HPE to Buy Big Data Infrastructure Startup BlueData

Hewlett Packard Enterprise is buying BlueData, a startup whose software makes deploying infrastructure for big data and machine learning easier for enterprises•HPE’s goal is to create a turnkey big data solution customers can use in their own data centers, in the cloud, or in hybrid scenarios•While promising, big data projects have a notoriously high failure rate inside enterprises, often because of the level of technical complexity involved

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HPE Synergy racks in a data center
HPE Synergy racks in a data centerHPE

Hewlett Packard Enterprise is buying BlueData, a startup built by former VMware engineers to make the way companies deploy infrastructure for data-intensive analytics and machine learning projects as easy as spinning up virtual servers in a public cloud.

HPE expects to close the deal (whose terms it did not disclose) by the end of January and plans to integrate BlueData’s software platform with its data center hardware and software solutions. The goal is to eventually sell a turnkey big data solution customers can use in their own data centers, in the cloud, or in hybrid scenarios that mix both.

In its six years of existence, Santa Clara, California-based BlueData has convinced numerous big-name enterprises to buy its technology. Its customer references include the likes of Citi, GlaxoSmithKline, Nasdaq, and Macy’s. One of its earliest and biggest investors has been Intel.

Big data analytics and the more recent rise of machine learning hold the promise of a whole new, data-driven way of doing business for companies. Enterprises have access to tons of data, be it historical data from internal operations, customer-behavior data, customer operational data, or other kinds. If they can effectively analyze all that data, goes the thinking, new efficiencies or entire new sources of revenue may emerge from the analysis.

While promising, however, big data projects have a notoriously high failure rate inside enterprises, often because of the level of technical complexity involved. That’s why a “turnkey solution for big data and machine learning may seem attractive to an enterprise IT exec.

“More than 50 percent of big data projects fail, and fail miserably,” Philippe Poutonnet, Google Cloud’s global product marketing lead, was quoted as saying in last year’s study by MIT Technology Review and Google. “Businesses are spending a lot of time with the data-gathering and data-preparation phases, as well as trying to figure out the data architecture, and they don’t have time to play with the data itself.”

In his blog post announcing the acquisition, general manager of HPE’s storage and big data group Milan Shetti cited an IDC prediction that by 2022 the global market for AI, machine learning, and big data will be worth about $160 billion. But he also cited a Gartner prediction that even two years from now half of organizations still won’t have enough AI and data literacy skills to get much business value out of their data.

The original idea behind BlueData was to give enterprises the ability to deploy popular big data frameworks – things like Hadoop, Spark, and – on-demand, without the headaches of integrating disparate data sources and making sure the environment is secure and compliant, the startup’s co-founder and CEO Kumar Sreekanti, wrote in a blog post. With the rise of machine learning, frameworks like TensorFlow and H2O were added to the mix.

Once the acquisition is closed, Kumar expects BlueData to leverage HPE’s brand, technology portfolio, global reach, and enterprise customer base to accelerate technological development and growth.

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About the Authors

Yevgeniy Sverdlik

Former editor in chief of Data Center Knowledge.

Data Center Knowledge

Data Center Knowledge, a sister site to ITPro Today, is a leading online source of daily news and analysis about the data center industry. Areas of coverage include power and cooling technology, processor and server architecture, networks, storage, the colocation industry, data center company stocks, cloud, the modern hyper-scale data center space, edge computing, infrastructure for machine learning, and virtual and augmented reality. Each month, hundreds of thousands of data center professionals (C-level, business, IT and facilities decision-makers) turn to DCK to help them develop data center strategies and/or design, build and manage world-class data centers. These buyers and decision-makers rely on DCK as a trusted source of breaking news and expertise on these specialized facilities.

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