A 15-Time Leader in the 2022 Gartner® Magic Quadrant™ for Data Quality Solutions

Last Published: Oct 11, 2023 |
Donal Dunne
Donal Dunne

Associate Director, Product Marketing

I am delighted to say that Gartner has named Informatica a Leader in its 2022 Gartner® Magic Quadrant™ for Data Quality Solutions1 for the fifteenth time in a row. By any standard for us, this is a remarkable recognition and magnificent testament to our focus on customer success and product innovation. We believe this recognition by Gartner underscores how Informatica is committed to making our customers truly data-driven enterprises, and how we help them create exponential value from trusted data.

Digital Transformation Is Powered by Data Quality

Many of the benefits expected from today’s digital transformation initiatives — in particular, analytics and machine learning — are achievable when you can look beyond any one data store or departmental silo. Meaning that when you combine many disparate internal and external data sources of varying standards and quality, you can generate insights you couldn’t get from siloed views. It’s about applying machine learning algorithms to recognize behavioral patterns, to identify consumer interests and to provide recommendations. It allows you to identify risks faster and take steps to increase your organizational resilience. And that is why data quality is so critical to delivering successful digital transformation and analytic initiatives.

Unfortunately, the companies that struggle to deliver data that is fit for business purpose are often the same ones that constrain their data quality efforts.

  • They see data quality as a cost sink, instead of a strategic contributor
  • They apply it in silos, instead of enterprise-wide
  • They bring it in late to fix costly problems, instead of early to prevent them
  • They manage data quality with manual processes instead of using the latest advances in automation and AI
  • They assume their analytics, CRM, ERP or other applications will take care of data quality

As a result, these companies do not realize their expected benefits from their digital transformation and modernization initiatives. However, the good news is that we are seeing a huge resurgence of interest in data quality as organizations realize the value of their data as a competitive differentiator.

Back to the Future? Behind the Resurgence in Data Quality

When predicting the future, it is always helpful to look back while also considering current and emerging trends. The alleged “demise” of data quality is a case in point. Many software companies and analysts have claimed that existing applications for example data warehousing or AI/ML would replace the need for a dedicated data quality solution. Yet here we are — 16 years after Gartner published their first Magic Quadrant for Data Quality Solutions — still talking about and evaluating data quality solutions.

Consider how organizations, as they rationalize and consolidate applications while they move workloads to the cloud, experience the same sort of challenges and impact of poor data quality as before. And, as these modernization initiatives continue to grow in size and scope, there is a renewed focus on the quality of the data. After, all why move dirty data to a new application and compromise future decisions based on bad data?

And although there are similarities between past and current needs, some things have changed. One key difference is the need for a modern, cloud-native data quality solution. A solution based on the guiding principles of simplicity, automation and scalability. What drives this need is increased data complexity, along with a growing community of data consumers who want to engage and innovate with data they can trust.

A Commitment to Continuous Innovation

Let me share some of the innovations we have delivered across these guiding principles. We believe these principles play an important role helping customers become more data-driven and allow them to make better decisions and create greater value from data.

Simplicity - Simple and easy data access, processing and consumption for all data consumers

  • Business technologists can simply analyze data with a profiling wizard experience and intelligent insights
  • A low-code / no-code user interface that makes it quick and easy for non-technical users and technical users to design and deploy data quality checks and remediations

Automation - 10X to 100X greater productivity with CLAIRE-powered automation

  • Data Quality insights for automatic detection of anomalies and predictive data quality rule recommendations
  • Data Quality automation and dashboards through deep governance integrations

Scalability - Cloud first, cloud-native data management at enterprise scale

  • Scaling with optimized data management engine lets you process data where and how you want
  • Build and maintain high-performance data pipelines with elastic infrastructure

Data quality is part of the industry’s first and only Intelligent Data Management Cloud (IDMC), our single, comprehensive, cloud-native data integration platform. Powered by CLAIRE, our AI-powered metadata engine, customers can leverage all the capabilities and innovations of IDMC for data ingestion and streaming, data integration, data catalog and data governance, while also being able to embed data quality into these processes to control costs, increase productivity and accelerate time to market.

As I’ve already mentioned, it’s important to look at past as well as current trends to deliver what customers need now and in the future. An example of this is the concept of Data Observability.2 Data observability, which Gartner recently identified as a key emerging technology, provides insights into the health and performance of the data infrastructure, data pipeline and the data itself.3 Some vendors take a narrow view and look at just one aspect. Informatica provides the most appropriate lens to observe the infrastructure, data pipeline and data, while also observing how the data is consumed and protected as well as how it complies with policies and regulations.

Finally, we believe that our customers are fundamental to our success in the Gartner Magic Quadrant for Data Quality Solutions. New York LifeCommunity Health ChoiceCNP Assurances and Celcom are all great examples of organizations that understand the value of high quality, trusted data and how it can transform their businesses.

Learn More

Discover how you can put our strengths and cautions to work for you. Download your complimentary copy of the 2022 Gartner® Magic Quadrant™ for Data Quality Solutions now.



1Gartner Magic Quadrant for Data Quality Solutions, Authors, Ankush Jain, Melody Chein, November 1, 2022
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 consisst 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.
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2Press Release, Gartner Identifies Key Emerging Technologies Expanding Immersive Experiences, Accelerating AI Automation and Optimizing Technologist Delivery, Meghan Rimol, August 10, 2022 https://www.gartner.com/en/newsroom/press-releases/2022-08-10-gartner-identifies-key-emerging-technologies-expanding-immersive-experiences-accelerating-ai-automation-and-optimizing-technologist-delivery

3Gartner, Hype Cycle for Emerging Technologies, 2022, Melissa Davis, Gary Olliffe, 25 July 2022.

First Published: Nov 04, 2022