Around 10 years ago, Master Data Management was used to manage older data technologies. It employed the familiar methods of extraction, transformation and load-based data movement, which had its downside. As the digital transformation ramped up and as data began pouring into the enterprise, the technology became outdated.

During Informatica World in San Francisco, California, MDM made a comeback, as the company used the principles of the old technology and discovered a new use for artificial intelligence.

“A lot of early adopters were there [at the beginning]. And as is usual with a lot of early adopters, there was a quick dip into the cycle of disillusionment. What you’ve seen over the last couple of years is the resurgence about MDM and looking at MDM as being a force of disruption for the digital transformation,” said Suresh Menon (pictured), senior vice president and general manager, Information Quality Solutions, at Informatica LLC.

Menon described the new use for MDM with John Furrier (@furrier) and Peter Burris (@plburris), co-hosts of theCUBE, SiliconANGLE Media’s mobile live streaming studio, during Informatica World. (* Disclosure below.)

Rethinking older technology to enhance the digital transformation

There are two groups of users to think about when applying MDM, according to Menon. The first thoughts are about managing business critical entities, such as customers and products. The other constituency is employees, channels and suppliers, along with their location. These parties all play a significant role in every organization’s data collection and storage, he stated.

“Master data management is about making sure that you have the most trusted, authoritative and consistent data about these entities, which can then fuel the rest of your enterprise … with a minimal amount of risk, and also to make sure that your products are being described and syndicated in the most efficient manner,” Menon said.

Burris, who has been analyzing the new uses for MDM commented that he pondered if applying it to this problem would work. He feels it seems to fit quite nicely now.

Menon explained that there is a re-definition of the technology. If you look at MDM from the old vantage point, it is hard to imagine it working with innovations such as Internet of Things data, social network data and interaction data that is not structured but moves in real time.

“This is really the third phase of MDM — going from batch analytics, fueling old real-time applications, whether it was marketing, customer service and so on; and now, providing the context that is necessary to connect dots across the billions and billions of data that is coming in, being able to provide that insight, and the outcome that organizations are hoping to achieve by bringing all this together,” Menon said.

The MDM of today is a combination of both the gathering insights from metadata and then applying AI through machine learning, according to Menon. Using well-curated data from MDM and blending it with AI makes it possible to detect information from those rapid data streams, infer the relationships and allow relationship exploration.

Automation and reacting to internal and external organizational changes is one benefit; the other is the ability for machines to learn from previous interactions, making MDM self-configuring. Menon also discussed stewardship and how MDM combined with machine learning is the only way to manage the data explosion and provide users access to the data they need.

“The third part of where MDM increases its relevance is … what’s next. What’s next is really about not just putting that data in the hands of the user or inside of a consuming application, but instead recommending what that application or user needs to do with that data” Menon concluded.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s independent editorial coverage of Informatica World 2017. (* Disclosure: TheCUBE is a paid media partner for Informatica World. Neither Informatica Corp. nor other sponsors have editorial influence on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE