With just five weeks until full enforcement, the pending laws of the European Union’s General Data Protection Regulation may have been the focus for the keynote at DataWorks Summit in Berlin, but the broader story of data governance spotlights the challenges facing event host Hortonworks Inc. as it evolves big data business beyond Apache Hadoop’s outdated methods of managing unstructured data.

“Hadoop has been around for a number of years now, but in many ways it’s been superseded in the agendas and priorities of enterprises that are building applications from data by some newer, primarily open-source technologies, such as Apache Spark and Tensorflow, for building deep learning and so forth,” said James Kobielus (@jameskobielus), lead analyst for data science, deep learning and application development at Wikibon and SiliconANGLE.

As host of theCUBE’s on-site coverage of DataWorks Summit, Kobelius kicked off today’s broadcast with a brief recap of the keynote and how Hortonworks’ announcements fit into current market trends for artificial intelligence and machine learning. (* Disclosure below.)

The crux of data governance

Announced today, Hortonworks’ new Data Steward Studio is designed to secure and govern data across enterprise data lakes. The end goal is to allow users to spend more time actually analyzing the data rather than tracking it down from disparate hybrid cloud environments and cleaning it up for analysis. Automation is key to Data Steward Studio’s ability to eliminate redundancies in identifying the data sets needing special attention.

It’s one step toward differentiating its services from rivals like Cloudera Inc. and MapR Technologies Inc., two other companies spurred by the early promise of Hadoop. Despite 42 percent annual revenue growth since 2016 and solid earnings for fourth quarter 2017, Hadoop faces challenges beyond its immediate competitors. Large-scale cloud providers like Microsoft Azure and Amazon Web Services Inc. are baking in more analytics tools, threatening to marginalize Hortonworks’ specialized offerings.

Perhaps that’s why Hortonworks, which built a business on on-premises analytics, is leaning on a partner ecosystem entrenched in multi and public cloud computing, alongside AI technologies. To weather this market shift, Hortonworks is pushing further into deep learning technologies to support growing market demand for intelligent, streaming data at the edge of the computing network.

“Big data is critically important for modeling and building the AI needed to power the intelligence in endpoints. Not just self-driving cars but intelligent appliances, conversational user interfaces for mobile devices,” said Kobielus, citing Amazon Alexa and Apple Siri as familiar examples. “We’ll be looking at those trends as well, toward pushing more of that intelligence to the edge and the power of big data and data-driven algorithms like machine learning in driving those kinds of applications,” he furthered, laying out a framework for upcoming interviews with Hortonworks and key partners like IBM.

Supporting Hortonworks’ effort to deliver GDPR-ready services, IBM Corp.’s partnership enables a greater depth of data governance within enterprise computing environments, according to Kobielus.

“We’ll be asking Hortonworks and IBM to net out where they’re going with their partnership in terms of enabling a multilayer governance environment to enable this machine learning pipeline to be deployed as an operational capability into more organizations,” Kobielus concluded.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s independent editorial coverage of DataWorks Summit.(* Disclosure: TheCUBE is a paid media partner for the DataWorks Summit Berlin event. Hortonworks, the event sponsor, does not have editorial control over content on theCUBE or SiliconANGLE.)

Photo: DataWorks Summit via Twitter