Companies are amassing data — structured, semi-structured and unstructured — at a rapid pace. Vendors are hard pressed to keep up, as these vats of disparate data aren’t easy to make sense of. It takes a complementary set of intelligent tools to punt complex tasks back and forth to score the final, golden, insights, according to Rahul Pathak (pictured), general manager of Amazon EMR, Athena, RDS for Oracle, RDS for SQL Server, and AWS Blockchain Templates at Amazon Web Services Inc.

As that mouthful of a title suggests, Amazon is churning out a lot of tools to operate on these ginormous data lakes.

“We’re coming from a world where customers had to decide what data they could keep, because their systems were expensive,” Pathak said. “Now we’re moving to a world of data lakes where storage and analytics are much lower cost, and so customers don’t have to make decisions about what data to throw away — they can keep it all and then decide what’s valuable later.”

That doesn’t mean such decisions will be made in a snap. A number of tools that leverage machine learning, artificial intelligence, and serverless computing can loosen the brain squeeze for analysts, according to Pathak.

Pathak spoke with Dave Vellante (@dvellante) and John Walls (@JohnWalls21), co-hosts of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, during the Inforum event in Washington, D.C. They discussed AWS’ evolving portfolio of data analytics tools and how both enterprise and software-vendor customers are using them. (* Disclosure below.)

Covering all databases

Three tools that help wade through data lakes for insights are Amazon Athena — a serverless SQL service for S3 object storage that lets any analyst log on, get an SQL prompt, and run a query.

Amazon Glue is for cataloging data in databases and getting data from raw form into an efficient form for query. Elastic MapReduce is for arbitrary analytics using open-source technologies.

“These things are all very much complementary to each other,” Pathak said, noting how they cover all the territory from structured to semi-structured to unstructured data.

These tools can help enterprises monetize data, and they can be baked into new products or services. For example, Infor Inc. builds cloud-based enterprise applications for specific verticals on top of Amazon services like these, Pathak concluded.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the Inforum event. (* Disclosure: TheCUBE is a paid media partner for Inforum 2018. Neither Infor Inc., the event sponsor, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE