Informatica Named a Gartner® Magic Quadrant™ Leader—For The 14th Time

Informatica once again named a Leader in the 2021 Gartner® Magic Quadrant™ for Data Quality Solutions

Last Published: Oct 07, 2021 |
Donal Dunne
Donal Dunne

Associate Director, Product Marketing

Informatica once again named a Leader in the 2021 Gartner® Magic Quadrant™ for Data Quality Solutions

Fourteen years is an eternity in technology—and for much of that time, I have heard commentators claim that new and emerging technologies would reduce the need for data quality solutions. For example, Big Data was supposed to eliminate the need for data quality. The assumption here was that because there was so much data, that any data quality problems would have a minimal impact. The same talking heads later claimed that AI would solve data quality problems automatically and AI models would perform just as well with dirty data. However, in both of these cases it has become clear that without clean, trusted data, these initiatives fail to deliver. In a paper published by Google Research (1), they noted that “data quality carries an elevated significance in high-stakes AI due to its heightened downstream impact, impacting predictions like cancer detection, wildlife poaching, and loan allocations.”

While I have been working with data quality solutions since 2003, I think it would help those of you who are new to data quality to provide a brief definition.

Gartner defines data quality as “the processes and technologies for identifying, understanding, and correcting flaws in data that support effective data and analytics governance across operational business processes and decision making. The packaged solutions available include a range of critical functions, such as profiling, parsing, standardization, cleansing, matching, monitoring, rule creation and analytics, as well as built-in workflow, knowledge bases and collaboration.”

So here in 2021, data quality continues to gain importance for organizations that are transforming their business and operations that support such initiatives as customer experience, data and analytics governance, operational efficiencies, predictive analytics, application modernization, and business resilience. This is why the Gartner® Magic Quadrant™ for Data Quality Solutions (2) is such a highly anticipated and valued report. We understand the formulation of the report comes from a range of sources including:

  • Request for Information that considers functional capabilities, customer base, pricing models, financial status, and other quantitative attributes
  • Vendor briefings that cover product strategy and innovation, market understanding
  • Customer surveys that capture how the vendors clients are using the product, their overall experience, and the value derived from the data quality solution
  • Gartner direct client inquiries that provide insights about use cases, business and technical strategies and priorities, and vendor experiences captured during these inquiries with their clients

With that in mind, here are the key highlights for me this year:

  • Recognition from our customers for the ongoing innovations we are making in data quality while providing a clear path to the cloud as their needs change
  • An integrated end-to-end solution that has the breadth and depth of functionality to enable our customers to handle the simplest use cases to the most complex across multiple data domains, sources, and landscapes
  • An Intelligent Data Management Cloud™ platform that has data quality integrated with all the data management processes – And available as and when needed through consumption-based pricing

Here at Informatica, we are proud of what we have achieved with Informatica Data Quality over the last number of years. Our consistent track record of successful deployments is the key strength of Informatica. We believe our placement as a Leader validates our ability to deliver the next generation Data Quality experience for organizations. As a result, over the past 12 months we have seen tremendous growth and adoption of our Cloud Data Quality offering as companies look for vendors that deliver data quality solutions natively in the cloud.

One more key point: We feel maintaining a Leadership position in the Gartner Magic Quadrant for Data Quality Solutions for 14 years would not be possible without our loyal customers, who have inspired and challenged us to deliver new innovations that deliver value to their organizations. With Informatica Data Quality solutions, companies like Celcom are accelerating 5G innovations, CNP Assurances are reducing the risk of cybercrime, Eli Lilly is improving analyst and engineering productivity, Telus is connecting with 14 million customers in a personal way or CVS, who achieved a 95% reduction in manual effort to analyze data.

We hope that you’ll take a moment and download your complimentary copy of this report.


(1) Nithya Sambasivan, Shivani Kapania, Hannah Highfill, Diana Akrong, Praveen Paritosh, Lora Aroyo for Google Research (2021), “Everyone wants to do the model work, not the data work”: Data Cascades in High-Stakes AI

(2) Gartner Magic Quadrant for Data Quality Solutions, Melody Chien, and Ankush Jain, September 29, 2021
This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Informatica.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
GARTNER and Magic Quadrant are registered trademarks and service marks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

First Published: Oct 04, 2021