# Best Data Quality Tools for Small Business - Page 2 ## 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=1327283&focus%5B%5D=135441&focus%5B%5D=19607&focus%5B%5D=148877&focus%5B%5D=40583&focus%5B%5D=1360&focus%5B%5D=24829&focus%5B%5D=40754) Highlighted products: SAS Viya, GTM Studio - Powered by ZoomInfo, HubSpot Data Hub, dbt, Insycle, Melissa Data Quality Suite, Planhat, and Traction Complete. Underlying data: [Grid® JSON](https://www.g2.com/categories/data-quality/grids.json?focus%5B%5D=sas-sas-viya&focus%5B%5D=gtm-studio-powered-by-zoominfo&focus%5B%5D=hubspot-data-hub&focus%5B%5D=dbt&focus%5B%5D=insycle&focus%5B%5D=melissa-data-quality-suite&focus%5B%5D=planhat&focus%5B%5D=traction-complete&segment=small-business) **Sponsored** ### Omatic Software Omatic Cloud is the nonprofit integration and data platform, built for everyday nonprofit users by nonprofit professionals who understand your workflows. Nonprofits juggle more systems than ever, creating data inconsistencies across systems. By supporting workflows across fundraising, program management, and financial reporting, Omatic Cloud helps you unlock the power of data to inform decisions, engage supporters, and scale your mission. Omatic Cloud provides: - App connectors for nonprofit tools - Bulk data imports (flat files) into CRM & accounting tools - Data transformation - Data mapping & routing - Data validation & deduplication - And much more! Omatic is backed by a world-class support team, providing hands-on implementation & training to help you get integrations live. Founded in 2002 and headquartered in Charleston, SC, we serve more than 3k social impact customers across Healthcare, Cause & Cure, Higher Ed, K-12, Family & Human Services, Arts & Cultural, and Faith-Based Orgs. [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=2026-08-03T07%3A25%3A56Z&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=42995&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%2Fsmall-business%3Fpage%3D2%26segment%3Dsmall-business&secure%5Btoken%5D=ebd9b10b80d868ec4c175aa62d720b36aac20ace44281bc40ad1ac93858d7d1f&secure%5Burl%5D=https%3A%2F%2Fomaticsoftware.com%2F%3Futm_source%3Dreview-site%26utm_medium%3Dg2%26utm_campaign%3Dpaid&secure%5Burl_type%5D=custom_url) ### [WinPure Clean & Match](https://www.g2.com/products/winpure-clean-match/reviews) Clean & Match Enterprise is the top-rated desktop platform for data quality management – powered with AI data matching for easy & efficient data cleaning, deduplication, & transformation.This software suite is ideal for cleaning, correcting and deduplicating mailing lists, databases, spreadsheets and CRMs. Experience the world’s most advanced AI data-matching solution that enables organizations to resolve complex records within minutes. \* Detect potential duplicates based on common-sense principles \* Determine possible relationships between datasets \* Intelligently identify duplicates based on learned principles \* Perform data matching at scale in just three step No code data cleansing & standardization. Teams spend 80% of their time in manual data cleaning and standardization. WinPure’s no-code software reduces the time spent with its intuitive interface. Users can: \* Clean columns with built-in pre-set standardization options \* Split components for targeted cleaning \* Create custom abbreviation & name dictionaries\* \* Parse address data to clean & standardize at a component level Catch non-exact matches with advanced fuzzy logic. Duplicate customer records with varying information need a powerful fuzzy match algorithm like WinPure to identify exact and possible matches. Users can: \* Cross-match between and across files \* Easily merge and purge or overwrite duplicates \* Create master records of consolidated records \* Export directly into your CRM or data source WinPure™ Clean & Match will help save your business time and money. \* Increase the accuracy of virtually ANY list, spreadsheet, database, CRM, etc. \* Locally installed Windows software so no need to worry about security as all processing is done on your own systems \* Save hours of valuable time cleaning and removing duplicated records from your lists or databases using built-in sophisticated fuzzy and phonetic match algorithms. \* Affordable licences available with World Class Support & Training. \* Free Demo with Live Online Training available. Seeing is believing! Schedule a live demo today with one of our product specialist at your convenience. We can learn about your requirements, answer questions, and review ways WinPure can help you and your organization. **Average Rating:** 4.7/5.0 **Total Reviews:** 73 #### How Do G2 Users Rate WinPure Clean & Match? - **Quality of Support:** 9.4/10 (Category avg: 8.9/10) - **Automation:** 9.4/10 (Category avg: 8.7/10) - **Identification:** 9.4/10 (Category avg: 8.9/10) - **Preventative Cleaning:** 9.8/10 (Category avg: 8.5/10) #### Who Is the Company Behind WinPure Clean & Match? - **Seller:** [WinPure](https://www.g2.com/sellers/winpure) - **Year Founded:** 2004 - **HQ Location:** Theale, Berkshire - **Twitter:** @WinPure 2,209 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=eedcb4852f0737998a61f5f9bf00b8b7399223fd1d1b74db7d9668f47e5ee6a7&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F2149782%2F&secure%5Burl_type%5D=linkedin_company_website) 9 employees on LinkedIn® #### Who Uses This Product? - **Top Industries:** Marketing and Advertising, Health, Wellness and Fitness - **Company Size:** 43% Small, 35% Medium #### What Do G2 Reviewers Say About WinPure Clean & Match? _AI-generated summary from verified user reviews_ ##### Pros - Users praise WinPure's **outstanding customer support** , noting the team's responsiveness and helpful guidance throughout the process. - Users highlight the **exceptional data quality** of WinPure Clean & Match, ensuring accurate and efficient data management. - Users value the **effective duplicate management** of WinPure, enhancing data accuracy and streamlining their processes effortlessly. - Users find WinPure **incredibly easy to use** , allowing them to quickly start matching projects without extensive training. - Users value the **easy access** WinPure provides with its intuitive interface, allowing quick start without extensive training. #### What Are Recent G2 Reviews of WinPure Clean & Match? **["The Best Decision We Made for Our Data Migration"](https://www.g2.com/survey_responses/winpure-clean-match-review-11752678)** **Rating:** 5.0/5.0 stars _— Verified User in Health, Wellness and Fitness_ [Read full review](https://www.g2.com/survey_responses/winpure-clean-match-review-11752678) **["Super tool to match millions of products"](https://www.g2.com/survey_responses/winpure-clean-match-review-9183862)** **Rating:** 4.5/5.0 stars _— Verified User in Wholesale_ [Read full review](https://www.g2.com/survey_responses/winpure-clean-match-review-9183862) #### What Are G2 Users Discussing About WinPure Clean & Match? - [What is WinPure Clean & Match used for?](https://www.g2.com/discussions/what-is-winpure-clean-match-used-for) ### [Flatfile](https://www.g2.com/products/flatfile/reviews) Migrating data is one of the biggest barriers to onboarding customers quickly and successfully. This process is often complex and error-prone, causing delays and frustration that can negatively impact the customer experience. Don’t let customer data become a bottleneck for your business. Accelerate your data onboard and migrations with AI-powered data transformations. Our source-to-target mapping auto-magically converts complex data into your desired format. Easily collaborate with stakeholders on data decisions with granular access control, ensuring the right people manage the right data at the right time. With our fully customizable developer-first platform and event-driven architecture you can create complex workflows tailored specifically to your business needs. No more costly, service-heavy migrations. Migrate data efficiently and with confidence. Come see how we help the world’s best data migration and implementation teams migrate customer data seamlessly. **Average Rating:** 4.6/5.0 **Total Reviews:** 31 #### How Do G2 Users Rate Flatfile? - **Quality of Support:** 9.4/10 (Category avg: 8.9/10) - **Automation:** 9.4/10 (Category avg: 8.7/10) - **Identification:** 9.2/10 (Category avg: 8.9/10) - **Preventative Cleaning:** 8.8/10 (Category avg: 8.5/10) #### Who Is the Company Behind Flatfile? - **Seller:** [Flatfile](https://www.g2.com/sellers/flatfile) - **Year Founded:** 2018 - **HQ Location:** Denver, Colorado - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=b1e40c441577d2680d7d33f58af50bb3a7032d5a5d9ed5504ab689abe3e260ce&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fflatfile%2F&secure%5Burl_type%5D=linkedin_company_website) 31 employees on LinkedIn® #### Who Uses This Product? - **Top Industries:** Computer Software - **Company Size:** 90% Small, 6% Medium #### What Do G2 Reviewers Say About Flatfile? _AI-generated summary from verified user reviews_ ##### Pros - Users value the **time efficiency** of Flatfile, appreciating the saved effort in developing similar functionalities independently. - Users find **time-saving** benefits in Flatfile, avoiding the need to build functionalities from scratch. ##### Cons - Users experience **unreliable error handling** with Flatfile, often facing unexpected server errors and UI instability. - Users report frequent **error notifications** that undermine trust, with server responses often leading to frustrating, cryptic experiences. - Users find Flatfile's **limited customization** options a significant drawback, hindering their ability to tailor the product to their needs. - Users find Flatfile's **limited features** frustrating, particularly due to its instability and lack of customizability. - Users report **limited functionality** with Flatfile, experiencing server errors and inadequate customizability during basic operations. #### What Are Recent G2 Reviews of Flatfile? **["Stable and very customizable"](https://www.g2.com/survey_responses/flatfile-review-10226209)** **Rating:** 4.5/5.0 stars _— Misha C._ [Read full review](https://www.g2.com/survey_responses/flatfile-review-10226209) **["Easy to use tools with a responsive and helpful team"](https://www.g2.com/survey_responses/flatfile-review-7974560)** **Rating:** 5.0/5.0 stars _— Playmaker R._ [Read full review](https://www.g2.com/survey_responses/flatfile-review-7974560) #### What Are G2 Users Discussing About Flatfile? - [What is flat file?](https://www.g2.com/discussions/what-is-flat-file) - [What are the advantages of a flat file?](https://www.g2.com/discussions/what-are-the-advantages-of-a-flat-file) - [What is a flat file used for?](https://www.g2.com/discussions/what-is-a-flat-file-used-for) ### [BizProspex CRM Cleaning](https://www.g2.com/products/bizprospex-crm-cleaning/reviews) At BizProspex, we help businesses fix CRM databases that have become unreliable over time. Duplicate contacts, outdated emails, incorrect job titles, and inconsistent formatting build up naturally, and they end up slowing down sales teams and weakening campaign results. Our CRM Cleaning service identifies these issues across your entire database and corrects them. We remove duplicates, standardize fields, and verify contact details like emails, phone numbers, and job titles against trusted sources. We combine AI-based detection with manual review from our analysts, so every record is checked for accuracy before delivery. With over 2500 projects completed and 13+ years of experience, we focus on giving teams a CRM they can actually trust, one that supports better targeting, stronger pipeline accuracy, and more confident decision making. **Average Rating:** 4.9/5.0 **Total Reviews:** 14 #### How Do G2 Users Rate BizProspex CRM Cleaning? - **Quality of Support:** 9.8/10 (Category avg: 8.9/10) - **Automation:** 9.0/10 (Category avg: 8.7/10) - **Identification:** 9.3/10 (Category avg: 8.9/10) - **Preventative Cleaning:** 9.0/10 (Category avg: 8.5/10) #### Who Is the Company Behind BizProspex CRM Cleaning? - **Seller:** [Bizprospex](https://www.g2.com/sellers/bizprospex) - **Year Founded:** 2013 - **HQ Location:** Suwanee, Georgia, United States - **Twitter:** @BizProspex 560 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=2054e5d1fe60de2d6cef24b5cb1904929c2284a0832d8ec1cb9fcf2feaf9ae49&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fbiz-prospex%2F&secure%5Burl_type%5D=linkedin_company_website) 164 employees on LinkedIn® - **Phone:** +91 7697120653 #### Who Uses This Product? - **Company Size:** 87% Small, 13% Medium #### What Are Recent G2 Reviews of BizProspex CRM Cleaning? **["Best B2B intent data"](https://www.g2.com/survey_responses/bizprospex-crm-cleaning-review-7156293)** **Rating:** 5.0/5.0 stars _— Verified User in Architecture & Planning_ [Read full review](https://www.g2.com/survey_responses/bizprospex-crm-cleaning-review-7156293) **["Cool software made by smart professional guys who know their job"](https://www.g2.com/survey_responses/bizprospex-crm-cleaning-review-4408140)** **Rating:** 5.0/5.0 stars _— Nikhil B._ [Read full review](https://www.g2.com/survey_responses/bizprospex-crm-cleaning-review-4408140) #### What Are G2 Users Discussing About BizProspex CRM Cleaning? - [What is BizProspex CRM Cleaning used for?](https://www.g2.com/discussions/what-is-bizprospex-crm-cleaning-used-for) ### [Syncari](https://www.g2.com/products/syncari/reviews) Syncari is an AI-ready, Agentic MDM platform that unifies, governs, and activates trusted data across all your systems, domains, and cloud infrastructure. Built for enterprises navigating the complexity of multi-agent environments and AI-driven operations, Syncari automates core data management workflows—from data modeling and lineage to validation and remediation—without needing heavy IT resources. At the heart of Syncari is its patented multi-directional sync, delivering real-time, bi-directional data consistency across CRMs, ERPs, cloud platforms, and data warehouses—without custom code or middleware. Syncari ensures continuously clean, synchronized, and governed data flows throughout your enterprise and is always ready for analytics, AI models, and operational use. Whether you're powering AI copilots, managing complex entity relationships, or standardizing data pipelines, Syncari helps you move beyond just managing data—to activating it. Why Syncari? -Syncari Agentic MDM™: Designed for orchestrating trusted data across AI agents and teams -Patented Multi-Directional Sync: Real-time updates across all connected platforms -Agentic Ops: Schema sync, field mapping, DQ enforcement, and remediation -Entity Resolution: Consolidate and deduplicate records across domains -Composable + Cloud-First: Built to plug into your existing SaaS and data stack -Low-Code / No-Code: Accessible to IT, data teams, RevOps, and business users alike Core Capabilities Unify, Sync, Automate, Activate, Model, Catalog, Lineage, Transform, Standardize, Verify, Remediate, Observe, Report, Consume Top Use Cases - Customer Master: Build a unified customer profile across GTM systems - Product Master: Align and enrich product data across eCommerce and ERP - Hierarchy Master: Govern legal entities, accounts, and territories - Analytics MDM: Push AI-ready data into BI tools and ML workflows - Data Products: Operationalize governed datasets for internal and external use - Data Quality: Automatically identify, validate, standardize, and remediate data issues across systems - MDM for Snowflake: Sync and manage master data directly inside Snowflake - MDM for GCP: Connect, unify, and activate trusted data in BigQuery and GCP tools - MDM for Your Data Warehouse: Maintain clean, governed, query-ready data across your cloud warehouse infrastructure -MCP Server for your unified data **Average Rating:** 4.8/5.0 **Total Reviews:** 41 #### How Do G2 Users Rate Syncari? - **Quality of Support:** 9.9/10 (Category avg: 8.9/10) - **Automation:** 9.7/10 (Category avg: 8.7/10) - **Identification:** 9.4/10 (Category avg: 8.9/10) - **Preventative Cleaning:** 9.4/10 (Category avg: 8.5/10) #### Who Is the Company Behind Syncari? - **Seller:** [Syncari](https://www.g2.com/sellers/syncari) - **Year Founded:** 2019 - **HQ Location:** Newark, California - **Twitter:** @syncari 236 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=da029888f8c85f818208e239614050bb139973474b1aa30aa1cfe9035ae2ca2f&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsyncari%2F&secure%5Burl_type%5D=linkedin_company_website) 51 employees on LinkedIn® #### Who Uses This Product? - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 51% Medium, 44% Small #### What Are Recent G2 Reviews of Syncari? **["Nicely Packaged Versatility and POWER"](https://www.g2.com/survey_responses/syncari-review-9566623)** **Rating:** 5.0/5.0 stars _— John M._ [Read full review](https://www.g2.com/survey_responses/syncari-review-9566623) **["Good Experience using Syncari as an Integration Architect"](https://www.g2.com/survey_responses/syncari-review-9550011)** **Rating:** 5.0/5.0 stars _— MUSTAPHA I._ [Read full review](https://www.g2.com/survey_responses/syncari-review-9550011) #### What Are G2 Users Discussing About Syncari? - [What is Syncari used for?](https://www.g2.com/discussions/what-is-syncari-used-for) - 1 comment ### [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) ### [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? - **Quality of Support:** 7.9/10 (Category avg: 8.9/10) - **Automation:** 8.2/10 (Category avg: 8.7/10) - **Identification:** 8.8/10 (Category avg: 8.9/10) - **Preventative Cleaning:** 8.3/10 (Category avg: 8.5/10) #### 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:** [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® - **Phone:** 1-800-727-0025 #### Who Uses This Product? - **Top Industries:** Higher Education, Research - **Company Size:** 51% Large, 26% Small #### What Do G2 Reviewers Say About SAS Data Management? _AI-generated summary from verified user reviews_ ##### Pros - Users find the **ease of use** of SAS Data Management instrumental for effective data preparation and transformation. - Users value the **user-friendly data transformation tools** in SAS Data Management, simplifying data preparation