A New World for Data Integration and Metadata Management

The 2016 Gartner Magic Quadrants for Data Integration Tools and Metadata Management Solutions are out, and Informatica is a leader in both of them—appearing highest on the axis for “ability to execute” and farthest to the right on the axis for “completeness of vision.” I highly recommend that you check them out, not just to see how various solutions compare, but for Gartner’s insight into how these two markets are evolving.

Rising complexity in the data integration market

With data driving so many important business decisions, enterprises are interested not only in data integration products themselves, but also how those products work with data quality, cloud, big data, master data management, metadata management, etc.

According to Gartner in the 2016 Magic Quadrant for Data Integration Tools: “The need for rapid data integration requires tools and platforms with increased ability to read, analyze, and react to local and foreign metadata in a dynamic model with distributed processing capabilities.”

We believe that for most organizations, their data management tools must work with:

  • On-premise and cloud data
  • “Regular data” and big data
  • Structured data and unstructured data
  • IT-managed data and self-service data
  • Batch data and streaming data
  • Centrally managed data and distributed data management

Informatica is well-positioned in the Leaders quadrant of the 2016 Gartner Magic Quadrant for Data Integration Tools.

Gartner DI MQ 2016Informatica believes that with the growth in data volume and variety on one hand, and the acceleration of analytics and application modernization on the other, data management is getting much more complex. It’s been clear for some time that approaches like hand-coding and “tool-of-choice” will not scale to enterprise use.  The growing complexity of the data environment requires an integrated data management platform for organization to deliver data at the speed required by the business.

Greater demands on metadata management

This year, Gartner introduces its first Magic Quadrant for Metadata Management Solutions. I’ve wanted to see an MQ address this topic for years, and I think its debut this year reflects a growing awareness that metadata management is critical not only for the context it brings to data, but also to address the challenge of accelerating data integration developer productivity.

Metadata management is increasingly being seen not as a standalone practice, but as a fundamental part of a data management platform.

Informatica is well-positioned in the Leaders quadrant of the 2016 Gartner Magic Quadrant for Metadata Management Solutions.

Gartner MM MQ 2016In this new MQ you can see the focus on the breadth of metadata management across all phases of data management, all styles of data delivery, and all types of data. We believe this is because metadata management is critical for:

  • Visibility into the flow of data from source to target.
  • Audit-ability, to see who changed what data, how and when.
  • Context, so that business users can add and manage business context to data for deeper understanding.
  • Governance of the rules and policies attached to data to manage its use and meaning, its authorized users, and other policies around security, data quality, and more.

But from a more strategic point of view, metadata will be critical to adding intelligence to the practice of data management. The platform can increasingly apply intelligence to improve productivity by understanding how data is being used, processed, and delivered by users. Some examples include:

  • Intelligent recommendations; such as how to join data sets, or related data sets that might be of interest.
  • Intelligent patterns; how somebody else has processed a data set, so that their work might be re-used by somebody who did not even know that this work had already been done.
  • Automation; after seeing patterns of activity over time, the data management platform will be able to intelligently do things automatically.

The bottom line for me is that data management is becoming more and more of a multi-capability process or a platform. And if this platform is to deliver value to the business, it increasingly needs to apply intelligence and machine learning to provide recommendations and automation that will drive productivity. So, really the Magic Quadrants for data integration and metadata management go hand-in-hand.

In the end, it all comes down to the ability of IT to deliver the data that the business needs at the quality level and in the timeframe that the business requires.  As the complexity of data management increases, the importance of a data management platform and metadata increase as well.

To understand Gartner’s take on these changing worlds, and the solutions leading the way, download the Gartner Magic Quadrant for Data Integration Tools and the Gartner Magic Quadrant for Metadata Management Solutions.

Gartner, Magic Quadrant for Data Integration Tools, Mark A. Beyer, Eric Thoo, Ehtisham Zaidi, Rick Greenwald, 08 August 2016.
Gartner, Magic Quadrant for Metadata Management Solutions, Guido De Simoni, Roxane Edjlali, 15 August 2016

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