend on complex matching rules and ongoing maintenance, DataGroomr uses AI-powered matching to accurately identify duplicate records across Accounts, Contacts, Leads, and other Salesforce objects with little to no configuration required. The platform helps organizations uncover more duplicates with greater accuracy, merge records safely and efficiently, automate deduplication processes, and prevent new duplicates from entering Salesforce. Intelligent matching continuously learns from data patterns and user actions to improve performance over time. Beyond duplicate management, DataGroomr provides comprehensive data quality capabilities including data standardization, email, phone, and address verification, and agentic data enrichment. Teams can fill in missing information, improve record completeness, maintain consistent formatting, and ensure customer and prospect data remains accurate and actionable. DataGroomr also supports key Salesforce workflows, including lead conversion, bulk record management, and import preparation. Organizations can identify and resolve data quality issues before they impact users, reports, automations, integrations, or downstream systems. With powerful automation, intuitive workflows, and real-time visibility into data quality health, DataGroomr makes it easy to establish and maintain trusted Salesforce data at scale. Customers benefit from improved user confidence, more accurate reporting, stronger operational efficiency, and better business outcomes. Trusted by organizations of all sizes and backed by exceptional customer support, DataGroomr delivers a smarter, simpler approach to Salesforce data quality, helping teams spend less time fixing data and more time using it. Start your free trial at: http://www.datagroomr.com

[Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list_llm&secure%5Bcategory_id%5D=74&secure%5Bchosen_at%5D=2026-08-03T19%3A59%3A02Z&secure%5Bdisplayable_resource_id%5D=74&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=74&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=122216&secure%5Bresource_id%5D=74&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fdata-quality%2Fenterprise%3Fopen_modal_url%3D%252Fproducts%252Fsas-sas-viya%252Fwishlists%253Fhost_path%253D%25252Fcategories%25252Fdata-quality%25252Fenterprise%2526source%253Dcategory&secure%5Btoken%5D=374c21bf7541a108bf9e3546dbe9e3b52febe6a1511cac3ac12a6e154b98cc74&secure%5Burl%5D=https%3A%2F%2Fdatagroomr.com%2F&secure%5Burl_type%5D=company_website)

### [Monte Carlo](https://www.g2.com/products/monte-carlo/reviews)

Monte Carlo is the agent trust platform, trusted by Nasdaq, Cisco, PepsiCo, and hundreds of enterprise organizations worldwide. Founded in 2019 and backed by leading investors, Monte Carlo pioneered data observability and has expanded into the full AI reliability stack. We're consistently ranked #1 in data observability on G2 — and we're built for what comes next. As enterprises scale from dozens to thousands of AI agents across mission-critical use cases, Monte Carlo monitors, troubleshoots, and improves both those agents and the underlying data powering them. Our platform covers the full trust stack — from the data pipelines feeding agents, to the context they retrieve, the decisions they make, and the outputs they produce — across four trust dimensions: context quality, performance, behavior, and outputs. Only Monte Carlo closes the full trust loop across both data and AI, and we meet enterprises wherever they are on the spectrum from human-guided oversight to fully autonomous operations. With 100+ integrations across Snowflake, Databricks, and the rest of your stack, you get full coverage without ripping anything out. Traditional monitoring tools stop at the pipeline or cover only one dimension of reliability — leaving teams to manually investigate, diagnose, and fix failures across disconnected tools. Monte Carlo closes that gap. Teams using Monte Carlo dramatically reduce time to detect and resolve data and AI incidents, scale monitoring coverage without scaling headcount, and build the internal trust that turns AI investments into real business outcomes. If your organization is serious enough about AI to put it in front of customers, executives, and critical decisions — Monte Carlo is the foundation it needs.

**Average Rating:** 4.3/5.0

**Total Reviews:** 532

#### How Do G2 Users Rate Monte Carlo?

- **Quality of Support:** 9.0/10 (Category avg: 8.9/10)
- **Automation:** 7.5/10 (Category avg: 8.7/10)
- **Identification:** 8.1/10 (Category avg: 8.9/10)
- **Preventative Cleaning:** 6.1/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Monte Carlo?

- **Seller:** [Monte Carlo](https://www.g2.com/sellers/monte-carlo)
- **Company Website:** montecarlo.ai
- **Year Founded:** 2019
- **HQ Location:** San Francisco, US
- **Twitter:** @montecarlo\_ai  
1,576 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=8fa88c14d2fc26528b6624093818df7cddee0fa28e5893d4f9039d018929480b&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fmonte-carlo-data%2F&secure%5Burl_type%5D=linkedin_company_website)  
548 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Data Engineer, Senior Data Engineer
- **Top Industries:** Financial Services, Computer Software
- **Company Size:** 50% Large, 42% Medium

#### What Do G2 Reviewers Say About Monte Carlo?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **ease of use** of Monte Carlo, praising its intuitive interface and helpful documentation.
- Users value the **custom alerts and integration** in Monte Carlo, enhancing stakeholder communication and data monitoring efficiency.
- Users find the **monitoring features** of Monte Carlo invaluable for catching data quality issues early and enhancing communication.
- Users appreciate the **custom alerting integration** in Monte Carlo, enhancing communication and data quality monitoring effectively.
- Users value the **easy setup and automated anomaly detection** of Monte Carlo, enhancing data quality and consistency monitoring.

##### Cons

- Users find the lack of **manual threshold settings** for alerts limiting, complicating the adjustment of alert sensitivities.
- Users find the **alert overload** from Monte Carlo's automated monitors to be disruptive and requiring excessive tuning efforts.
- Users face challenges with the **inefficient alert system** , including issues with notifications and complex UI elements.
- Users find the **UX improvement** necessary, citing slow performance and disorganized features as major drawbacks.
- Users find that Monte Carlo has **limited functionality** for custom metrics and manual threshold settings, hindering deeper analysis.

#### What Are Recent G2 Reviews of Monte Carlo?

**["Automated Monitoring and Lineage That Quickly Boost Data Trust"](https://www.g2.com/survey_responses/monte-carlo-review-13033733)**

**Rating:** 4.0/5.0 stars

_— Manga D._

[Read full review](https://www.g2.com/survey_responses/monte-carlo-review-13033733)

**["MonteCarlo: A Powerful Tool for Data Observability and Inspection"](https://www.g2.com/survey_responses/monte-carlo-review-9549414)**

**Rating:** 5.0/5.0 stars

_— Pavan S._

[Read full review](https://www.g2.com/survey_responses/monte-carlo-review-9549414)

#### What Are G2 Users Discussing About Monte Carlo?

- [What is your primary use case for Monte Carlo, and how has it impacted your data observability?](https://www.g2.com/discussions/what-is-your-primary-use-case-for-monte-carlo-and-how-has-it-impacted-your-data-observability)
- [What are the characteristics of Monte Carlo simulation?](https://www.g2.com/discussions/what-are-the-characteristics-of-monte-carlo-simulation)
- [What software is used for Monte Carlo simulation?](https://www.g2.com/discussions/what-software-is-used-for-monte-carlo-simulation)
- [What is Monte Carlo method used for?](https://www.g2.com/discussions/what-is-monte-carlo-method-used-for)
- [What is Monte Carlo software?](https://www.g2.com/discussions/what-is-monte-carlo-software) - 1 comment

### [Data Quality Navigator](https://www.g2.com/products/data-quality-navigator/reviews)

Data Quality Navigator (DQN) is a business-driven, end-to-end data quality platform that enables organizations to understand, improve, and continuously manage data quality in a measurable and scalable way. It moves data quality away from purely technical responsibility and enables business users to take ownership working with intuitive processes that reflect real operational needs. DQN comes with 2,500+ pre-built rules based on real business issues, so organizations don’t have to start from scratch. Instead, they can focus directly on the most critical problems and see measurable improvements within weeks. This fast, impact-focused approach helps stabilize operations early, avoid risks such as failed migrations or production delays, and build continuous improvement over time. Key Functionalities → Data Integration (Seamlessly connect and synchronize data across systems) → Data Profiling & Assessment (Understand data quality and structure) → Data Validation (Choose from over 2,500 predefined validation rules or create your own) → Data Harmonization & Deduplication (Create unified and consistent records) → Data Cleansing (Resolve errors and improve data reliability) → Data Enrichment (Enhance data with additional business context) → Automated Data Quality (Use AI-powered agents to identify, cleanse, enrich, harmonize, and optimize data at scale) → Data Migration (Prepare, map, and validate data for target systems) → Data Governance (Ensure ownership, control, and sustainable quality)

**Average Rating:** 4.7/5.0

**Total Reviews:** 23

#### How Do G2 Users Rate Data Quality Navigator?

- **Quality of Support:** 9.6/10 (Category avg: 8.9/10)
- **Automation:** 9.3/10 (Category avg: 8.7/10)
- **Identification:** 9.6/10 (Category avg: 8.9/10)
- **Preventative Cleaning:** 10.0/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Data Quality Navigator?