significantly. - Users value the **robust data cleaning tools** in SAS Data Management, enhancing accuracy and consistency throughout analytics projects. - Users find that **SAS Data Quality streamlines data preparation** , ensuring business-ready analytics and improving overall data standards. - Users value the **strong data transformation capabilities** of SAS Data Management, ensuring effective data manipulation and quality control. ##### Cons - Users find the **expensive cost** of SAS Data Management to be a major barrier to access and integration. - Users find SAS Data Management to have a **not user-friendly interface** , making navigation difficult for less experienced individuals. - Users face **slow performance** when handling large datasets, causing frustration and increased time consumption for reports. - Users find that **training is required** to effectively navigate the complexities of SAS Data Management, especially for non-technical individuals. - Users find the **complexity** of SAS Data Management challenging, requiring advanced statistical knowledge to navigate effectively. #### What Are Recent G2 Reviews of SAS Data Management? **["Effortless Data Proficiency Management"](https://www.g2.com/survey_responses/sas-data-management-review-12704573)** **Rating:** 5.0/5.0 stars _— Han L._ [Read full review](https://www.g2.com/survey_responses/sas-data-management-review-12704573) **["Sas Data integration studio review"](https://www.g2.com/survey_responses/sas-data-management-review-11499859)** **Rating:** 5.0/5.0 stars _— sai bharath M._ [Read full review](https://www.g2.com/survey_responses/sas-data-management-review-11499859) #### What Are G2 Users Discussing About SAS Data Management? - [What is SAS Data Governance used for?](https://www.g2.com/discussions/what-is-sas-data-governance-used-for) - [What is SAS Scoring Accelerator used for?](https://www.g2.com/discussions/what-is-sas-scoring-accelerator-used-for) ### [DQE One](https://www.g2.com/products/dqe-one/reviews) DQE One is a real-time data quality platform that validates, standardizes, deduplicates, and enriches customer data, including email addresses, phone numbers, and postal addresses. It helps businesses maintain accurate, complete, and unified customer data across CRM systems, marketing platforms, and operational tools. DQE One solves common data quality challenges such as: - Invalid emails and poor deliverability - Incorrect postal addresses and failed deliveries - Wrong phone numbers and unreachable contacts - Duplicate records and fragmented customer data - Inconsistent data formats across systems It ensures that customer data is clean and usable from the moment it enters your systems. Key capabilities include: - Real-time validation of email, phone, and address data - Data standardization and formatting across systems - Duplicate detection and record merging to create a single customer view - Data enrichment to complete and enhance customer information - Global address validation with country-specific rules - API-first architecture for real-time processing and easy integration DQE One detects duplicate customer records and merges them to create a unified customer view. This improves CRM reliability, reporting accuracy, and overall data consistency. Typical use cases include: - CRM data cleansing and deduplication - E-commerce checkout optimization - Lead capture and contact data validation - Customer data integration across multiple systems - Data governance and data quality initiatives DQE One integrates with platforms such as Salesforce, HubSpot, and other CRM, marketing automation, and e-commerce tools. It can be deployed via API or connectors to ensure data quality across all customer touchpoints. DQE One is designed for companies that want to improve data accuracy, reduce operational inefficiencies, eliminate duplicates, and deliver better customer experiences through reliable data. **Average Rating:** 4.8/5.0 **Total Reviews:** 39 #### How Do G2 Users Rate DQE One? - **Quality of Support:** 9.7/10 (Category avg: 8.9/10) - **Automation:** 9.0/10 (Category avg: 8.7/10) - **Identification:** 9.3/10 (Category avg: 8.9/10) - **Preventative Cleaning:** 8.6/10 (Category avg: 8.5/10) #### Who Is the Company Behind DQE One? - **Seller:** [DQE](https://www.g2.com/sellers/dqe) - **Company Website:** dqe.tech - **Year Founded:** 2008 - **HQ Location:** Levallois-Perret, Île-de-France - **Twitter:** @dqe\_software 173 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=c5e15f9d3cdb19e154b5528bad5897f0ec11441cb0db7f18d2e86ad012f8ca8d&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fdqe-software%2F&secure%5Burl_type%5D=linkedin_company_website) 77 employees on LinkedIn® #### Who Uses This Product? - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 36% Medium, 36% Small #### What Do G2 Reviewers Say About DQE One? _AI-generated summary from verified user reviews_ ##### Pros - Users find DQE One to be **easy to use** and highly intuitive, enhancing operational efficiency and data management. - Users value the **seamless CRM integration** of DQE One, enhancing data consistency and operational efficiency effectively. - Users praise the **data accuracy** of DQE One, enhancing data management and operational performance with ease of use. - Users laud the **improved data quality** from DQE One, enhancing both management processes and operational performance. - Users find DQE One to be an **intuitive solution** , greatly simplifying data management and enhancing accessibility for all teams. #### What Are Recent G2 Reviews of DQE One? **["Simple API and very precise results for normalizing our POI addresses"](https://www.g2.com/survey_responses/dqe-one-review-12262097)** **Rating:** 5.0/5.0 stars _— Denis B._ [Read full review](https://www.g2.com/survey_responses/dqe-one-review-12262097) **["an effective solution to ensure the quality and reliability of data"](https://www.g2.com/survey_responses/dqe-one-review-12889203)** **Rating:** 5.0/5.0 stars _— Sana B._ [Read full review](https://www.g2.com/survey_responses/dqe-one-review-12889203) ### [OneSchema](https://www.g2.com/products/oneschema/reviews) OneSchema provides AI agents for data operations that automate data prep, driving efficiency and improving client project margins. By standardizing raw client files to your RFIs, OneSchema helps teams reach insights and deliver results faster. **Average Rating:** 4.6/5.0 **Total Reviews:** 47 #### How Do G2 Users Rate OneSchema? - **Quality of Support:** 9.5/10 (Category avg: 8.9/10) - **Automation:** 7.7/10 (Category avg: 8.7/10) - **Identification:** 8.1/10 (Category avg: 8.9/10) - **Preventative Cleaning:** 8.9/10 (Category avg: 8.5/10) #### 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:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=b0e54924b21e123b7d3316e698cb1237c373294f7505156e33a1535329f23886&secure%5Burl%5D=http%3A%2F%2Fwww.linkedin.com%2Fcompany%2Foneschema&secure%5Burl_type%5D=linkedin_company_website) 18 employees on LinkedIn® #### Who Uses This Product? - **Top Industries:** Computer Software, Information Technology and Services - **Company Size:** 50% Small, 44% Medium #### What Do G2 Reviewers Say About OneSchema? _AI-generated summary from verified user reviews_ ##### Pros - Users value the **responsive community support** of OneSchema, as they quickly resolve issues and answer questions effectively. - Users appreciate the **quick and effective customer support** of OneSchema, resolving issues promptly and efficiently. - Users value the **customization options** in OneSchema, enabling intuitive and tailored importers for their needs. - Users appreciate the **ease of use** of OneSchema, finding it intuitive and responsive to their needs. - Users value the **responsive support** from OneSchema, ensuring quick resolutions and confidence in their product usage. ##### Cons - Users desire enhanced **customization options** for OneSchema, seeking greater flexibility in the importer and UX improvements. - Users seek enhanced customization and **better UX in interface design** to improve data transformation efficiency. - Users seek **improved UX** in OneSchema, emphasizing the need for better customization and data transformation options. - Users desire **enhanced UX improvements** in OneSchema for better customization and streamlined data transformations. #### What Are Recent G2 Reviews of OneSchema? **["Very intuitive developer experience and stellar UI for users."](https://www.g2.com/survey_responses/oneschema-review-8413749)** **Rating:** 4.5/5.0 stars _— Anton N._ [Read full review](https://www.g2.com/survey_responses/oneschema-review-8413749) **["Quality product with fast support"](https://www.g2.com/survey_responses/oneschema-review-10258401)** **Rating:** 4.5/5.0 stars _— Nep P._ [Read full review](https://www.g2.com/survey_responses/oneschema-review-10258401) ### [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:** 4.4/5.0 **Total Reviews:** 115 #### How Do G2 Users Rate Plauti? - **Quality of Support:** 9.3/10 (Category avg: 8.9/10) - **Automation:** 8.2/10 (Category avg: 8.7/10) - **Identification:** 8.7/10 (Category avg: 8.9/10) - **Preventative Cleaning:** 8.6/10 (Category avg: 8.5/10) #### Who Is the Company Behind Plauti? - **Seller:** [Plauti](https://www.g2.com/sellers/plauti) - **Company Website:** plauti.com - **Year Founded:** 2011 - **HQ Location:** Arnhem, Netherlands - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=29bcf746de0784fe9c7dbbb5663d0dae3e1d2f193814ae150125f609e8d9eb6d&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fplauti-b-v-%2F&secure%5Burl_type%5D=linkedin_company_website) 58 employees on LinkedIn® #### Who Uses This Product? - **Top Industries:** Non-Profit Organization Management, Computer Software - **Company Size:** 56% Medium, 35% Small #### What Do G2 Reviewers Say About Plauti? _AI-generated summary from verified user reviews_ ##### Pros - Users love the **ease of use** of Plauti, appreciating its straightforward, customizable interface and responsive support. - Users appreciate the **powerful duplicate management features** of Plauti, offering customizable criteria and advanced merge rules. - Users praise the **customer support** for being helpful and quick to respond, enhancing the overall experience with Plauti. - Users appreciate the **ease and efficiency of merging leads** with Duplicate Check, thanks to customizable merge rules and support. - Users appreciate the **customization options** of Plauti, which allow tailored solutions for different organizational needs. ##### Cons - Users find the **learning curve steep** , with complex configurations and unclear features making initial use challenging. - Users find the **complexity of options and configurations** in Plauti overwhelming and challenging to master. - Users express frustration with **data management issues** , highlighting limitations in Merge Rules and storage concerns. - Users experience **difficulties with data validation rules** and limits on records, impacting their growing company's needs. - Users find **limited functionality** in Plauti, especially in matching rules, creating confusion during the deduplication process. #### What Are Recent G2 Reviews of Plauti? **["Plauti: Seamless Salesforce Integration and Reliable Deduplication"](https://www.g2.com/survey_responses/plauti-review-12675539)** **Rating:** 5.0/5.0 stars _— Verified User in Manufacturing_ [Read full review](https://www.g2.com/survey_responses/plauti-review-12675539) **["Affordable, No-Frills Duplicate Management—Best for Experienced Users"](https://www.g2.com/survey_responses/plauti-review-11822086)** **Rating:** 4.0/5.0 stars _— Jonathan W._ [Read full review](https://www.g2.com/survey_responses/plauti-review-11822086) #### What Are G2 Users Discussing About Plauti? - [How do I check for duplicates in Salesforce?](https://www.g2.com/discussions/how-do-i-check-for-duplicates-in-salesforce) - 1 comment, 1 upvote - [‹ Prev‹ Prev](/categories/data-quality/small-business?order=g2_score#product-list) - [1](/categories/data-quality/small-business?order=g2_score#product-list) - 2 - Next ›Next › Spotlight Categories [Restaurant POS Systems](https://www.g2.com/categories/restaurant-pos) [Compensation Management Software](https://www.g2.com/categories/compensation-management) [Video Conferencing Software](https://www.g2.com/categories/video-conferencing) [Marketing Analytics Tools](https://www.g2.com/categories/marketing-analytics) [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms) 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) - [Cloud File Storage](/categories/cloud-file-storage) - [Database Software](/categories/database-software) - [Data Center Infrastructure Management (DCIM)](/categories/data-center-infrastructure-management-dcim) - [Data Center Networking](/categories/data-center-networking) - [Data Exchange Platforms](/categories/data-exchange-platforms) - [Data Fabric](/categories/data-fabric) - [Data Integration Tools](/categories/data-integration-tools) - [Data Management Software](/categories/data-management-software) - [Data Mapping](/categories/data-mapping) [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, small business features, pricing, setup, and installation differ from businesses of other sizes, which is why we match buyers to the right Small 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 Small Business Data Quality category. In addition to qualifying for inclusion in the Data Quality Tools category, to qualify for inclusion in the Small Business Data Quality Tools category, a product must have at least 10 reviews left by a reviewer from a small business. Show More * * * ## 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.