What’s Changed: 2016 Gartner Magic Quadrant for Data Quality Tools

What’s Changed: 2016 Gartner Magic Quadrant for Data Quality Tools

Technology research giant Gartner, Inc. has released the 2016 version of their Magic Quadrant for Data Quality Tools. According to Gartner, this market continues to show notable growth as a result of cost, optimization and digital business initiatives. Revenue growth is also on par, as the data quality software sector grew at a rate of 13.54 percent in 2015. The application of data quality tools amongst enterprise organizations is on the rise, and is vital to enabling Data Analytics stakeholders deliver business value. Given the scale and complexity of the data landscape across organizations of all types and sizes, tools to assist in quality automation continue to attract widespread interest.

Gartner provides a market definition: “The tools provided by vendors in this market are used by organizations for both internal deployment in their IT infrastructure and as cloud deployments such as SaaS. They use them to directly support various scenarios that require better data quality for business operations (such as transactional processing, master data management [MDM], big data, business intelligence [BI] and analytics), and to enable staff in data-quality-oriented roles, such as data stewards, to carry out data quality improvement work. Off-premises solutions, in the form of hosted data quality offerings, SaaS delivery models and cloud services, continue to evolve and slowly grow in popularity.”

Gartner’s market description has been updated for this year’s report to reflect new market dynamics driven by emerging technology trends and the continued maturation of data quality tools for enterprise-class business applications. The market comprises vendors that offer proprietary software solutions to address core functional requirements of the discipline. However, data quality tools also provide a wide range of related functional capabilities which are not unique to this sector but are required to execute the core functions of data quality assurance, or for more niche applications.

gartner-mq-for-emm-2015-1-638The 2016 Gartner Magic Quadrant for Data Quality Tools:

  • Complete enterprise market overview from leading researchers
    • Magic Quadrant graphic for quick and easy vendor comparison
  • Strengths and weaknesses of the top integration tools
  • Expert analyst recommendations
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Informatica has pulled ahead of IBM as the clear-cut top dog in this software sector, though the latter retains a strong position and should continue to challenge for market supremacy in the years ahead. SAP and SAS continue to duke it out for the third-highest spot in the leaders bracket, and though SAS improved a tick in the ability to execute metric, SAP remains the 2016 victor in the ongoing battle between three-letter acronymed mega-vendors. While Trillium Software’s positioning on the grid is the same as it was last year, the vendor’s future is now in a state of flux after Syncsort signed a definitive agreement to acquire them for $112 million.

Oracle and Information Builders certainly stayed on theme, as neither solution provider showed any notable movement in the leader’s column, though both retained their standing. Both companies are toeing their respective lines and are in danger of a downgraded standing in 2017 as Gartner continues to redefine the metrics that make up the evolving data quality market. However, IBM continues to invest in product innovations and Information Builders touts a good understanding of data quality and adjacent markets.

Gartner’s market challengers column looks awfully similar to last year’s, as the same two providers call this sector home. Based in Stamford, Connecticut, Pitney Bowes has ambitions of broadening its global market reach through partner networks. Reference customers scored the company’s flagship data quality product, Spectrum, highly in visualization capabilities as it functionally supports location and spacial data enrichment requirements. Experian has a plethora of data quality tools that customers rate highly for support for business analysts and information stewards. In addition, Experian’s tools offer ease of implementation and fast time to value.

Talend was the only provider to take a noteworthy step forward in the visionaries bracket, as Gartner sees the vendor’s innovation and business model appealing. Talend launched its IPO on the NASDAQ in July and has introduced semantic discovery, data quality on Spark, and machine learning for record matching to wider sectors of the market through effective packaging and reasonable pricing. Ataccama and Neopost showed minor regression in the ability to execute metric while MIOsoft’s standing remained unchanged. However, MIOsoft offers an innovative, forward-thinking product for emerging use cases, providing contextual data quality technology using graph analytics and machine learning for Big Data and IoT.

RedPoint, Innovative Systems, Uniserv and BackOffice Associates populate the niche players quadrant for the second year in a row, with three of the providers showing no noticeable change in standing. The only exception is RedPoint, who showed a small improvement in Gartner’s ability to execute metric. Now within a stone’s throw of becoming a market challenger, RedPoint offers excellent technical support, professional services and overall capabilities with respect to requirements, with reference customers citing the vendor as providing high value for the money.

The 2016 Magic Quadrant is made up of the same 17 providers as last year’s report, with the exception of DataMentors, who was dropped because they no longer meet the criteria for inclusion. Data quality tools providers are expanding with increased activity in the market, both in a proprietary sense and in partnerships with other solutions that offer enterprise Data Integration tools. Gartner believes that businesses should take these trends into account in their strategies for selecting and deploying data quality tools in order to optimize investments in this sector.

Read Gartner’s Magic Quadrant.

Timothy King
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Timothy King

Editor, Data and Analytics at Solutions Review
Timothy is an enterprise technology writer and analyst at Solutions Review, covering Business Intelligence and Data Analytics, Data Integration and Data Management. He holds a Bachelor of Arts Degree in History from the University of Massachusetts Lowell. Timothy believes that data can allow us predict things about our future, just as history has aided in the uncovering of our past.
Timothy King
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