BOSTON—Hewlett Packard Enterprise is continuing to expand its capabilities in big data analytics as part of what officials have called a pivot in the way the company is approaching the fast-growing space.
At the tech vendor’s Big Data Conference 2016 here Aug. 30, HPE officials unveiled enhancements to the Haven OnDemand machine learning platform it launched in March that are aimed at making it easier for developers and data scientists to build applications that can draw insight and information from the huge amounts of data being generated by their businesses.
At the same time, HPE also unveiled the latest version of its Vertica analytics software that enables users to analyze the data more quickly—regardless of where it’s sitting, whether on-premises, in the cloud or in a Hadoop data lake.
All of the new and enhanced offerings are part of the larger vision at HPE that businesses of all sizes need to have the speed, scale and flexibility to access and analyze all their structured and unstructured data wherever it resides and with whatever tools they need. The company is changing how it looks at and addresses the challenge of data analytics, according to Jeff Veis, vice president of marketing for the Big Data Business Unit inside HPE Software. It’s shifting from an inside-out point of view—where the focus is primarily on its core software offerings—to more of an outside-in look, where it starts with the customer’s data challenges and moves from there into software features.
“Big data analytics is not only a big company challenge,” Veis told eWEEK. “It’s hitting everybody.”
At the show, Veis and other company officials talked about what customers are looking for from HPE in terms of helping them better collect, store, analyze and act on their data, from performance and scale to flexibility, choice and simplicity. The new and enhanced offerings are designed to address many of those demands.
HPE is bolstering its Haven OnDemand machine learning-as-a-service platform with Combinations, a way for developers and businesses to more easily take advantage of the 75 or so machine learning APIs in the platform to build their data-rich applications. Currently, developers using two or more APIs to build an application to access and analyze their data have to do a lot the coding themselves, a time-consuming and at times frustrating process, according to Fernando Lucini, CTO of HPE Software’s Big Data Platform unit.
For the past two years, HPE engineers have been developing what is now Haven OnDemand Combinations, a cloud-based offering hosted on Microsoft’s Azure cloud platform that gives developers an easy and intuitive way of stitching these multiple APIs together and creating a single API call. They essentially can choose the APIs they want to apply and the order in which to apply them, and the Combinations technology pulls them together, eliminating the need for developers to do any coding and speeding up the application development process and improving data throughput speeds.
The combinations of APIs can be saved and reused by the developers or others within the business. In addition, developers can cut and paste the code directly into their application development projects.
“It simplifies people’s lives substantially,” Lucini told eWEEK.
In addition, HPE offers a catalog of pre-built machine learning API combinations, and also is planning to create a marketplace for applications that developers build based on the API combinations. Developers can use a Freemium account to build new combinations for prototypes at no charge. The commercial version will give customers increased quotas and enterprise-grade service-level assurance, officials said.
HPE Expands Machine Learning Capabilities for Big Data Analytics
The company already has 18,000 developers working with Haven OnDemand—part of HPE’s larger effort to provide machine learning capabilities to a wider group of users—and Combinations is available now for early access, with general availability coming in the fourth quarter.
Key new features in Vertica 8—which had been code-named Frontloader—include support for more cloud platforms, in-database capabilities and enhanced capabilities to access and analyze data residing in multiple places. The features help address customer demands for greater openness and flexibility when it comes to the huge amounts of data being generated and stored, according to Colin Mahony, senior vice president and general manager of HPE Software’s Big Data Platform business.
“When it comes to choice, customers want to run [their analytics workloads] on a lot of different platforms,” Mahony said at the show.
That includes a choice of cloud platforms, according to officials. Vertica, which already supports Amazon Web Services (AWS), can now work with Azure, a move that not only increases the options for customers but also builds on a strategic agreement HPE and Microsoft forged late last year to work together on hybrid cloud solutions.
In addition, through Vertica 8—which will be released in the fourth quarter—users can now more easily and securely access and analyze data that resides in Hadoop data lakes. Until now, businesses could put Vertica into Hadoop, which enabled them to analyze that data with Hadoop-like economics but at a cost of performance, Veis said. Or they could use Vertica to access the data, but that meant that the data would have to be copied and moved into Vertica. Now, with new Parquet and ORC readers, customers can use Vertica 8 on data residing in the Hadoop data lake without having to copy and move the data.
“We’re bringing the analytics to the data rather than bringing the data to the analytics,” Veis said.
In-database machine learning algorithms enable developers to natively create and deploy R-based machine learning models directly in Vertica for large data sets, and a new optimized Apache Spark adapter offers fast data exchange between Vertica and Spark systems.
In addition, core data movement and orchestration improvements can result in 700 percent faster data loading for hundreds of thousands of columns, officials said.