- **Seller:** [BearingPoint](https://www.g2.com/sellers/bearingpoint)
- **Company Website:** www.bearingpoint.com
- **Year Founded:** 2002
- **HQ Location:** Amsterdam, North Holland, Netherlands
- **Twitter:** @BearingPoint  
7,317 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=972cc615e13079f0fadbb0a1da5f55a63d263025c3bf57e9e910359e0e63f7b0&secure%5Burl%5D=http%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fbearingpoint&secure%5Burl_type%5D=linkedin_company_website)  
10,062 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 56% Large, 24% Small

#### What Are Recent G2 Reviews of Data Quality Navigator?

**["Powerful Data Quality Cockpit with Fast Implementation and Strong Integrations"](https://www.g2.com/survey_responses/data-quality-navigator-review-13084424)**

**Rating:** 4.5/5.0 stars

_— Yann S._

[Read full review](https://www.g2.com/survey_responses/data-quality-navigator-review-13084424)

**["Improve data quality and save manual inspection time"](https://www.g2.com/survey_responses/data-quality-navigator-review-12847807)**

**Rating:** 4.0/5.0 stars

_— mohamed h._

[Read full review](https://www.g2.com/survey_responses/data-quality-navigator-review-12847807)

### [D&B Connect](https://www.g2.com/products/d-b-connect/reviews)

D&B Connect (the next generation of D&B Optimizer) is an AI-driven Data Management Platform based on the D&B Cloud that provides businesses with customer data and market insights. With D&B Connect, users can collaborate on data management tasks, visualize, monitor, and benchmark data, as well as assess overall data health. Integrations with Master Data Management Platforms, Customer Data Platforms, and CRMs enable automated data updates and anomaly detection through the identity resolution engine. MAP integrations allow for the automation of cross-channel marketing tasks on social media, email, and websites.

**Average Rating:** 4.1/5.0

**Total Reviews:** 131

#### How Do G2 Users Rate D&B Connect?

- **Quality of Support:** 8.5/10 (Category avg: 8.9/10)
- **Automation:** 8.1/10 (Category avg: 8.7/10)
- **Identification:** 8.1/10 (Category avg: 8.9/10)
- **Preventative Cleaning:** 8.1/10 (Category avg: 8.5/10)

#### Who Is the Company Behind D&B Connect?

- **Seller:** [Dun & Bradstreet](https://www.g2.com/sellers/dun-bradstreet)
- **Company Website:** www.dnb.com
- **HQ Location:** Short Hills, NJ
- **Twitter:** @DunBradstreet  
22,541 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=20afd0d2cd48d50cc271386179ca16404da5c8da48609b5c3528ba607428f128&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F2385%2F&secure%5Burl_type%5D=linkedin_company_website)  
5,747 employees on LinkedIn®
- **Ownership:** NYSE: DNB

#### Who Uses This Product?

- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 44% Medium, 31% Small

#### What Do G2 Reviewers Say About D&B Connect?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** of D&B Connect, enjoying seamless integration and simplified data management.
- Users find the **data accuracy** of D&B Connect essential for enhancing growth and streamlining CRM integration.
- Users value the **extensive data quality** in D&B Connect, enhancing record mapping and enriching CRM systems effectively.
- Users appreciate the **easy setup** of D&B Connect, facilitating seamless integration and efficient data enrichment.
- Users value the **accuracy** of D&B Connect, enhancing data insights and supporting compliance and growth effectively.

##### Cons

- Users find **limited control and tracking** over data usage in D&B Connect, leading to confusion and inefficiencies.
- Users find D&B Connect **expensive** , limiting access for smaller businesses due to high pricing tiers and data coverage disparities.
- Users face a challenging **learning curve** with D&B Connect, making it difficult to utilize the tool effectively.
- Users find **limited functionality** in D&B Connect, facing challenges with account creation and contact matching processes.
- Users are frustrated by **missing features** in D&B Connect, such as incomplete data and slow reporting capabilities.

#### What Are Recent G2 Reviews of D&B Connect?

**["Flexibility to enable data governance and improve data quality for the business"](https://www.g2.com/survey_responses/d-b-connect-review-12212327)**

**Rating:** 5.0/5.0 stars

_— Avijit S._

[Read full review](https://www.g2.com/survey_responses/d-b-connect-review-12212327)

**["Seamless CRM Integration with Robust Data Enrichment"](https://www.g2.com/survey_responses/d-b-connect-review-12328160)**

**Rating:** 4.5/5.0 stars

_— Ramy A._

[Read full review](https://www.g2.com/survey_responses/d-b-connect-review-12328160)

#### What Are G2 Users Discussing About D&B Connect?

- [What are the benefits of vitamin d3?](https://www.g2.com/discussions/what-are-the-benefits-of-vitamin-d3) - 1 upvote
- [What happens when your vitamin D is low?](https://www.g2.com/discussions/what-happens-when-your-vitamin-d-is-low) - 1 upvote
- [How do we get vitamin D?](https://www.g2.com/discussions/how-do-we-get-vitamin-d)
- [What does vitamin D do?](https://www.g2.com/discussions/what-does-vitamin-d-do)

### [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:** 774

#### How Do G2 Users Rate SAS Viya?

- **Quality of Support:** 8.4/10 (Category avg: 8.9/10)
- **Automation:** 9.0/10 (Category avg: 8.7/10)
- **Identification:** 8.7/10 (Category avg: 8.9/10)
- **Preventative Cleaning:** 8.8/10 (Category avg: 8.5/10)

#### 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:** www.sas.com
- **Year Founded:** 1976
- **HQ Location:** Cary, NC
- **Twitter:** @SASsoftware  
60,863 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=64db42c044af5bbad79bd9677a620a6c31a8ff1abf4e7b2a6f1d6ed9561d105d&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1491%2F&secure%5Burl_type%5D=linkedin_company_website)  
18,638 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Student, Biostatistician
- **Top Industries:** Pharmaceuticals, Banking
- **Company Size:** 33% Large, 33% Small

#### What Do G2 Reviewers Say About SAS Viya?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **ease of use** of SAS Viya, which simplifies data visualization and enhances decision-making efficiency.
- Users value the **sophisticated analytical capabilities** of SAS Viya, enabling easy deployment and real-time decision-making.
- Users appreciate the **advanced analytical methods** offered by SAS Viya, enhancing decision-making and logistical data analysis capabilities.
- Users value the **end-to-end data lifecycle tooling** of SAS Viya, enhancing business insight and strategic decision-making.
- Users love the **intuitive interface** of SAS Viya, making data analysis and model deployment effortless for all skill levels.

##### Cons

- Users find SAS Viya to have a **learning difficulty** , making it challenging for non-technical individuals to navigate effectively.
- Users find the **learning curve steep** , making it challenging for non-technical users to navigate SAS Viya effectively.
- Users find the **visualization complexity** in SAS Viya challenging, particularly for non-technical users and beginners.
- Users struggle with the **difficult learning curve** of SAS Viya, particularly for new and non-technical users.
- Users find the **expensive pricing** of SAS Viya to be a significant barrier to entry for potential adoption.

#### What Are Recent G2 Reviews of SAS Viya?

**["Effective Data Analysis with SAS Viya"](https://www.g2.com/survey_responses/sas-viya-review-11872818)**

**Rating:** 4.5/5.0 stars

_— Fungai J._

[Read full review](https://www.g2.com/survey_responses/sas-viya-review-11872818)

**["SAS Viya: Powerful AI & Data Analysis with Seamless Integrations"](https://www.g2.com/survey_responses/sas-viya-review-11855145)**

**Rating:** 5.0/5.0 stars

_— Verified User in Hospital & Health Care_

[Read full review](https://www.g2.com/survey_responses/sas-viya-review-11855145)

#### What Are G2 Users Discussing About SAS Viya?

- [What is SAS Visual Data Mining and Machine Learning used for?](https://www.g2.com/discussions/what-is-sas-visual-data-mining-and-machine-learning-used-for) - 2 comments

### [Atlan](https://www.g2.com/products/atlan/reviews)

Atlan is the context layer for enterprise AI. It continuously reads your warehouses, databases, pipelines, BI tools, and business systems to reverse construct an enterprise data graph that captures assets, lineage, entities, metrics, policies, and relationships. On top of that graph, it enriches and curates machine-readable semantics — descriptions, popular joins, KPI and metric definitions, ontologies, and business rules — and organizes them into governed, versioned context repos: bounded bundles of context that reflect how your company defines key concepts and makes decisions. These context repos are then exposed through open interfaces (SQL, APIs, SDKs, OSI/MCP-style protocols) so that agents, copilots, and AI applications can call the same trusted context in real time, rather than each team hard-coding its own logic. Human-on-the-loop governance workflows for conflict resolution, deprecation, feedback, and certification keep that context trustworthy as the business, data, and models evolve.

**Average Rating:** 4.5/5.0

**Total Reviews:** 133

#### How Do G2 Users Rate Atlan?

- **Quality of Support:** 9.2/10 (Category avg: 8.9/10)
- **Automation:** 7.7/10 (Category avg: 8.7/10)
- **Identification:** 7.6/10 (Category avg: 8.9/10)
- **Preventative Cleaning:** 6.8/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Atlan?

- **Seller:** [Atlan](https://www.g2.com/sellers/atlan)
- **Company Website:** www.atlan.com
- **Year Founded:** 2019
- **HQ Location:** New York, US
- **Twitter:** @AtlanHQ  
9,804 Twitter followers
- **LinkedIn® Page:** [in.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=76bdd8566f32b170e53cfee476c7ff510e111497aa6c737d48bedd8b767b15e1&secure%5Burl%5D=https%3A%2F%2Fin.linkedin.com%2Fcompany%2Fatlan-hq&secure%5Burl_type%5D=linkedin_company_website)  
558 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Financial Services, Information Technology and Services
- **Company Size:** 51% Medium, 42% Large

#### What Do G2 Reviewers Say About Atlan?

_AI-generated summary from verified user reviews_

##### Pros

- Users commend Atlan for its **ease of use** , enabling smooth data collaboration and making data management accessible to everyone.
- Users value Atlan's **powerful data discovery and collaboration features** , enhancing data quality, governance, and accessibility.
- Users value the **seamless collaboration** with Atlan, enhancing data understanding and team efficiency across organizations.
- Users appreciate the **superior data cataloging** capabilities of Atlan, enhancing data discovery and collaboration effortlessly.
- Users appreciate the **easy setup** of Atlan, which enhances collaboration and streamlines workflows effortlessly.

##### Cons

- Users face **integration issues** with Atlan, particularly with Teams and non-native database setups requiring complex configurations.
- Users experience significant **dependency issues** in Atlan, hindering functionality and complicating automated updates and integrations.
- Users note the **limited customization** of Atlan, wishing for more flexibility to suit diverse team workflows.
- Users experience **slow technical support** and inaccuracies in resolutions, impacting their overall satisfaction with Atlan.
- Users experience **limited customization and technical complexity** in Atlan's UI, making it challenging for non-technical users.

#### What Are Recent G2 Reviews of Atlan?

**["Visual Design, Collaboration, and Outstanding Customer Support"](https://www.g2.com/survey_responses/atlan-review-13191535)**

**Rating:** 4.5/5.0 stars

_— Verified User in Transportation/Trucking/Railroad_

[Read full review](https://www.g2.com/survey_responses/atlan-review-13191535)

**["Atlan as a Central Metadata Hub with Powerful Lineage and AI-Assisted Documentation"](https://www.g2.com/survey_responses/atlan-review-12758713)**

**Rating:** 4.5/5.0 stars

_— Keith G._

[Read full review](https://www.g2.com/survey_responses/atlan-review-12758713)

### [GTM Studio - Powered by ZoomInfo](https://www.g2.com/products/gtm-studio-powered-by-zoominfo/reviews)

Note: GTM Studio is the upgraded version of ZoomInfo Marketing and ZoomInfo Operations. GTM Studio is ZoomInfo's AI-powered go-to-market canvas that unifies signals, systems, and teams in one intelligent workspace so plays fire automatically, moments aren't missed, and reps always know what to do next. Designed for RevOps and marketing teams, GTM Studio eliminates tool sprawl by connecting CRM, marketing, sales, and third-party data into a single live canvas - giving every team a complete, AI-ready view of their market. At the core of GTM Studio is built-in waterfall enrichment that automatically fills in missing contact and account data across 25+ vendors, so the data powering every play is always complete and actionable. AI-powered insights surface buying signals in real time, helping teams respond to in-market buyers in under five minutes - before competitors have even pulled a list. Every insight is grounded in your ICP, so GTM decisions are faster, sharper, and more informed. GTM Studio is built for speed to execution. A library of pre-built plays - including inbound acceleration, champion tracking, and competitive displacement - can be launched in a single click, with no tickets, no engineering support, and no waiting. Custom plays can be designed, tested, and scaled without code or developer involvement, compressing what used to take weeks into minutes. Specialized AI agents handle enrichment, scoring, routing, and message creation automatically, so teams stay focused on results rather than operations. GTM Studio integrates with the tools revenue teams already rely on - Salesforce, HubSpot, Salesloft, Gong, Slack, and 50+ more - ensuring signals flow freely across the stack and execution happens without friction. Built-in analytics measure what's working in real time, while automated workflows and alerts keep teams responsive to every change in GTM data. The result is a GTM motion that runs on its own - where top-performing teams launch more than 50 plays per quarter, expansion campaigns that once took three weeks go live in 30 minutes, and every seller always knows exactly where to focus next.

**Average Rating:** 4.5/5.0

**Total Reviews:** 3,395

#### How Do G2 Users Rate GTM Studio - Powered by ZoomInfo?

- **Quality of Support:** 8.9/10 (Category avg: 8.9/10)
- **Automation:** 8.9/10 (Category avg: 8.7/10)
- **Identification:** 9.0/10 (Category avg: 8.9/10)
- **Preventative Cleaning:** 8.8/10 (Category avg: 8.5/10)

#### Who Is the Company Behind GTM Studio - Powered by ZoomInfo?

- **Seller:** [ZoomInfo](https://www.g2.com/sellers/zoominfo-26a9872a-d61e-4832-ab53-5e972b230706)
- **Company Website:** www.zoominfo.com
- **Year Founded:** 2000
- **HQ Location:** Vancouver, WA
- **Twitter:** @ZoomInfo  
23,515 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=bd618c71d6b4b0acc542c8b46079b4c9423a65a072ce8f8590d4f3ed35e8aebb&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fzoominfo%2F&secure%5Burl_type%5D=linkedin_company_website)  
4,221 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 63% Medium, 24% Large

#### What Do G2 Reviewers Say About GTM Studio - Powered by ZoomInfo?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **accurate B2B contact data** and intuitive filtering options, enhancing targeted prospecting and campaign efficiency.
- Users appreciate the **accuracy of data and intent signals** , enhancing their lead generation and targeting efforts effectively.
- Users find **GTM Studio easy to use** , enhancing lead enrichment with simple segmentation and sorting options.
- Users value the **reliable and accurate B2B contact data** from GTM Studio, enhancing campaign targeting and efficiency.
- Users value the **reliable and accurate B2B contact data** offered by GTM Studio, enhancing their targeting and campaign efficiency.

##### Cons

- Many users find the **pricing too high** for small teams, making it less accessible for their needs.
- Users experience **data inaccuracy** , with outdated information and missing data for niche roles affecting reliability.
- Users note that the **high pricing** may not be suitable for smaller teams with limited budgets.
- Users find the **learning curve steep** initially due to the platform's complexity and extensive features.
- Users find the **complex interface** of GTM Studio challenging initially, requiring training to navigate effectively.

#### What Are Recent G2 Reviews of GTM Studio - Powered by ZoomInfo?

**["Amazing Platform That Helps Marketers Bridge the Gap with your Audience"](https://www.g2.com/survey_responses/gtm-studio-powered-by-zoominfo-review-9742370)**

**Rating:** 5.0/5.0 stars

_— Verified User in Hospital & Health Care_

[Read full review](https://www.g2.com/survey_responses/gtm-studio-powered-by-zoominfo-review-9742370)

**["Account Exectuive"](https://www.g2.com/survey_responses/gtm-studio-powered-by-zoominfo-review-9414756)**

**Rating:** 5.0/5.0 stars

_— Alex P._

[Read full review](https://www.g2.com/survey_responses/gtm-studio-powered-by-zoominfo-review-9414756)

#### What Are G2 Users Discussing About GTM Studio - Powered by ZoomInfo?

- [What impact has Chorus by ZoomInfo had on the enhancement of sales conversations and customer insights?](https://www.g2.com/discussions/what-impact-has-chorus-by-zoominfo-had-on-the-enhancement-of-sales-conversations-and-customer-insights)
- [What is Chorus.ai used for?](https://www.g2.com/discussions/what-is-chorus-ai-used-for)
- [What is ZoomInfo MarketingOS used for?](https://www.g2.com/discussions/what-is-zoominfo-marketingos-used-for)
- [What are ZoomInfo scoops?](https://www.g2.com/discussions/what-are-zoominfo-scoops)
- [What information does ZoomInfo provide?](https://www.g2.com/discussions/what-information-does-zoominfo-provide)

### [Collibra](https://www.g2.com/products/collibra/reviews)

Try Collibra for free @ Collibra.com/tour Collibra is for organizations with complex data challenges, hybrid data ecosystems—and big ambitions for data and AI. We help organizations who are trying to accelerate data and AI use cases while ensuring compliance, but are struggling with fragmented governance and visibility across the whole hybrid data ecosystem. Collibra unifies governance for data and AI across every system, data source and user—to create safe autonomy and a foundation for scaling AI and data use cases. With Collibra, you can accelerate all your data and AI use cases, safely and with well–understood data. That’s Data Confidence.

**Average Rating:** 4.2/5.0

**Total Reviews:** 99

#### How Do G2 Users Rate Collibra?

- **Quality of Support:** 8.2/10 (Category avg: 8.9/10)
- **Automation:** 7.8/10 (Category avg: 8.7/10)
- **Identification:** 8.4/10 (Category avg: 8.9/10)
- **Preventative Cleaning:** 7.1/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Collibra?

- **Seller:** [Collibra](https://www.g2.com/sellers/collibra)
- **Company Website:** www.collibra.com
- **Year Founded:** 2008
- **HQ Location:** New York, New York
- **Twitter:** @collibra  
5,756 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=fcd053a42a3c664461e0d84dcd30ce00a076bf85f5efcb48a6ef76db774cc0d1&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F288365%2F&secure%5Burl_type%5D=linkedin_company_website)  
1,095 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Financial Services, Banking
- **Company Size:** 72% Large, 19% Medium

#### What Do G2 Reviewers Say About Collibra?

_AI-generated summary from verified user reviews_

##### Pros

- Users love the **unified data intelligence platform** of Collibra, enhancing collaboration and visibility for CDO teams.
- Users value the **comprehensive data management** capabilities of Collibra, enhancing compliance and fostering alignment across teams.
- Users value the **collaboration capabilities** of Collibra, enhancing alignment between Business and IT across the platform.
- Users find Collibra to be **intuitive and easily configurable** , enhancing their data management and governance experience.
- Users value the **seamless integrations** with diverse tools, enhancing data ecosystems and streamlining governance processes.

##### Cons

- Users face **complexity issues** with Collibra, leading to frustrations in onboarding and configuration as well as bottlenecks.
- Users struggle with **limited functionality** due to complex navigation and unintuitive language, hindering effective use of Collibra.
- Users find **Collibra complex** , with challenges in onboarding, unclear roles, excessive notifications, and technical issues hindering efficiency.
- Users face **integration issues** with Collibra, leading to bottlenecks and inconsistent connections with other tools.
- Users struggle with **user interface issues** in Collibra, facing navigation challenges and unclear language hindering usability.

#### What Are Recent G2 Reviews of Collibra?

**["Powerful Data Governance and Quality Platform"](https://www.g2.com/survey_responses/collibra-review-12128662)**

**Rating:** 5.0/5.0 stars

_— Katerina V._

[Read full review](https://www.g2.com/survey_responses/collibra-review-12128662)

**["Collibra Data Quality Module"](https://www.g2.com/survey_responses/collibra-review-7563210)**

**Rating:** 5.0/5.0 stars

_— Frank L._

[Read full review](https://www.g2.com/survey_responses/collibra-review-7563210)

#### What Are G2 Users Discussing About Collibra?

- [What is Collibra data governance tool?](https://www.g2.com/discussions/what-is-collibra-data-governance-tool)
- [Is Collibra a good tool?](https://www.g2.com/discussions/is-collibra-a-good-tool)
- [What can Collibra do?](https://www.g2.com/discussions/what-can-collibra-do)
- [What are the features of Collibra?](https://www.g2.com/discussions/what-are-the-features-of-collibra)

### [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:** 208

#### How Do G2 Users Rate dbt?

- **Quality of Support:** 8.8/10 (Category avg: 8.9/10)
- **Automation:** 9.3/10 (Category avg: 8.7/10)
- **Identification:** 8.7/10 (Category avg: 8.9/10)
- **Preventative Cleaning:** 8.2/10 (Category avg: 8.5/10)

#### 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  
14,792 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=2528ac46bc91e3acc7ad9e4f602bdecf43b7a29cef8c7a88fcb0b299043e4e1a&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fdbtlabs%2F&secure%5Burl_type%5D=linkedin_company_website)  
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:** 56% Medium, 27% Small

#### What Do G2 Reviewers Say About dbt?

_AI-generated summary from verified user reviews_

##### Pros

- Users love the **ease of use** of dbt, thanks to its clear structure, intuitive documentation, and seamless integration.
- Users value dbt for its **integration of software engineering best practices** , enhancing maintainability and collaboration in SQL transformations.
- Users value the **automation** features of dbt, significantly enhancing SQL code maintainability and transforming data workflows.
- Users value the **transformative power** of dbt, efficiently organizing and modeling data for actionable insights.
- Users value dbt for its **high data quality** , ensuring integrity and enhancing analytics workflows through modularization and documentation.

##### Cons

- Users face challenges with **limited functionality** in dbt due to rigid models and debugging difficulties, affecting project progress.
- Users often face **dependency issues** with dbt, leading to time-consuming troubleshooting and disruption in workflows.
- Users find the **steep learning curve** of mastering concepts like Jinja and Git to be quite challenging.
- Users struggle with **unhelpful error messages** in dbt, making troubleshooting difficult and frustrating.
- Users face **confusing error reporting** that complicates troubleshooting and hinders quick identification of issues.

#### What Are Recent G2 Reviews of dbt?

**["dbt Streamlines Data Pipelines with Powerful Incremental and SCD2 Features"](https://www.g2.com/survey_responses/dbt-review-12712114)**

**Rating:** 5.0/5.0 stars

_— Hithesh P._

[Read full review](https://www.g2.com/survey_responses/dbt-review-12712114)

**["Simple SQL-Driven Materializations with Powerful Lineage"](https://www.g2.com/survey_responses/dbt-review-12985641)**

**Rating:** 5.0/5.0 stars

_— Anish G._

[Read full review](https://www.g2.com/survey_responses/dbt-review-12985641)

#### What Are G2 Users Discussing About dbt?

- [What is DBT data Modelling?](https://www.g2.com/discussions/what-is-dbt-data-modelling) - 2 comments
- [What is DBT technology?](https://www.g2.com/discussions/what-is-dbt-technology) - 2 comments
- [What is DBT database tool?](https://www.g2.com/discussions/what-is-dbt-database-tool) - 1 comment
- [What is DBT tool used for?](https://www.g2.com/discussions/what-is-dbt-tool-used-for) - 2 comments

### [Acceldata](https://www.g2.com/products/acceldata/reviews)

Acceldata is an autonomous data and AI platform that helps enterprise data, engineering, and AI teams run analytics and deploy AI agents across hybrid, multi-cloud, on-premises, and sovereign data environments, without requiring data consolidation or migration. Most enterprise data platforms were built on the assumption that data would eventually centralize into a single warehouse or lakehouse. In practice, large enterprises operate four or more data platforms simultaneously, with data distributed across cloud providers, on-premises systems, and regulated environments that cannot move data across borders. Acceldata addresses this by bringing compute to wherever data already resides, rather than forcing data to move to the compute engine. The platform is built with an xLake architecture, which provides a unified layer for running, governing, and observing data workloads across any combination of infrastructure. It supports petabyte-scale analytics, agentic data workflows, and AI agent deployment under a single governance and cost management framework. Key capabilities include: 1. Data and AI Observability — End-to-end monitoring of data pipelines, data quality, AI agent behavior, and LLM outputs. Includes anomaly detection, data lineage, reconciliation, and alert management across environments. 2. Agentic Data Management (ADM) — Deploys autonomous agents to automate data quality monitoring, pipeline operations, catalog management, and incident response across distributed data estates. 3. Agentic Data Engineering (ADE) — Builds, orchestrates, and runs data pipelines using intelligent agents that automate pipeline creation, federated querying, and job management. 4. Data Warehousing — Executes queries in-place across lakehouses and warehouses using a Velox-accelerated engine, supporting open formats including Apache Iceberg, Delta Lake, Hudi, and Parquet with no vendor lock-in. 5. Data Platform Modernization — Provides phased migration paths for enterprises running Hadoop or Cloudera infrastructure, with in-place, sidecar, and forklift migration options built on an open-source foundation. Acceldata is designed for large enterprises in financial services, life sciences, telecommunications, manufacturing, retail, and insurance, particularly organizations operating regulated data environments where governance and data residency requirements prevent full cloud migration. The platform integrates with Snowflake, Databricks, AWS, Azure, GCP, and major open-source data frameworks.

**Average Rating:** 4.4/5.0

**Total Reviews:** 55

#### How Do G2 Users Rate Acceldata?

- **Quality of Support:** 8.9/10 (Category avg: 8.9/10)
- **Automation:** 8.8/10 (Category avg: 8.7/10)
- **Identification:** 9.0/10 (Category avg: 8.9/10)
- **Preventative Cleaning:** 7.3/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Acceldata?

- **Seller:** [Acceldata](https://www.g2.com/sellers/acceldata)
- **Company Website:** www.acceldata.io
- **Year Founded:** 2018
- **HQ Location:** Campbell, CA
- **Twitter:** @acceldataio  
340 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=ff52e799d3a014d58eaea8cb85b707bea7fd8b9545c3b55ba9d8a6edf3cca69b&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Facceldata&secure%5Burl_type%5D=linkedin_company_website)  
299 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Computer Software, Information Technology and Services
- **Company Size:** 61% Large, 23% Medium

#### What Do G2 Reviewers Say About Acceldata?

_AI-generated summary from verified user reviews_

##### Pros

- Users commend Acceldata's **ease of use** , highlighting its simple interface and efficient data handling capabilities.
- Users praise the **fast and responsive customer support** of Acceldata, greatly enhancing their experience and efficiency.
- Users commend Acceldata for its **efficient monitoring** capabilities, enhancing data visibility and supporting quick decision-making.
- Users appreciate the **quick onboarding and effective support** of Acceldata, enhancing data management and strategy development.
- Users appreciate the **comprehensive monitoring tools** of Acceldata, enabling proactive data management and enhanced reliability.

##### Cons

- Users find the UX of Acceldata **lacking intuitiveness** and face issues with GUI elements and response time.
- Users find the **initial setup complex** , with a steep learning curve and documentation that needs improvement.
- Users find the **difficult setup** of Acceldata challenging, noting a steep learning curve and inadequate documentation.
- Users find the **learning curve steep** , making initial setup and documentation improvement necessary for better user experience.
- Users find the **learning difficulty** of Acceldata challenging, especially during the initial setup and system creation.

#### What Are Recent G2 Reviews of Acceldata?

**["Versatile Data Observability with Brilliant Alerting and Monitoring"](https://www.g2.com/survey_responses/acceldata-review-12949346)**

**Rating:** 4.5/5.0 stars

_— Luciana S._

[Read full review](https://www.g2.com/survey_responses/acceldata-review-12949346)

**["Enterprise Data Reliability and Observability Platform with Strong Customization"](https://www.g2.com/survey_responses/acceldata-review-12122073)**

**Rating:** 5.0/5.0 stars

_— Jayakumar S._

[Read full review](https://www.g2.com/survey_responses/acceldata-review-12122073)

### [Oracle Data Quality](https://www.g2.com/products/oracle-data-quality/reviews)

Oracle Enterprise Data Quality delivers a complete, best-of-breed approach to party and product data resulting in trustworthy master data that integrates with applications to improve business insight.

**Average Rating:** 4.0/5.0

**Total Reviews:** 54

#### How Do G2 Users Rate Oracle Data Quality?

- **Quality of Support:** 8.4/10 (Category avg: 8.9/10)
- **Automation:** 8.2/10 (Category avg: 8.7/10)
- **Identification:** 9.2/10 (Category avg: 8.9/10)
- **Preventative Cleaning:** 8.6/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Oracle Data Quality?

- **Seller:** [Oracle](https://www.g2.com/sellers/oracle)
- **Year Founded:** 1977
- **HQ Location:** Austin, TX
- **Twitter:** @Oracle  
827,997 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=a14fcbcd818b49d781453c19628a9479a70cc1e8e335e54c876392ab5f543da3&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1028%2F&secure%5Burl_type%5D=linkedin_company_website)  
208,078 employees on LinkedIn®
- **Ownership:** NYSE:ORCL

#### Who Uses This Product?

- **Top Industries:** Hospital & Health Care, Information Technology and Services
- **Company Size:** 50% Large, 28% Small

#### What Are Recent G2 Reviews of Oracle Data Quality?

**["Excellent"](https://www.g2.com/survey_responses/oracle-data-quality-review-8936494)**

**Rating:** 5.0/5.0 stars

_— Ms. Tejaswini P._

[Read full review](https://www.g2.com/survey_responses/oracle-data-quality-review-8936494)

**["Streamlining Data Integrity with Oracle Data Quality"](https://www.g2.com/survey_responses/oracle-data-quality-review-8928291)**

**Rating:** 4.5/5.0 stars

_— Mohd. I._

[Read full review](https://www.g2.com/survey_responses/oracle-data-quality-review-8928291)

#### What Are G2 Users Discussing About Oracle Data Quality?

- [What is Oracle Data Quality used for?](https://www.g2.com/discussions/what-is-oracle-data-quality-used-for)

### [Informatica Cloud Data Quality](https://www.g2.com/fr/products/informatica-cloud-data-quality/reviews)

Informatica Cloud Data Quality permet à votre entreprise d'adopter une approche holistique de la gestion de la qualité des données pour identifier, corriger et surveiller rapidement les problèmes de qualité des données dans vos applications métier. La solution transforme vos processus de qualité des données en un effort collaboratif entre les utilisateurs métier et l'informatique. Cela crée un environnement qui exploite les données pour garantir le succès des initiatives de gestion des données de référence, d'IA, de ML et de modernisation du cloud.

**Average Rating:** 4.1/5.0

**Total Reviews:** 19

#### How Do G2 Users Rate Informatica Cloud Data Quality?

- **Qualité du support:** 9.2/10 (Category avg: 8.9/10)
- **Automatisation:** 8.3/10 (Category avg: 8.7/10)
- **pièce d'identité:** 8.3/10 (Category avg: 8.9/10)
- **Nettoyage préventif:** 6.7/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Informatica Cloud Data Quality?

