Data Quality Software

Data Quality Software Overview

Data quality software tools are used by businesses to improve the consistency, accuracy, and overall completion of their data by analyzing sets of information and identifying any inaccuracies or gaps. Common categories for these tools include data observability, data cleansing, data auditing, and data migration. They are used heavily by data analysts, data scientists, and various Operations personnel for sales and marketing departments.

Data quality software helps improve an organization's data reliability, which is essential to providing a solid basis for effective decision-making. By detecting anomalies across multiple data sources, these tools help businesses achieve higher data completion. For instance, these tools may automatically correct typos, flag bad data entries, and view dependencies in a data stack. With the emergence of big data strategies, data quality improvement has become an essential process. Investing in these types of software is becoming a more popular course of action across business types.

With data quality tools becoming more used within organizations, it’s important to understand the strategies they use. They include:

  • Parsing and standardizing data: Data is broken up into multiple structured elements and then each element is standardized according to predefined rules.
  • Matching and merging data: Data records that look similar are automatically flagged as possible matches, and if they are found to be matches the records are then merged.
  • Case management: Some data records will be found to be incomplete or erroneous. This problematic data is automatically flagged and placed in a queue where it can be investigated and remediated later.
  • Address Verification: Validating address formats and verifying that the address represents a real physical location.

Best Data Quality Software include:

SAP Data Quality Management, HubSpot Operations Hub (PieSync), DemandTools, and Clear Analytics.

Data Quality Software TrustMap

TrustMaps are two-dimensional charts that compare products based on trScore and research frequency by prospective buyers. Products must have 10 or more ratings to appear on this TrustMap.

Data Quality Products

(1-25 of 82) Sorted by Most Reviews

The list of products below is based purely on reviews (sorted from most to least). There is no paid placement and analyst opinions do not influence their rankings. Here is our Promise to Buyers to ensure information on our site is reliable, useful, and worthy of your trust.

DemandTools

DemandTools for AppExchange is a data quality toolset for Salesforce.com CRM centric customers. The product comprises 11 individual modules to control, standardize, verify, deduplicate, import and manipulate Salesforce and/or Force.com data.

ZoomInfo OperationsOS

ZoomInfo's OperationsOS is a data-as-a-service (DaaS) platform that provides B2B commercial data delivered on the user's terms boasting strong match rates, match accuracy, fill rate, and fill accuracy that combined can boost the user's data reliability.

HubSpot Operations Hub (PieSync)

HubSpot Operations Hub (based on technology from the former PieSync that was acquired by HubSpot November 2019) is a two-way contacts integration platform. The vendor emphasizes quick and easy setup automated customer and client data matching and updating between apps.

Informatica Data Quality

The vendor states that Informatica Data Quality empowers companies to take a holistic approach to managing data quality across the entire organization, and that with Informatica Data Quality, users are able to ensure the success of data-driven digital transformation initiatives and…

Key Features

  • Data source connectivity (6)
    94%
    9.4
  • Data profiling (6)
    92%
    9.2
  • Master data management (MDM) integration (6)
    90%
    9.0
SAP Data Quality Management

SAP Business Objects Data Quality Management embeds data quality functionality into SAP applications.

Key Features

  • Data source connectivity (12)
    100%
    10.0
  • Master data management (MDM) integration (11)
    99%
    9.9
  • Data profiling (11)
    96%
    9.6
SAP Data Services

SAP Data Services is an offering from SAP to improve data quality.

Key Features

  • Data element standardization (11)
    70%
    7.0
  • Data profiling (11)
    60%
    6.0
  • Data source connectivity (11)
    50%
    5.0
Clear Analytics

Clear Analytics is a business intelligence solution that enables non technical end users to perform analytics by leveraging existing knowledge of Excel coupled with a built in query builder. Some key features include: Dynamic Data Refresh, Data Share and In-Excel Collaboration.

Key Features

  • Customizable dashboards (8)
    91%
    9.1
  • Pixel Perfect reports (8)
    90%
    9.0
  • Report Formatting Templates (8)
    88%
    8.8
Oracle Enterprise Data Quality

Oracle Enterprise Data Quality is, as the name would suggest, a data quality offering from Oracle for enterprises.

Key Features

  • Data profiling (7)
    100%
    10.0
  • Data source connectivity (7)
    95%
    9.5
  • Master data management (MDM) integration (7)
    95%
    9.5
Talend Data Quality

Talend Data Quality is an open source data management tool handling parsing, standardization, matching and data profiling.

IBM InfoSphere QualityStage

IBM InfoSphere QualityStage is a data quality offering from IBM.

V12 Data

The V12 Data Platform (formerly called the Launchpad Marketing Cloud) is comprised of a collection of online and offline marketing solutions that is designed to manage existing customer relationships and identify new prospective customers by granting users access to The V12 Group…

OvalEdge

OvalEdge is a data catalog and data governance tool that virtually centralizes all of a company's data into a single repository or catalog. OvalEdge provides a progressive approach to data governance, helping companies to:Catalog: Make data asset discovery easy by automatically cataloging…

Precisely Spectrum Quality

Trillium Quality, formerly Syncsort Trillium DQ, is a data quality solution that supports rapidly changing business needs, data sources and enterprise infrastructures including big data and cloud.

Melissa Data Quality Suite

The Data Quality Suite from Melissa headquartered in San Margarita, helps organizations of all sizes verify and maintain data so they can effectively communicate with their customers via postal mail, email or phone.

IBM InfoSphere Information Analyzer

IBM InfoSphere Information Analyzer provides a data quality solution featuring assessment, monitoring, and rule design and analysis, from IBM.

Ataccama ONE

Ataccama is a data quality platform handling data parsing, standardization, cleansing and matching, and data profiling.

SAS DataFlux

SAS DataFlux's capabilities handle data profiling, matching, cleansing and monitoring. Capabilities are available as individual products or as a platform. DataFlux competes with Informatica, Trilliium, Ataccama, and SAP Data Quality Management.

Experian Phone Validation (Mobile Validation)

Experian phone verification software finds the number and checks if it’s active. The software also collects information like phone type and network provider. To make sure the phone number is receiving calls, the software sends a test message to the phone, which is not visible to…

Experian Aperture Data Studio

Experian offers the Aperture Data Studio, a data quality management platform based on technology acquired by Experian with QAS, ltd.

Collibra Data Intelligence Cloud

The Collibra Platform is a cloud-based data governance platform from the company of the same name in Brussels, enabling users to gain visibility into their data, collaborate intelligently and enable users to easily access trustworthy data, automate processes, manage compliance and,…

Experian Email Validation

The Experian Email Address Verification service helps marketing, customer service, and informational emails reach the right customer. It works by using an email validator to check email addresses. The validator determines whether the email is real and can receive mail.

PostGrid Address Verification

PostGrid Address Verification API and platform allows companies to verify, validate, standardize, autocomplete and parse postal addresses globally across 245+ countries. The service cleans data along with a lot of other metadata into the user's system. It can be used on a website…

Enquero PowerMe from Genpact

PowerMe, from Genpact company Enquero, creates discoverable pool of Analytics and BI assets enabling business users to search, discover, and collaborate with data. PowerMe is an Integrated Analytics Catalog with built-in Data Quality and Data Lineage that aims to provide high-quality…

Certica Solutions Certify

Certica Solutions offers Certify, a web-based enterprise data quality application that continually validates databases for business rule integrity, data quality requirements and potential compliance issues. Centralized, automated and designed to validate hundreds of millions of records…

SAP Data Quality Management, microservices for location data

To run at the speed of business, accurate business data is crucial, especially the location data for your customers, your suppliers, and your people. SAP® Data Quality Management, microservices for location data, smoothly embeds address cleansing, validation, and other location-…

Learn More About Data Quality Software

What is Data Quality Software?

Data quality software tools are used by businesses to improve the consistency, accuracy, and overall completion of their data by analyzing sets of information and identifying any inaccuracies or gaps. Common categories for these tools include data observability, data cleansing, data auditing, and data migration. They are used heavily by data analysts, data scientists, and various Operations personnel for sales and marketing departments.

Data quality software helps improve an organization's data reliability, which is essential to providing a solid basis for effective decision-making. By detecting anomalies across multiple data sources, these tools help businesses achieve higher data completion. For instance, these tools may automatically correct typos, flag bad data entries, and view dependencies in a data stack. With the emergence of big data strategies, data quality improvement has become an essential process. Investing in these types of software is becoming a more popular course of action across business types.

With data quality tools becoming more used within organizations, it’s important to understand the strategies they use. They include:

  • Parsing and standardizing data: Data is broken up into multiple structured elements and then each element is standardized according to predefined rules.
  • Matching and merging data: Data records that look similar are automatically flagged as possible matches, and if they are found to be matches the records are then merged.
  • Case management: Some data records will be found to be incomplete or erroneous. This problematic data is automatically flagged and placed in a queue where it can be investigated and remediated later.
  • Address Verification: Validating address formats and verifying that the address represents a real physical location.

Data Quality Software Features

Some of the most common features found within data quality software products include:

  • Connectivity to multiple data sources
  • Data profiling and auditing to help find anomalies, hidden relationships between data elements
  • Seamless integration with Master Data Management (MDM) systems
  • Parsing and standardization of data elements according to pre-defined rules
  • Match and merge capability
  • Data format and valid address checking
  • Address validation

Data Quality Software Comparison

Consider these factors when comparing data quality software:

  • Scalability: For some products, the number of users and concurrent processes you plan to have within the system could cause some products to slow down their performance. If you plan to have multiple users, be sure the data quality tool is able to function at its normal performance under increased stress.
  • Ease of Use: The learning curve for some of the products may be steep for some developers if they aren’t already experienced using the kind of coding some of the tools contain. Many reviews highlight how easy to use or accessible a given data quality tool is to developers and business users.

Start a data quality software comparison here

Pricing Information

Most data quality software vendors do not provide transparent pricing information. Pricing can depend on factors like the number of data sources used and how many features are included in the product. For customized pricing, be sure to contact the vendor directly. Businesses should expect to pay for a data quality tool via a monthly subscription.

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Frequently Asked Questions

What businesses benefit most from data quality software?

Any business with a lot of data can benefit from data quality tools, but they are particularly useful for businesses with multiple data sources pertaining to a single subject. For example, if a business has multiple data sources on a single customer, a data quality tool will help standardize that data.

Are there any free or open source data quality tools?

There aren’t many completely free data quality options, but many proprietary tools offer free trials that users can use to familiarize themselves with each data quality option before making a purchasing decision.

How can I best utilize a data quality tool?

Data quality tools will help you cleanse and standardise your data, but to get the most out of a data quality tool, a business should implement a data quality strategy across all of their applications that collect data. By combining data quality tools with a good data quality strategy, businesses can get more value out of every piece of data they collect.

What does data quality software do?

Data quality software is designed to ensure that business data is as reliable as possible. Data quality tools improve business data by detecting anomalies across multiple data sources, as well as cleansing and standardizing data for analysis.

What are the benefits of using data quality software?

Some key benefits to note for businesses when using data quality software include:

  • Availability of high-quality data for business intelligence projects and master data management.
  • Reduced time to implement data governance or compliance audits.
  • Consolidated views of customers and households enabling more effective cross and upselling.
  • Provision of research data for fraud detection and planning.