Best Data Quality Software for Medium-Sized Businesses

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

    In addition to qualifying for inclusion in the Data Quality Software category, to qualify for inclusion in the Medium-Sized Business Data Quality Software category, a product must have at least 10 reviews left by a reviewer from a medium-sized business.

    Top 10 Data Quality Software for Medium-Sized Businesses

    • RingLead
    • DemandTools
    • Talend Open Studio for Data Quality
    • Melissa Clean Suite
    • Melissa Data Quality Suite
    • Introhive
    • Openprise
    • Microsoft Data Quality Services
    • D&B Optimizer
    • WinPure Clean & Match

    Compare Medium-Sized Business Data Quality Software

    G2 takes pride in showing unbiased reviews on user satisfaction in our ratings and reports. We do not allow paid placements in any of our ratings, rankings, or reports. Learn about our scoring methodologies.
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    (145)4.3 out of 5
    Entry Level Price:FREE

    About RingLead RingLead is a SaaS cloud-based data orchestration platform that offers a complete end-to-end suite of solutions to discover, clean, protect, enhance, segment, score, and route your CRM and marketing automation data. Since 2003 RingLead has helped solve the data challenges of Fortune 500, and other large, medium, & small enterprises across the globe. RingLead automates the way organizations conduct their most important data processes: - Deduplication - Normalization - Enri

    (153)4.5 out of 5
    Optimized for quick response
    Entry Level Price:$10 per user / per month

    DemandTools is a CRM data quality suite that enables organizations to deliver high-quality data in Salesforce CRM or Microsoft Dynamics 365 CRM. The DemandTools modules are broken down into three major sections according to their primary objectives: Maintenance Tools – Modules for data loading, data backups, data manipulation, report management and record reassignments Cleansing Tools – Modules for duplicate merging and prevention and lead conversion management Discovery Tools – Modules for c

    (26)4.4 out of 5

    Talends open source products and open architecture create unmatched flexibility so you can solve integration challenges your way.

    (96)4.4 out of 5
    Optimized for quick response
    Entry Level Price:$30 per 10,000 Addresses

    Melissa’s Clean Suite (previously Melissa Listware) fights dirty data in your Salesforce®, Microsoft Dynamics CRM®, or Oracle CRM and ERP platforms by verifying, standardizing, correcting and appending your customer contact data records. The result – clean, vibrant, valuable data you can use for squeaky clean omnichannel marketing and sales success. • Autocomplete, verify and correct contacts before they enter the CRM • Add valuable demographic and firmographic data for effective lead scoring,

    (84)4.4 out of 5
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    Entry Level Price:$0.015 records per year

    Melissa’s 35 years of deep domain expertise in address management and data quality combines a global consortium of multi-sourced data with the latest innovations to help businesses keep their customer data clean. Our enterprise Data Quality Suite provides wide capabilities that clean, correct and verify addresses, names, phones and emails at the point of entry. The Data Quality Suite offers: Address Verification: Validates, corrects and standardizes addresses in batch, point of entry or can o

    (29)4.3 out of 5
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    Born from the frustration of trying - and failing - to utilize CRM to discover who knows who, Introhive is an AI-powered platform that helps organizations of all sizes and complexity unlock the power of their business relationships. Introhive’s automated data collection and AI-powered relationship intelligence empower sales, marketing and business development teams to ditch mundane data entry and focus on what matters most—building connections and closing deals. Introhive helps clients: - In

    (49)4.9 out of 5
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    Openprise Data Orchestration and CDP solutions automate all your business processes to deliver a crystal-clear, 360-degree view of customers and prospects across your entire martech stack. Openprise is a single, no-code platform that combines the best practices, business rules, and data you need to automate hundreds of processes like list loading, cleansing and enrichment, segmentation, account scoring, and many more. With Openprise, you can boost campaign performance, scale up your operations,

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

    (52)3.9 out of 5
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    Powered by the Data Cloud, D&B Optimizer serves as the foundational building block for your sales and marketing alignment by delivering valuable business intelligence on more than 350 million business records and their corporate hierarchies. These records are curated from thousands of sources and are updated 5 million times a day providing you with the quality B2B data you need to increase productivity and organizational alignment, while enabling you to accelerate growth. D&B Optimizer

    (59)4.7 out of 5

    Clean & Match is WinPure’s award-winning data cleansing and data matching software suite, specially designed to increase the accuracy of business or consumer data. This software suite is ideal for cleaning, correcting and deduplicating mailing lists, databases, spreadsheets and CRMs. 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 a

    (27)4.4 out of 5
    Entry Level Price:$1,096 per year

    Cloudingo solves the biggest problem with Salesforce data: duplicate records. What’s unique about Cloudingo is its ability to comb through Salesforce to find duplicated records while giving you the most flexibility and control, with the least headaches of any deduplication tool on the market. And while removing duplicates is at the core of what Cloudingo does, there’s a lot more to data cleansing. Developed with user feedback in mind, it’s no wonder Cloudingo is a favorite app among Salesforce u

    (23)4.1 out of 5

    DataMatch Enterprise is a highly visual desktop data cleansing application specifically designed to resolve customer and contact data quality issues. The suite consists of scalable configurations for deduplication & record linking, suppression, enhancement, extraction, and standardization of business and customer data.

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    Check out the G2 Grid® for the top Data Quality Software products. G2 scores products and sellers based on reviews gathered from our user community, as well as data aggregated from online sources and social networks. Together, these scores are mapped on our proprietary G2 Grid®, which you can use to compare products, streamline the buying process, and quickly identify the best products based on the experiences of your peers.
    Leaders
    High Performers
    Contenders
    Niche
    D&B Optimizer
    DemandTools
    Cloudingo
    RingLead
    Melissa Data Quality Suite
    Introhive
    DataMatch Enterprise
    WinPure Clean & Match
    Microsoft Data Quality Services
    Talend Open Studio for Data Quality
    Openprise
    Melissa Clean Suite
    Market Presence
    Satisfaction

    Learn More About Data Quality Software

    What is Data Quality Software?