- **Vendeur:** [Informatica](https://www.g2.com/fr/sellers/informatica)
- **Site Web de l'entreprise:** www.informatica.com
- **Année de fondation:** 1993
- **Emplacement du siège social:** Redwood City, CA
- **Twitter:** @Informatica  
99,643 abonnés Twitter
- **Page LinkedIn®:** [www.linkedin.com](https://www.g2.com/fr/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=06f93f9659c25422bea5c34037117512928a659c5d640bb989ed85a85cdb1252&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F3858%2F&secure%5Burl_type%5D=linkedin_company_website)  
2,802 employés sur LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Technologie de l'information et services
- **Company Size:** 180% Large, 80% Medium

#### What Are Recent G2 Reviews of Informatica Cloud Data Quality?

**["Consultant principal en qualité des données - expérience de mise en œuvre d'IDQ dans divers secteurs et plateformes."](https://www.g2.com/fr/survey_responses/informatica-cloud-data-quality-review-2266012)**

**Rating:** 5.0/5.0 stars

_— Utilisateur vérifié à Logiciels informatiques_

[Read full review](https://www.g2.com/fr/survey_responses/informatica-cloud-data-quality-review-2266012)

**["Outil très nécessaire pour maintenir la qualité des données"](https://www.g2.com/fr/survey_responses/informatica-cloud-data-quality-review-4202570)**

**Rating:** 4.0/5.0 stars

_— Sandeep K._

[Read full review](https://www.g2.com/fr/survey_responses/informatica-cloud-data-quality-review-4202570)

### [Demandbase One](https://www.g2.com/products/demandbase-one/reviews)

Demandbase is the leading, enterprise-grade account-based GTM platform for sales and marketing teams designed to make every moment and every dollar count. Since creating the category in 2013, we have been pioneering technologies to sharpen revenue teams’ ability to confidently deliver the right message to the right customers at the right time. Powered by industry-leading data, our transparent and tunable AI-enhanced model, and integrations that meet your tech stack where it is, Demandbase helps you to take meaningful action confidently and efficiently. We know that there’s no such thing as ‘one-size- fits-all’ account-based marketing and sales. That’s why we built our platform to be flexible, easily handling dynamic GTM motions, nuanced business rules, and diverse integrations that others struggle with. Demandbase One™ is your account-based GTM command center, powering your entire revenue stack. Our AI-driven engine unifies first and third-party data, streamlines cross-channel execution, and connects the tools in your stack with the same data, insights, and workflows to accelerate your revenue.

**Average Rating:** 4.4/5.0

**Total Reviews:** 1,941

#### How Do G2 Users Rate Demandbase One?

- **Quality of Support:** 8.8/10 (Category avg: 8.9/10)
- **Automation:** 9.0/10 (Category avg: 8.7/10)
- **Identification:** 8.7/10 (Category avg: 8.9/10)
- **Preventative Cleaning:** 8.3/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Demandbase One?

- **Seller:** [Demandbase](https://www.g2.com/sellers/demandbase)
- **Company Website:** www.demandbase.com
- **Year Founded:** 2005
- **HQ Location:** San Francisco, CA
- **Twitter:** @Demandbase  
21,346 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=fbd6df6ae02e0de4dfedb3f639579bc9dbe447eab6e09932935521ae69a2dba8&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F89759%2F&secure%5Burl_type%5D=linkedin_company_website)  
987 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Account Executive, Business Development Representative
- **Top Industries:** Computer Software, Information Technology and Services
- **Company Size:** 48% Medium, 32% Large

#### What Do G2 Reviewers Say About Demandbase One?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **ease of use** of Demandbase One, enhancing efficiency in building targeted custom audiences effortlessly.
- Users value the **comprehensive datasets** of Demandbase One, enhancing targeted marketing and audience engagement strategies.
- Users value the **comprehensive toolset** of Demandbase One, enhancing account targeting and analytics for effective ABM strategy.
- Users value the **unified data and seamless integrations** of Demandbase One, enhancing their marketing and sales efforts significantly.
- Users value the **insightful intent data** from Demandbase One for fast and effective account targeting and decision making.

##### Cons

- Users face a **steep learning curve** with Demandbase One, making it challenging to utilize all features effectively.
- Users find the **steep learning curve** of Demandbase One frustrating, requiring more training to maximize its features.
- Users find the **steep learning curve** of Demandbase One challenging, particularly for new or smaller teams lacking expertise.
- Users find the **learning difficulty** of Demandbase One challenging, particularly for those lacking technical skills.
- Users find the **navigation unintuitive** , making it challenging to navigate and manage campaigns effectively.

#### What Are Recent G2 Reviews of Demandbase One?

**["Powerful Intent Data and Account Insights for B2B Account Prioritization"](https://www.g2.com/survey_responses/demandbase-one-review-12823589)**

**Rating:** 4.5/5.0 stars

_— Himanshu J._

[Read full review](https://www.g2.com/survey_responses/demandbase-one-review-12823589)

**["Demandbase One: Powerful Targeting, Intent Insights, and Account-Level Visibility"](https://www.g2.com/survey_responses/demandbase-one-review-12742698)**

**Rating:** 4.0/5.0 stars

_— Nijat I._

[Read full review](https://www.g2.com/survey_responses/demandbase-one-review-12742698)

#### What Are G2 Users Discussing About Demandbase One?

- [As a beginner, how do I effectively use Demandbase One's account-based marketing feature for targeted campaigns?](https://www.g2.com/discussions/as-a-beginner-how-do-i-effectively-use-demandbase-one-s-account-based-marketing-feature-for-targeted-campaigns) - 1 upvote
- [What is Demandbase ABM/ABX Cloud used for?](https://www.g2.com/discussions/what-is-demandbase-abm-abx-cloud-used-for)
- [What does Insideview Data Integrity do?](https://www.g2.com/discussions/what-does-insideview-data-integrity-do)
- [What is the use of Insideview Data Integrity?](https://www.g2.com/discussions/what-is-the-use-of-insideview-data-integrity)
- [What does inside view do?](https://www.g2.com/discussions/what-does-inside-view-do)

### [Microsoft Data Quality Services](https://www.g2.com/products/microsoft-data-quality-services/reviews)

SQL Server Data Quality Services (DQS) is a knowledge-driven data quality product.

**Average Rating:** 3.9/5.0

**Total Reviews:** 47

#### How Do G2 Users Rate Microsoft Data Quality Services?

- **Quality of Support:** 8.0/10 (Category avg: 8.9/10)

#### Who Is the Company Behind Microsoft Data Quality Services?

- **Seller:** [Microsoft](https://www.g2.com/sellers/microsoft)
- **Year Founded:** 1975
- **HQ Location:** Redmond, Washington
- **Twitter:** @microsoft  
13,091,739 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=9458f51bd6ded48ad432a804f19ad736469f007787569b63827154231c315630&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fmicrosoft%2F&secure%5Burl_type%5D=linkedin_company_website)  
231,632 employees on LinkedIn®
- **Ownership:** MSFT

#### Who Uses This Product?

- **Company Size:** 53% Small, 29% Medium

#### What Are Recent G2 Reviews of Microsoft Data Quality Services?

**["Data Quality Services: it is petit great tool with so much potential!"](https://www.g2.com/survey_responses/microsoft-data-quality-services-review-5312253)**

**Rating:** 4.0/5.0 stars

_— Ricardo S._

[Read full review](https://www.g2.com/survey_responses/microsoft-data-quality-services-review-5312253)

**["Very reliable useful tool"](https://www.g2.com/survey_responses/microsoft-data-quality-services-review-1813034)**

**Rating:** 5.0/5.0 stars

_— Debbie T._

[Read full review](https://www.g2.com/survey_responses/microsoft-data-quality-services-review-1813034)

#### What Are G2 Users Discussing About Microsoft Data Quality Services?

- [What is Microsoft Data Quality Services used for?](https://www.g2.com/discussions/what-is-microsoft-data-quality-services-used-for)

### [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?

- **Quality of Support:** 8.6/10 (Category avg: 8.9/10)
- **Automation:** 9.2/10 (Category avg: 8.7/10)
- **Identification:** 8.8/10 (Category avg: 8.9/10)
- **Preventative Cleaning:** 8.5/10 (Category avg: 8.5/10)

#### 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  
26,149 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=ae8a7629c5a6d593caff29361a6ee3fb670df11992dd94a9656c66461078b340&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F903031%2F&secure%5Burl_type%5D=linkedin_company_website)  
2,304 employees on LinkedIn®
- **Ownership:** Private

#### Who Uses This Product?

- **Top Industries:** Information Technology and Services, Hospital & Health Care
- **Company Size:** 35% Large, 35% Small

#### What Are Recent G2 Reviews of Alteryx Designer Cloud?

**["Great way to trick people into learning relational algebra"](https://www.g2.com/survey_responses/alteryx-designer-cloud-review-9652085)**

**Rating:** 4.5/5.0 stars

_— Alexander D._

[Read full review](https://www.g2.com/survey_responses/alteryx-designer-cloud-review-9652085)

**["The Inovation is comming"](https://www.g2.com/survey_responses/alteryx-designer-cloud-review-9632148)**

**Rating:** 4.0/5.0 stars

_— Carlos Alexandre T._

[Read full review](https://www.g2.com/survey_responses/alteryx-designer-cloud-review-9632148)

#### What Are G2 Users Discussing About Alteryx Designer Cloud?

- [What are data wrangling tools?](https://www.g2.com/discussions/what-are-data-wrangling-tools)
- [Which of the following data sources does Trifacta Enterprise Support?](https://www.g2.com/discussions/which-of-the-following-data-sources-does-trifacta-enterprise-support)
- [Is Trifacta an ETL tool?](https://www.g2.com/discussions/is-trifacta-an-etl-tool) - 1 comment
- [What is Trifacta used for?](https://www.g2.com/discussions/what-is-trifacta-used-for)

### [Openprise](https://www.g2.com/products/openprise/reviews)

Openprise makes your GTM data smarter with AI and automation. As the only data and AI orchestration platform built for modern go-to-market teams, Openprise automates your processes, unifies your data silos, and consolidates point solutions so Ops leaders can build smarter GTM data — your data, your way, your timeline. Fortune 500 companies and high-growth enterprises alike rely on Openprise and its partner ecosystem to unlock cleaner data, more efficient operations, and AI-ready pipelines. See how Openprise makes your GTM data smarter at www.openprisetech.com and follow us on LinkedIn. For more information, please visit www.openprisetech.com.

**Average Rating:** 4.9/5.0

**Total Reviews:** 63

#### How Do G2 Users Rate Openprise?

- **Quality of Support:** 9.9/10 (Category avg: 8.9/10)
- **Automation:** 9.7/10 (Category avg: 8.7/10)
- **Identification:** 9.3/10 (Category avg: 8.9/10)
- **Preventative Cleaning:** 9.8/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Openprise?

- **Seller:** [Openprise](https://www.g2.com/sellers/openprise)
- **Year Founded:** 2014
- **HQ Location:** San Mateo, US
- **Twitter:** @openprisetech  
3,573 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=5a06d53d5b41c29b500284c2751e01fba08bff4013b283d4b99ce3715191b4b8&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F3526047%2F&secure%5Burl_type%5D=linkedin_company_website)  
125 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Computer Software, Information Technology and Services
- **Company Size:** 59% Large, 34% Medium

#### What Do G2 Reviewers Say About Openprise?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **booking efficiency** of Openprise due to its advanced database and flexible lead routing options.
- Users value Openprise for its **strong database and flexible lead routing options** , enhancing their data management capabilities.
- Users value the **robust database and flexible lead routing options** of Openprise, enhancing data management efficiency.
- Users value the **flexible options** in Openprise for complex lead routing and robust database management.
- Users value the **strong database and flexible lead routing options** of Openprise, enhancing their lead generation capabilities.

##### Cons

- Users find the **navigation and configuration difficult** , indicating a need for improvements in the Openprise UI.

#### What Are Recent G2 Reviews of Openprise?

**["Great Tool, Even Better Implementation and Support Teams!"](https://www.g2.com/survey_responses/openprise-review-5210577)**

**Rating:** 5.0/5.0 stars

_— Veronica K._

[Read full review](https://www.g2.com/survey_responses/openprise-review-5210577)

**["Robust and versatile tool for Lead routing process automation"](https://www.g2.com/survey_responses/openprise-review-10755221)**

**Rating:** 4.0/5.0 stars

_— Verified User in Computer Software_

[Read full review](https://www.g2.com/survey_responses/openprise-review-10755221)

#### What Are G2 Users Discussing About Openprise?

- [What is Openprise used for?](https://www.g2.com/discussions/what-is-openprise-used-for)

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Similar Categories

- [Infrastructure as a Service (IaaS)](/categories/infrastructure-as-a-service-iaas)
- [Active Metadata Management](/categories/active-metadata-management)
- [Address Verification](/categories/address-verification)
- [AIOps Platforms](/categories/aiops-platforms)
- [Application Server](/categories/application-server)

- [Blockchain](/categories/blockchain)
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- [Data Exchange Platforms](/categories/data-exchange-platforms)
- [Data Fabric](/categories/data-fabric)
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[Browse Data Quality Themes](/categories/data-quality/themes)

 ![Shalaka Joshi](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Shalaka Joshi")
SJ

Researched and written by [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)

Updated 

Products classified in the overall Data Quality category are similar in many regards and help companies of all sizes solve their business problems. However, enterprise business features, pricing, setup, and installation differ from businesses of other sizes, which is why we match buyers to the right Enterprise Business Data Quality 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 Enterprise Business Data Quality category.

In addition to qualifying for inclusion in the Data Quality Tools category, to qualify for inclusion in the Enterprise Business Data Quality Tools category, a product must have at least 10 reviews left by a reviewer from an enterprise business.

Top Tools at a Glance

| 

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Automated data cleansing with governed AI/ML pipelines

 | 

User Review

"Effective Data Analysis with SAS Viya"

 |
| 

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Proactive pipeline anomaly detection with ML-powered observability

 | 

User Review

"MonteCarlo: A Powerful Tool for Data Observability and Inspection"

 |
| 

 | 

SQL transformation quality with automated testing

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User Review

"Simple SQL-Driven Materializations with Powerful Lineage"

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| 

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HubSpot-native CRM deduplication and data quality

 | 

User Review

"A Powerful Platform for Centralizing and Managing Customer Data"

 |
| 

 | 

AI-driven data quality and pipeline observability

 | 

User Review

"Automates Data Governance"

 |
| 

 | 

CRM record enrichment with firmographic data governance

 | 

User Review

"Seamless CRM Integration with Robust Data Enrichment"

 |
| 

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Cross-system data lineage and governance trust

 | 

User Review

"Centralized Data Catalog with Powerful Governance and Lineage Visibility"

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| 

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Customer health data centralization and hygiene

 | 

User Review

"A Strategic Platform for Scaling Customer Success"

 |

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Show More

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## How Do You Choose the Right Data Quality Tools?

### What You Should Know About Data Quality Tools

### What are Data Quality Tools?

Data quality software is a set of various tools and services created to derive meaningful data for organizations. The tools condition the data to meet the specific needs of the users. Data quality is an integral part of data governance and data management processes through which all the data of the organization is governed. Data quality tools make it possible to achieve accuracy, relevancy, and consistency of data to make better decisions.

High-quality data can deliver desired outputs, whereas poor-quality data can result in disastrous insights. Organizations that are data-driven and frequently use data analytics for decision-making make data quality a prime factor in deciding its usefulness.

### What are the Common Features of Data Quality Tools?

Features of data quality tools mainly consider the dimensions or the metrics that define quality. These solutions can support some or all of the functions as mentioned below to deliver useful end results:

**Data cleansing:** It is the process of removing redundant, incorrect, and corrupt data. It is sometimes referred to as data cleaning or data scrubbing. Being one of the critical stages in data processing, most data quality tools have this feature. A few of the common data inaccuracies include incorrect entries and missing values.

**Data standardization:** It is a major step in organizing data. It involves converting data into a common format which makes it easier for users to access and analyze the data. This stage fulfills one of the parameters of data quality—consistency. Bringing the data into a single common format makes sure that data is consistent. Data standardization plays a key role in achieving accuracy which is another factor in data quality. It helps by giving users access to the latest cleansed and updated data.

