As part of an effort to better integrate two of the major elements of its Big Data Platform, Hewlett-Packard today upgraded the HP Haven Big Data Enterprise and OnDemand Platforms.
At the core of that upgrade is the launch of an HP Haven Connector Framework Server that tightly couples the HP IDOL search platform with the analytics capabilities of the HP Vertica columnar database. The end result, says Jeff Veis, vice president of marketing for Big Data at HP, is a more symbiotic pairing of two Big Data technologies will enable organizations to more easily pull data from over 400 sources into the HP Vertica platform.
In addition to unveiling a more tightly integrated implementation of IDOL and Vertica at the Gartner Business Intelligence and Analytics Summit, HP added an HP Haven Knowledge Graphing Tool that makes it simpler to identify relationships between data sets and an update to HP Haven Speech-to-Text neural networks software that is now 75 percent more accurate across 20 different languages.
Finally, HP is adding HP Haven Targeted Query Response, which enables developers to refine and customize search results based on specific sets of criteria, and HP Haven IDOL Search Optimizer, which allows end users to more easily design and run search across a broad array of data types.
Ever since HP combined the IDOL search technology it gained with the acquisition of Autonomy with the Vertica database and a distribution of Hadoop to create Haven, HP has been working toward creating a highly integrated Big Data platform that makes it easier to use structured and unstructured data to drive composite analytics applications spanning structured and unstructured data.
Unlike other Big Data platforms, Veis says HP Haven is not simply a laundry list of Big Data technologies bundled in a suite, but rather a highly integrated platform that organizations large and small can use to create and augment new and existing business processes.
HP is clearly betting heavily on Big Data investments to drive a whole host of revenue opportunities across the data center. Before it can realize those ambitions, however, it clearly needs to establish that when it comes to Big Data, the company has more to offer than just the IT infrastructure required to run it.