Hortonworks has used its DataWorks Summit in Berlin, formerly known as the Hadoop Summit, to launch a data governance plug-in named Studio to its DataPlane platform, announced last year.
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The supplier, which began life in 2011, as one of the Hadoop distributors, alongside Cloudera and MapR, says DataPlane delivers data architecture as a service, with data governance baked in with Apache Atlas.
Scott Gnau, chief technology officer at Hortonworks, said at a press and analyst briefing at the summit: “DataPlane services should be thought of as a substrate on which applications will be built, like Studio.”
He said the supplier is now comprehensively at what he called a “3.0 stage”, where plain Hadoop distribution was 1.0 and, and 2.0 was about data flow, not merely data at rest. It named the most recent upgrade to its Hadoop DataFlow product HDF 3.0 in June 2017, with the addition of a “streaming analytics manager” tool.
“We are living in a world of ‘data entropy’, with connected mobile and IoT devices, the likes of search recommendations generating more data, but also raised expectations [of quality data delivery] among the public. We are about managing the lifecycle of data from point of origin to point of rest,” said Gnau.
However, none of the four customers who featured in the briefing – representing WorldPay, Hotels.com, the Orwell Group, and Klarna – said they were using any DataPlane services as yet.
The supplier said in a press statement that Data Steward Studio (DSS) is a “service that gives enterprises consistent security and governance for data assets across big data repositories”.
Analyst firm Forrester commented: “Increasing data volume is creating new challenges in integration, security, curation, administration and governance. Business users want real-time trusted data to make accurate business decisions, while technology management wants to simplify administration and lower costs.”
Hortonworks said its DSS can provide information stewards, data scientists, business analysts and with robust capabilities to find, curate, collaborate, secure and report data engineers on data.
Customers can get a comprehensive view of their data across data lakes that aggregates critical data assets, reducing the time it takes to understand key data aspects while reducing risk.
“Uncovering insights from diverse data types across multiple data lakes requires substantial amounts of effort to establish lineage, improve quality and eliminate redundancies across data assets,” added Gnau.
Meanwhile, the supplier also introduced updates to its Data Lifecycle Manager (DLM) product, which is said to allow “data to be encapsulated and copied seamlessly across the physical private storage and public cloud environments for full data mobility to enable the right workloads in the right environment for the right use case”.