Can new metadata and machine learning salvage data swamps?

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Once touted data lakes have deteriorated into data swamps, but a slew of new technologies could salvage the data inside with help from machine learning.

“You’re starting to see solutions taking advantage of that data lake,” said John Furrier (@furrier), co-host of theCUBE, SiliconANGLE Media’s mobile live streaming studio, during BigData SV 2017 in San Jose, CA. (*Disclosure below.)

“You’re starting to see technologies taking streaming and batch and pulling them together,” he said, noting new products from Informatica LLC, Zaloni Inc. and others.

George Gilbert (@ggilbert41), theCUBE co-host, agreed that these new technologies might breathe life into data swamps.

“It’s really about the meta data. In other words, it’s the data about what’s in the data lake,” he said. “It’s important because it tells us how to navigate what’s in the data lake and it helps clean up the swamp.”

Then data scientists put machine learning to work on that data and build much better applications from there, Gilbert explained.

Compute jump-starts machine learning

But is machine learning ready? Furrier said that artificial intelligence and machine learning have been around for years but were typically more useful to sci-fi writers than software developers. However, the jump in compute power underway is going to change that, he said.

“You have now unlimited compute power, potentially with cloud computing. That power now can actually run software models that could not have bee run even five years ago,” Furrier stated.

Both CPU makers and the open-source community hear the demand for scalable big data analytics, and they understand that machine learning is critical. Furrier noted Intel’s work on its new Xeon CPUs.

“They’re optimizing their Xeon processors to work with TensorFlow [a Google machine learning system] in a way that’s going to increase the scalability,” he said.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of BigData SV 2017. (*Disclosure: Some segments on SiliconANGLE Media’s theCUBE are sponsored. Sponsors have no editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE