Move on out, data lake. Companies no longer have patience for huge vats of random, unorganized data. Today, they want usable, analytics-ready data at their fingertips. It’s a tall order, but technologies like artificial intelligence and application program interfaces are making it a reality. They’re important building blocks of what some are calling the “data platform” — a more practical, high-yield improvement on the data lake.

The purpose of a data platform is to eliminate the need to execute data projects in a piecemeal fashion, according to Amit Walia (pictured), president of products and marketing at Informatica LLC. A data lake and some unwieldy analytics software do not make up a data platform. With just those elements, a company will have to build out every data project slowly and painfully from the ground up. A data platform has effective elements already composed or at the ready for faster time to value.

“It has to be very modular and API driven,” Walia said. “Nobody wants to buy a monolithic platform. It’s going to be like a Lego block — it builds by itself,” Walia said. “Platform is very critical to accelerate your … data-driven transformational journeys, but the platform better be API driven, microservices based, very nimble … not a precursor to value creation, but creates value as you go along.”

Walia spoke with John Furrier (@furrier), host theCUBE, SiliconANGLE Media’s mobile livestreaming studio, at theCUBE’s studio in Palo Alto, California. In a separate interview, Furrier spoke with Ronen Schwartz, senior vice president and general manager of data integration and cloud integration at Informatica. They discussed how a well-constructed data platform can speed up time to value for data projects (see the full interviews with transcript here and here.) (* Disclosure below.)

AI for data flood relief

The data platform is versatile and ready for use cases from the get-go — not after years of tedious composing, according to Walia. AI helps quickly sort large sets of data into useful categories that companies can build on.

“For example, you have a data-integration platform. You can do data quality on top; you can do master data management on top; you can provide governance; you can provide privacy; you can do cataloging. It all builds,” Walia stated. 

The increasing volume of data is a blessing and a curse to companies hoping to drive insights and profits from it. AI-assisted data management is crucial for navigating it Any integrated data platform should leverage AI to quickly parse data and help companies make decisions, according to Walia. Informatica builds AI and machine learning into its products and data platform. Claire, the company’s metadata-driven AI tool, is embedded on its Intelligent Data Platform.

Watch the complete video interview with Amit Walia below:

APIs make data dance across enterprise

APIs are also extremely handy tools on a data platform for quickly surfacing value. Informatica has partnered with Google Cloud Platform on a hybrid API offering. It allows any user of Informatica’s integration platform as a service to publish APIs to Google’s Apigee cross-cloud API-management platform, and vice versa, according to Schwartz.

“Everything that you build in Informatica cloud is basically automatically an API inside Apigee,” Schwartz said. “It actually means that you can do more things with the data in an easier way. And, also, it means that you can actually share it with more users within the enterprise.”  

It allows users to complete various data projects with less labor, he added. They can also take a data or business process, automate it, and turn it into an API. Exposing this process as an API allows multiple other services, capabilities, etc., to very easily leverage it.

“They’re publishing it as an API in one click. At that stage, anybody anywhere can very, very easily consume that API and basically use this process again and again,” Schwartz stated. This can make processes more consistent and scalable, as well as help companies develop apps faster.

“We’re basically making the data available in the best way for their offering, and that kind of allows them to focus on their innovation rather than how do they work in the different places,” Schwartz concluded. 

Watch the complete video interview with Ronen Schwartz below, and be sure to check out more of SiliconANGLE’s and theCUBE’s CUBE Conversations. (* Disclosure: Informatica LLC sponsored this segment of theCUBE. Neither Informatica nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE