Data quality software refer to a wide range of tools and services specifically designed to deliver comprehensive and precise data to organizations. Data quality software vendors offer a broad range of functions and capabilities, which include data cleansing, profiling, parsing, monitoring, and enrichment. The data quality software allow organizations to comprehend, standardize, and monitor the data over the course of its lifecycle, ensuring continuous operation within the system. Ensuring data quality should be a paramount concern to the authorities, as a good dataset within an organization can be a key enabler to gain competitive advantage in the market by conducting better analysis and craft business strategies that will have long-term implication on realizing organizational goals. The 6 key considerations of data quality, which every enterprise should seek for, include consistency, conformity, completeness, uniqueness, accuracy, and integrity of data.

Top 10 Data quality software 2020:

  1. Informatica Corporation
  2. Ibm Corporation
  3. Sap Se
  4. Sas Institute Inc
  5. Syncsort
  6. Talend
  7. Experian Plc
  8. Oracle Corporation
  9. Alteryx Inc
  10. Microsoft Corporation


The vendors are placed into 4 categories based on their performance in each criterion: “visionary leaders,” “innovators,” “dynamic differentiators,” and “emerging companies.” The top 25 vendors evaluated in the data quality software market include Alteryx, Ataccama, BackOffice Associates, Data Ladder, DQ Global, Experian, IBM, Informatica, Information Builders, Infosolve Technologies, Ixsight Technologies, Innovative Systems, Microsoft, Oracle, QFire Software, Pitney Bowes, Neopost, RedPoint Global, SAS Institute, Syncsort, Trianz, Talend, Tamr, and Uniserv.


Vendors who fall into this category receive high scores for most of the evaluation criteria. They have strong and established product portfolios and a very strong market presence. They provide mature and reputable data integration tools. They also have strong business strategies. The visionary leaders in data quality software include IBM, Informatica, Oracle, SAP, SAS Institute, and Talend.


They are established vendors with very strong business strategies. However, they are low in their product portfolios. They focus on a specific type of technology related to the product. Data quality software vendors who fall in this category are Experian, Information Builders, Microsoft, and Pitney Bowes.


Innovators in the data quality software are the vendors who have demonstrated substantial product innovations as compared to their competitors. They have very focused product portfolios. However, they do not have very strong growth strategies for their overall businesses. Vendors who fall in this category are Alteryx, Ataccama, BackOffice Associates, Data Ladder, Innovative Systems, QFire Software, Syncsort, Tamr, and Trianz.


These are vendors with niche product offerings who are starting to gain their positions in the data quality tools market. They do not have very strong business strategies as compared to other established vendors. They might be new entrants in the market and require some more time before getting a significant traction. Data quality software vendors who fall in this category are DQ Global, Infosolve Technologies, Neopost, RedPoint Global, and Uniserv.

Organizations worldwide have adopted data quality tools in order to reap the best possible value from the raw content. The exponential rise in the number of desktop and mobile device users and the easy accessibility to the desired data has enabled organizations to leverage businesses. Further, an enormous amount of data continually generated and accessed through multiple sources has inevitably led to the occurrence of data redundancies and inconsistencies. Furthermore, the ability to sort information from heterogeneous data sources has given significant traction to the data quality tools market. Lately, a collection of various types of data in an organization has led to an unavoidable need to maintain the quality of data in organizations. Considering the intense competition in different industry verticals, organizations are encouraged to utilize advanced data management tools to enhance their business decisions and operational workflows. The data types include customer data, product data, financial data, compliance data, and supplier data.


Customer data is data that is pertaining to the customer. It is one of the major factors which enable organizations to sustain in the competitive market. The integration of critical information pertaining to their clients/customers helps organizations in order to govern their operations and formulate their business plans. Further, with data quality tools integrated over a single platform provides a complete view of client-related content. Customer data is generated and compiled through the Customer Relationship Management (CRM) systems installed among the organizations which allow collection and maintenance of reliable, precise, and updated customer records enabling integrity and authenticity. The streamlined centralization of customer data helps organizations to analyze customer preferences, strengthen customer relationships, augment sales, and strategize on building new clientele as well.


The product data comprises the information related to the products and offerings. The product data creates value for an organization by managing data that describes their tangible and intangible assets, which helps in managing the business operations process such as sales, purchase, planning, production, and associated processes. Additionally, the centralization of product data offers the executives to have an integrated view of the entire lifecycle of their product. Product data extensively help organizations to administer operational performance by analyzing complete data through single point of assistance. Moreover, product data facilitates both the front-office and back-office functions.


Poor quality of financial data can have a long-term impact on the organizations’ finances. With higher accuracy of data, better decisions can be made, and finance being the critical deciding factor, it is one of the major reasons for fueling the growth among various organizations and finance institutions. Financial data comprises sets of information related to the financial operations of a business. These sets of data are used by management to study business performance and identify whether there is need for defining new business strategies. In a recent study, 35% of banks say they are having trouble accumulating customer data and in managing all the requirements that come with this data. Additionally, according to another survey in 2016, 33% of participants stated that data quality was significant challenge and hence, increased adoption can be witnessed among organizations.


Regulatory pressures are crucial factors for organization in every industry. Compliance data can be referred to as the data that is collected under these stated regulations, which can be used to recognize and predict future outcomes. This data helps organizations in the assessment of potential risks and useful for controlling the entire risk landscape, by balancing the risks through required actions.


Today supplier data is considered as the base upon which an organization operates. Supplier data also called vendor data is information provided to the enterprises about the suppliers. It delivers a compiled view of the vendor/supplier comprising information such as supplier offerings, procurement sourcing, accounts, and deliverables, among various others. The companies are using the data quality software to manage and improve the supplier data, to transform it into supplier intelligence to empower the organization and help in making more confident decisions; moreover, good quality supplier data enables enterprise in monitoring supplier records eventually improving the supplier relationships. According to a survey in 2014, 67% of participants agreed that poor supplier data quality was a key barrier that impacted their operations. Similarly, 95% of procurement professionals recognized supplier data quality as an extremely important factor to meet the procurement objectives.

Best Data Quality Software 2022

Comparing 26 vendors in Data Quality Software across 148 criteria.
All vendors(26)
Selected by small-360Analysts
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Datamatch Enterprise creates fully scalable configurations for deduplication and record linkage. The solution has the ability to identify and transform complex product data from disparate sources. Data Ladder’s advanced semantic recognition technology assesses product data instantly from various data sources, understands the context, and helps users make informed decisions by precisely matching, categorizing, and deriving complex product hierarchies. The company's data deduplication software also allows organizations to find matches across all the data sources with a 96% accuracy.
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Informatica Data Quality software ensures best data quality for all business applications, whether they are on-premises or cloud applications. The solution includes unified role-based tools that facilitate the participation of business in the data quality process and deliver comprehensive support for applying data quality rules to products, assets, and customer data. The company provides enhanced flexibility and agility to its customers in terms of accessing and cleansing the data which is located at any source within an enterprise, be it on premises or on the cloud.
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IBM focuses on various aspects of data quality. IBM InfoSphere Information Server offers several capabilities that address data quality needs of businesses. IBM InfoSphere Information Server is an IBM data quality software which helps enterprises extract more value from complex, heterogeneous information spread across systems. IBM offers a substantial range of products for managing the end-to-end data quality requirements of organizations.
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SAP offers SAP Data Management in the data quality tools market. SAP Data Management offers a broad range of functionalities for data quality, data integration, and data cleansing. It offers flexibility to the business users, maintains data quality, and ensures data consistency across the enterprise. SAP Data Management helps access data on-premises and on the cloud. SAP Data Management can be integrated with SAP Information Steward to assist enterprises in tracking data records for enhanced information governance.
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SAS data quality software provides various features including data integration, data cleansing, data profiling, and data preparation for Hadoop, data governance, and event stream processing. The company’s data management solutions help businesses analyze and maintain the data generated by different devices, sensors, and software. The solution allows organizations to clean their data without having to extract it or move it.
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Through the acquisition of Trillium Software, Syncsort gained unparalleled advantage in offering comprehensive solutions for the data integration and data quality tools markets. Trillium Software has a strong foothold in the data quality tools market and offers TS Quality, a single solution which is capable of ingesting both structured and unstructured data. Trillium Quality solution categorizes data across the enterprise including the unstructured and semi structured data to enhance the efficiency of the business and IT Teams. 
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Talend offers Talend Open Studio as Data Quality Software as its prime solution in the data quality tools market. The software offers intrinsic features, such as data profiling tools, which are instrumental in providing a comprehensive view of enterprise data, and help to recognize grey areas in the organization where the data is either incomplete or duplicated or out of conformance with standards.
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Experian Data Quality is a global provider of data quality software and services. These software and services are offered via flexible Software-as-a-Service (SaaS) and on-premises deployment models. The company offers comprehensive data management solutions which help organizations achieve their business goals. Experian Data Quality assists in maintaining the accuracy of the collected data which leads to an efficient operational workflow. It offers a real-time capturing of the customer information which helps in keeping data up-to-date.
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Oracle offers various tools for maintaining the data quality of an organization. The Oracle Enterprise Data Quality product suite helps organizations achieve maximum business value by providing high-quality data. The solution provides businesses with multi-user project support with an ability to manage all types of data including customer, product, asset, financial, and operational data.
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Alteryx's Data Quality software allows organizations to understand the quality of a dataset and also enhance the data to make it ready for analytics. The company provides data profiling visualizations which offer a segmentation view based on quality and issues. The company also delivers specific statistics based on individual fields in the user's data, based on their data types. Moreover, Alteryx offers in excess of 45 tools like find and replace, that help companies in improving the quality of their data.
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Microsoft Data Quality Services is a knowledge-based product that provides both computer-assisted and interactive methods to govern integrity and quality of the data sources. The DQS solution performs data cleansing through cloud-based reference data services provided by reference data providers. Microsoft Data Quality Services also provides data profiling integrated with data quality tasks, allowing analysis of the integrity of enterprise data. The data quality tools offered by Microsoft Server DQS empower an information steward or an IT expert to keep up the quality of data.
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Pitney Bowes offers a wide range of products in the data quality tools market. These products include Spectrum Data Discovery Module, Spectrum Advanced Matching Module, Spectrum Data Normalization Module, Spectrum Universal Name Module, and Spectrum Universal Addressing Module. The various capabilities offered by the company’s products are data profiling, advanced data matching and consolidation, data enrichment with reference data, standardization and normalization of data, monitoring trends, and Key Performance Indicators (KPIs).
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Ataccama's Data Quality software & Cleansing solution helps users in transforming their data. It allows companies to use an extensive set of predefined algorithms or enables them create their own. The company's Anomaly Detection feature leverages AI to identify problems in data loads, including data volume changes, etc. Ataccama's Data Profiling helps users learn about the critical patterns in their data. It also finds duplicate records and uses multiple edit distance metrics to reveal hidden relationships in the data.
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Information Builders offer a comprehensive product suite that helps organizations monitor and manage their information assets. The company offers the iWay Omni-Gen Data Management platform which has Omni-Gen Data Quality Edition as one of its chief components. Omni-Gen Data Quality Edition is instrumental in offering all-inclusive features and capabilities that are designed to optimize the integrity of the enterprise data irrespective of the data source, location, or format.
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Trianz offers DataVision as its core offering in the data quality tools market. DataVision+ is an automated solution, designed to meet the needs of data comparison across various sources. The cloud and mobileenabled platform enables users to write custom SQL queries, compare data between source and target environments, and generate meaningful reports. DataVision+ is also capable of synchronizing metadata and generating queries automatically to compare. In addition, the solution can test crystal reports and big data.
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Tamr offers a patented enterprise data unification platform that combines machine learning with human expertise for combining numerous data sources to provide unmatched scalability, speed, and accuracy. The company distinguishes itself from other market players by offering a bottom-up, machine-learning based approach which is instrumental in unifying disparate enterprise datasets.
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Backoffice Associates has developed a Data Quality Scorecard that provides web-based analytics, reports, and insights through a consolidated dashboard that allows businesses to view their critical business metrics. The company also conducts Data Quality and Readiness Assessment, which is supported by their applications which instantly deliver report findings with specific data challenges. The company also offers the best practices in Data Quality developed by experts to help organizations in addressing their data problems.
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Qfire's The rule editor allows look-up checks, comparisons and integrity statements to be added without coding. QFire’s set-and-forget built-in feature enables organizations to instantly create the validation rules needed to apply to data. Also, QFire Validate notifies the users about the error details whenever a new data item blocks the flow. QFire Quality Firewall helps users to decide if upon a course of action to protect an entire dataset. The users get the flexibility to decide if the error to be marked as critical, high, medium or low.
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Infosolve's Data Quality software identifies and eliminates nulls and invalid data. It also discovers data patterns and frequency counts. The company's Data Enhancement provides organizations an opportunity to supplement information in their existing data and also supports organizations through their planning cycles. The company's Data Quality solutions offer well-defined data profiling capabilities which are important for the identification of data quality problems. OpenCDI has been developed on the Infosolve’s innovative Zero Based solution platform which delivers maximum flexibility with the open source technology and high ROI.
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Ixsight’s Customer Information Management solution helps assess customer, supplier, product and material data including unstructured text information in order to enable smarter decision-making for companies. Dedupe collaborates customer information and internal information to provide in-depth analysis of potential loyalty. Deduplix assesses records in real-time and offers total flexibility in providing the best results. It also enables businesses to categorize modules to validate matches and create golden records.
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Innovative System's Enlighten instantly scales from thousands of records to hundreds of millions. The solution's in-depth understanding of data context eliminates errors and saves considerable effort and money. The company deploys teams who have expertise in data quality which provides seamless and rapid implementation along with consistent support. The company provides multiple delivery options such as on-premise and SaaS or a combination of both, depending on the business situation. These options are fully scalable.
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RedPoint consolidates customer data from multiple sources, in any format, without coding. It enables users to integrate first, second, and third party sources to enable a complete and precise view of every customer. Businesses use RedPoint Data Quality solutions to automate data quality with zero latency, to make decisions which result into better customer experiences. The solution leverages advanced matching algorithms to deliver accurate and automated master customer data. The solution reads data across multiple sources, including CRM, ERP, and all major databases.
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DQ for Dynamics™ is a leading data deduplication and data cleansing solution which works right inside Dynamics CRM.

Find duplicates fast using our advanced fuzzy searching logic, then review multiple duplicate records side by side, to first perfect and then merge duplicate records. Apply enrichment, validation, formatting, suppression and many more functions available through DQ on Demand™. Ultimately leaving you with a single, high quality, mastered Golden Record or Single Customer View within your Microsoft Dynamics 365 CE database.

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Neopost's ConnectSuite e-Validate is a simple cloud-based solution that helps businesses instantly update customer addresses. It minimizes instances of returned mail and parcels, with savings of up to USD 25 per piece. The solution also enhances email delivery by rectifying addresses for customers who have changed their addresses. The company's Quadient Bulk Mailer helps companies simplify their mailings, improve deliverability, and acquire the lowest postage rates. Quadient Architect is another contact data quality solution offered by Neopost that validates contact data across digital channels and updates existing records for compliance and customer experience.
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The Uniserve Customer Data Platform provides a multi dimensional view whereby all customer data is consolidated into a single dataset. It then creates a Golden Profile that delivers consistent high-quality data required for successful customer data management on the Customer Data Platform. The platform offers better scaleability which allows businesses to choose the data sources to be integrated. It manages customer data without interrupting running businesses and also provides quicker deployment and rapid return on investment (ROI).
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Tibco enables users to manage multi-domain master data assets in one solution, including flexible workflows and data quality that provide better visibility and control. The company's MDM is an accurate data source that helps businesses in enhancing their revenue by communicating with customers on their preferred channels. The company's EBX software provides businesses with self-service capabilities to help them manage their key data assets on one unified solution.
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Data Quality Software Related Articles
Frequently Asked Questions (FAQs)
The overall data quality tools market is expected to grow at a CAGR of 17.7% from 2017 to 2022.
Data quality software refers to a wide range of tools and services specifically designed to deliver comprehensive and precise data to organizations. Data quality software vendors offer a broad range of functions and capabilities, which include data cleansing, profiling, parsing, monitoring, and enrichment. The data quality software allow organizations to comprehend, standardize, and monitor the data over the course of its lifecycle, ensuring continuous operation within the system. Ensuring data quality should be a paramount concern to the authorities, as a good dataset within an organization can be a key enabler to gain competitive advantage in the market by conducting better analysis and craft business strategies that will have long-term implication on realizing organizational goals. The 6 key considerations of data quality, which every enterprise should seek for, include consistency, conformity, completeness, uniqueness, accuracy, and integrity of data.
Data quality solution providers, Governance, Risk Management, and Compliance (GRC) solution providers, Consulting companies, Government agencies, Risk assessment service providers, Investors and venture capitalists, Value-added resellers, Small and Medium-Sized Enterprises (SMEs) and large enterprises, Third-party providers, Consultants/consultancies/advisory firms, Support and maintenance service providers and Technology providers etc.
Data quality tools are generally effective in four areas: data cleansing, data integration, master data management, and metadata management. The tools generally identify errors with the help of algorithms and lookup tables. They also helps in managing multiple tasks, that include validating contact details and mailing addresses, data mapping, data consolidation associated with ETL tools, data validation reconciliation, sample testing, data analytics etc.