    Data is arguably the single biggest driver in modern business. Because of its value as both a point of reference and as a way to drive profit and potential, data integrity is imperative for success.

    Data quality solutions are explicitly designed to improve data integrity for any data sources a business might need maintained. They sift through and isolate “bad" data to either correct it or purge it from the data source. Data quality software can also help make your business’ data more uniform so that integrating your data with other software is less frustrating and time consuming.

    Key Benefits of Data Quality Software

    • Data identification and repair
    • Data normalization
    • Improved overall data utility

    Why Use Data Quality Software?

    Data quality software, as the name suggests, is built for improving the caliber of your company’s data. It can be easy for business data entries to be incomplete, duplicated, improperly formatted, or flat out incorrect, especially when that data involves personal or contact data. As such, it’s important that businesses have ways to correct and maintain the quality of their data quickly and often. Hence, data quality software.

    Subpar data integrity can be costly for businesses, both in work hours and money spent. Employees might have to spend extra time verifying data correctness or completeness when that time could be spent focusing on projects or other tasks. As well, in situations like marketing or sales where you might be paying for items or services at a per-person rate, duplicate or inaccurate data can negatively impact the bottom line. Data quality solutions are a great option for companies to be sure that their business data is accurate and complete and helps minimize the negative outcomes associated with bad data.

    Who Uses Data Quality Software?

    Because of the wide range of specializations that data quality solutions can take, anyone in a business could potentially find at least some value from data quality software. The specific type of data quality software a person ends up using relates by and large to their position in the company. Sales and marketing may use one type, while database admins or shipping specialists would use other types.

    Kinds of Data Quality Software

    Data quality solutions are usually designed with one or a few specific data sources in mind. They typically focus on improving the quality of data in one or more of the following categories.

    CRM — Many data quality solutions are used in the context of CRM because of how important customer and prospect data is for generating and retaining sales. CRM-focused data quality software is aimed at keeping all prospect and client data up to snuff.

    Database — Other data quality software is built specifically for creating and retaining quality within databases. These data quality solutions are built to handle a high volume of data entries. The range of data that these solutions can process is wide, since so many different types of data—from personal to transactional and anything in between—can be stored in a database.

    ERP — Some solutions are designed for ERP systems to ensure end-to-end financial, business, and supply data are accurate. Though taking a similar span of data types as database-focused data quality solutions, those for ERPs deal with that data through the actual ERP platform directly.

    File type specific — The previously noted data sources aren’t the only places where quality matters. Many of us rely on files like spreadsheets or XMLs every day to complete our tasks. Data quality solutions can be built for those specific file types to help businesses organize data that doesn’t get stored in larger systems like those listed above.

    Data Quality Software Features

    Data identification — Data quality solutions must be able to identify “good" and “bad" data within your data source(s). Data identified as bad is then passed through a cleansing process.

    Data cleansing — Cleansing—correcting or removing—bad data can take several forms, be it deletion, modification, merging, or other methods. Deduplication (the act of removing identical entries) and modification (e.g., capitalizing all first letters in names) are some of the most common cleansing methods.

    Normalization — For many kinds of data to be useful, the data has to be uniform for processing through other software. Normalization is the data quality process of standardizing all data of a certain type to the same format.

    Automation and scheduling — Manually running data identification and cleansing tasks can be a pain. Many data quality solutions allow you to automate these tasks, both routinely and with new incoming data, and they can offer scheduling capabilities for, say, weekly quality checks.

    Reporting — Many data quality solutions will include reporting features to give your business an idea of how much data was assessed, what changed, where any issues occurred, and other overhead information you may need.

    Additional Data Quality Features

    Data appending — While some data may need to be deleted, adjusted, or normalized, other data might have components missing that are critical to the data being affected. Data appending—the addition of component pieces to existing data—can be a valuable asset for making whole, useful data from an incomplete source.

    Data enrichment — Businesses sometimes use disparate data sources to build a stronger overall pool of data from which to work. Data enrichment features allow businesses to bring in data from multiple sources, normalize and bolster that data, and use it as though it came from a single source.

    Regulatory compliance — For industries where regulations are top priorities (e.g., health care and finance), a data quality solution would need to be able to preserve quality in the data source(s) without breaking regulations. Some data quality solutions take regulatory compliance into consideration for cleaning, which helps businesses stay compliant at the data source.

    Potential Issues with Data Quality Software

    Normalization inaccuracy — Normalizing your data against an improper format can be a project-halting mistake. Be sure, when setting up any normalization parameters for your data, that the parameters are absolutely correct the first time. Otherwise, you may have to spend extra time renormalizing your data to fix a mistake from the normalization template.

    Over- or underbuying — Prior to purchasing, be sure you understand the full extent of capabilities you need (or might need) your data quality solution to have. Buying for only, say, a CRM focus might not be the best idea when your company also stores a lot of business data in databases. Or purchasing a file-type-oriented solution might be limiting if your business plans to expand into a CRM in the near future. But also, be sure to be realistic about the functions you’ll use, else your business might overspend for a product whose functions aren’t all useful to you.

    Standards adherence — If your business deals with data that needs to apply to certain regulations (e.g., medical data), be sure that the data quality solution you select can handle the demands that come with regulatory adherence. Not complying with data regulations is an expensive problem that businesses should avoid as much as possible.

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