SAP Data Quality Management, Informatica Data Quality, SAP Data Services, Oracle Enterprise Data Quality, IBM InfoSphere Information Analyzer, IBM InfoSphere QualityStage, SAP Address and Geocoding Directories, Data Quality Monitor, Data Quality Explorer, and Data Quality Batch Suite.
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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.
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…
SAP Business Objects Data Quality Management embeds data quality functionality into SAP applications.
Oracle Enterprise Data Quality is, as the name would suggest, a data quality offering from Oracle for enterprises.
Talend Data Quality is an open source data management tool handling parsing, standardization, matching and data profiling.
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…
Ataccama is a data quality platform handling data parsing, standardization, cleansing and matching, and data profiling.
Trillium Cloud developed by Trillium Software, now a Syncsort property since the 2016 acquisition, is an enterprise cloud-based data quality option, available as a subscription service and designed to present a simpler, expert-assisted management solution.
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 offers the Aperture Data Studio, a data quality management platform based on technology acquired by Experian with QAS, ltd.
RingLead Cleanse (formerly Duplicate Prevention, or "Unique Entry") enforces perimeter protection around B2B databases to stop dirty data in real time, at the source, and consistently maintain and improve the health of data. It is a ZoomInfo solution since the September 2021 acquisition.…
IBM InfoSphere Information Analyzer provides a data quality solution featuring assessment, monitoring, and rule design and analysis, from IBM.
Omni-Gen aims to facilitate efficient integration and mastering of data by helping MDM implementers collaborate with business people regarding business domains such as customer, location, and supplier. Instead of starting with a survey of existing data – a bottom-up approach – business…
Spectrum Enterprise OnDemand from Pitney Bowes is a customer data quality offering for validating addresses and enhancing data with geographic information.
Syncsort Trillium DQ for Big Data (formerly Trillium Quality for Big Data) supports enterprises using a Big Data framework like Hadoop with data quality functions like data integration, data cleansing, standardization and parsing, with prebuilt process flows that can be configured…
Information Builder's Omni-Gen Integration Editions is presented as a unified solution from that aims to ensure access to timely, accurate data across all systems, processes, and stakeholders with unmatched interoperability between disparate systems and data. According to the vendor,…
Omni-Gen™ Data Quality Edition makes it easier for business and IT to collaborate on data management projects. It helps companies leverage powerful data integration and cleansing technologies to ensure data accessibility, consistency, accuracy, and timeliness. Organizations can…
Health Language (a subsidiary, now integrated into Walters Klower Health since late 2013), is an enterprise clinical and health content management system, a data quality solution designed to transform data from abstract to actionable, so users in healthcare can maximize reimbursement,…
The Data Quality Explorer from German company Uniserv is a data quality offering.
Data Quality Real-Time Services is a data quality offering from German company Uniserv.
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. These tools will usually be categorized as either data cleansing, data auditing, or 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 the notion of reliable data, which is essential to providing a solid basis for effective decision-making. By detecting anomalies across multiple data sources, an organization is able to achieve higher data completion with the automatic elimination of typos and abbreviation errors. 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: Checking format and that address represent a real physical location.
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
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.
Some key benefits to note for businesses when using data quality software include:
