The dirty little secret about Big Data projects is the actual length of time it takes to put one into production. When many organizations allocate six figures to hire a data scientist, they generally fail to take into account that most of them will spend the better part of a year working on basic data plumbing issues before being able to derive any meaningful insights from all the data they’re collecting.
To help speed that process along, Koverse today released Koverse Platform Version 2.0, an update to a data prep tool that includes a Universal Indexing Engine. Koverse is guaranteeing that with the engine, organizations will be able to put a data lake into production in less than 30 days.
Paul Brown, chief product officer for Koverse, says the engine is designed to automate the ingestion of any type of data. Anyone in the organization can interrogate that data in real time at any level of scale by using a self-service Forensic Search tool or via any number of data visualization, advanced analytics and business intelligence applications accessing that data via an open application programming interface (API).
Brown says that Koverse was originally created to deal with Big Data projects involving national security at the NSA. Now Koverse is extending that data preparation tool to meet the needs of the average enterprise.
Of course, getting Big Data into a format where it can be analyzed is only the beginning of the Big Data journey. But given the costs and scope of Big Data projects, most IT organizations would be well-advised to get a head start any way they can.