**Data profiling:** Data profiling is the process of analyzing data, understanding the structure of data, and identifying the potential projects for the specified data. Data is minutely analyzed using analytical tools to detect characteristics like mean, minimum, maximum, and frequency.

**Data deduplication:** It is a process to eliminate excessive copies of data and reduce storage requirements. It is also called intelligent compression or single-instance storage or data dedupe.

**Data validation:** This feature ensures that data quality and accuracy are in place. In automated systems, there is minimal or almost no human supervision when the data is entered. This makes it essential to check that the data entered is correct. Common types of data validation include data check, code check, range check, format check, and consistency check. There also are certain data quality rules defined for data management platforms.

**Extract, transform, and load (ETL):** When organizations advance in the technology strategy, data from existing systems are transferred to the new systems. ETL forms a vital task of the data migration process. The end goal is to maintain data quality for the data that is being migrated. ETL stands third in the phases of the data quality lifecycle. Other phases are quality assessment, quality design, and monitoring. It involves extracting data from the data sources, transforming it by deduplicating it, and loading it into the target database.

**Master data management (MDM):** This feature manages quality data by organizing, centralizing, and enriching data. It includes non-transactional data like customer data and product data. MDM is important for enterprise data management.

**Data enrichment:** This feature is the process of enhancing the value and accuracy of data by integrating internal and external data with the existing information.

**Data catalog:** Data catalog hosts data and metadata to help users with their data discovery. Data quality monitoring tools have this feature to increase transparency in workflows.

**Data warehousing:** Data warehousing focuses on unifying data from various data sources. It ensures enterprise data quality by improving the accuracy of data.

**Data parsing:** Data usually is conformed to specific formats. For example address, telephone number, and email address all have data patterns. Parsing helps with such address verifications and also if the telephone numbers are conforming to the patterns. 

Other features of data quality software: [ERP Capabilities](https://www.g2.com/categories/data-quality/f/erp) and [File Capabilities](https://www.g2.com/categories/data-quality/f/file).

### What are the Benefits of Data Quality Tools?

Data is one of the most valuable resources for organizations today. Having high-quality data has the following advantages:

**Effective data implementation:** Good quality data improves the performance of teams and results in better business. It keeps all the departments of the organization on the same page and helps them work efficiently.

[**Improved customer relationships**](https://www.g2.com/categories/data-quality/f/crm) **:** Data quality plays a major role in retaining customers. It helps organizations track customer preferences and interests.

**Insightful decision-making:** The decision-makers always need up-to-date information to make better decisions. Data quality tools ensure business intelligence is attained through high-quality data. Good data quality helps in reducing the risk of bad decisions based on poor-quality data and increasing the efficiency of the decision-making process.

**Effective customer targeting:** With high-quality data at their fingertips, organizations can track the characteristics of their existing customers and create personas depending on what their customers prefer. This can further lead to forecasting the needs of the target market.

**Efficient product development:** Engineering teams in software development companies can audit their KPIs like engagement with the new product online. Auditing data points like button clicks can help engineers understand how ready their product is to be launched in the market or if there are any changes needed. 

**Data matching:** Effective data quality monitoring tools help in data matching. Data matching is the process of comparing two different data sets and matching them against each other. This process helps in identifying duplicate data within a [database](https://www.g2.com/categories/data-quality/f/database).

### Who Uses Data Quality Tools?

Data being the new fuel is driving organizations to figure out how it can be used to make business decisions. Below is a list of departments that utilize data quality management software :

**Data quality analysts:** They monitor the quality of data using data quality tools that help companies make informed decisions. They work with database developers to modify database designs as per the need. This persona primarily helps with data analysis, further improving the quality.

**Marketing teams:** Marketing managers must have high-quality data at use because good quality data helps drive efficient marketing campaigns in the future. Data quality tools help the teams filter unnecessary information and focus on the target market to gain a better understanding.

**IT teams:** Several times there are duplicate records which makes it difficult for IT teams to have data quality control in place. With the use of software, it is easier to govern the data and optimize data quality management.

### Challenges with Data Quality Tools 

Data quality changes with what is fed into the system. Sometimes there are a few of the below-mentioned difficulties faced while using data quality tools:

**Duplicated data:** Data deduplication tools are a must before passing over the data to the next steps. Since large amounts of data are generated through various disparate sources, it is often flawed, or some entries are duplicated. However, deduplication tools can identify the same data points and assign them for deduplication. 

**Lack of complete information:** Manual entries can cause incomplete information or not having information for every dataset. This could cause data quality tools to underperform.

**Heterogenous formats:** Inconsistent data formats are always a common pain point for data analysts. While working with data outsourcing services providers, it is recommended to specify preferred formats.

### How to Buy Data Quality Tools?

#### Requirements Gathering (RFI/RFP) for Data Quality Software

Depending upon the industry, there are a variety of data quality dimensions that must be kept in mind before the purchase of the software. Data management strategy is expected to address data governance requirements. Along with it, there are other requirements like data retention and archiving. An RFI or RFP from vendors helps to optimize the evaluation process. 

#### Compare Data Quality Products

**Create a long list**

To begin with, organizations should make a list of data quality software vendors providing features like data profiling, data preparation, deduplication, and other relevant features depending on the results they are looking to achieve.

**Create a short list**

On the basis of the fulfillment of primary requirements, the next step covers shortlisting the vendors by asking a few questions like:

- Do they provide automation in their software?
- How do the products/tools maintain performance and scale?
- What are their support timings and escalation procedures?

**Conduct demos**

Demos are an efficient way of verifying which vendor fits the bill. It gives the organization an in-depth understanding of the software. Organizations can also get answers to how well-stacked the vendor is. Usually, demos for data quality software would include the presentation of various tools and capabilities of the software such as data standardization feature, metadata management, and data quality management to name a few.

#### Selection of Data Quality Tools

**Choose a selection team**

The team involved in making this decision must include relevant decision makers. A chief marketing officer, who often needs clean data to nurture leads from their team, can test the tools during the demo. The next member to be kept in the loop is the sales lead. Data quality is equally important for the sales workforce as they want to focus more on revenue generation than just updating the data in the CRM. Data analysts are also involved since they are the ones who use these tools for data quality assessments. Along with it, data quality analysts are included in the team because they use the software to examine the data for quality requirements depending on different departments and share this processed data with them.

**Negotiation**

Because data quality is of utmost importance, it is advisable to choose the right tools for assessment. Tools that work in real time and that can be used easily by business users are something organizations want to have. It is advisable to look at the pricing of the software, if there are any additional costs, and also if the vendor offers any discount. Many data quality tools are available in both cloud and on-premises structures. It is better to have tools in the cloud as manual data quality monitoring for enterprise data could be difficult for one person or even a team.

**Final decision**

The decision to buy data quality software has to be taken by the teams involved throughout the buying process. Sales, marketing, and data analyst teams can benefit from buying the right data quality software.

### Data Quality Trends

**Data warehouse modernization**

Data warehouse modernization helps the current data warehouse environment work in synchronization with rapidly changing requirements. Organizations are coping with managing the expansion of data and data systems by modernizing the data warehouse. This emerging trend focuses on data automation to achieve the desired quality of data and business practices alike.

**Modern data hubs**

Data hubs are data storage architectures with a seamless flow of data that follow the hub and spoke model. Modern data hubs have features like data storage, harmonization, governance, metadata, and indexing. These features indicate that data hubs are more efficient than data consolidation.

**Data democratization**

Recently, organizations are making data available to independent business functions. This is to improvise transparency and consistency amongst all the departments in the organization. Advancements in visualizations have made data visibility easier at a technical level and as the trend progresses, it is expected to have the same effect on non-technical users, i.e., ease of access to data.

**Machine learning (ML) algorithms in data quality** 

Machine learning (ML) algorithms have become important for a company's data management strategy. Enterprise data is usually big data which makes it essential to have automation. Machine learning algorithms can make it possible to automate the process giving end results. ML algorithms help in improving data quality scores by identifying wrong data, incomplete data, duplicate data, and also help in performing functions like clustering, detecting anomalies, and association rule mining.