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Informatica Adds GreenBay for AI-driven Analytics Boost

Less than 12 months after Informatica announced that it was the sole investor in GreenBay Technologies Inc., Informatica has announced its acquisition of GreenBay, effective 17 August 2020. GreenBay’s tech will become embedded into Informatica’s CLAIRE engine, beginning with the Intelligent Data Platform Fall 2020 release.

GreenBay develops and owns some cool data management IP, blending machine learning with big data analytics. Its AI-enabled CloudMatcher allows analysts and data scientists to match data accurately with sources. This is a capability that seems like an obvious need, but is intrinsically challenging to accomplish. Such capabilities will only become more valuable as understanding, describing, and aligning data with business all become more complex.

Because there is a massive market opportunity, we see a more vendors pushing forward on similar types of capabilities. All have a primary goal of reducing data analyst/data scientist “scut work” (and associated costs) while improving outcomes. Most combine AI, ML and RPA to varying extents. Informatica’s integration of GreenBay tech into the CLAIRE engine and cloud platform should provide a competitive leg up. That said, there is no such thing as a sustainable technological advantage in most markets.

Platform Integration Is Key

Properly integrated into its CLAIRE engine and Intelligent Data Platform, GreenBay should fill a competitive need for Informatica. As my Analyst Syndicate colleague Tom Austin noted in a discussion on this acquisition: “The ability to automatically identify and tag new or revised incoming data streams is a dream most IT people have when they’re confronted with a growing, vast federation of disparate data sources, especially where no one really knows how to clean all of it up and properly align, tag, tie to knowledge graphs, and so on.”

The acquisition follows and complements Informatica’s July 2020 acquisition of Compact Solutions. Compact’s MetaDex software leverages metadata to enable and provide data governance – another increasingly valuable MDM capability in the IoT era. Both acquisitions enable significant reduction in labor, time, and errors in managing and analyzing large volumes of diverse data.

A third, similarly complementary relationship with Databricks, announced in May 2019, introduced product integrations between the two companies’ offerings to scale, accelerate, and govern big data pipelines using AI and machine learning techniques for data discovery and end-to-end data lineage visibility. It remains to be seen how, or if, this will be integrated with the Compact MetaDex and GreenBay CloudMatcher capabilities. Given current market trends, it will be surprising if it is not.






The views and opinions in this analysis are my own and do not represent positions or opinions of The Analyst Syndicate. Read more on the Disclosure Policy.