Big Data intelligence firm ClearStory Data has just launched a new version of its Apache Spark based analytics software that speeds up the time it takes to analyze data from disparate sources. In addition, it’s touting a faster approach for preparing data for analysis, together with a simple method for blending data.

ClearStory’s Intelligent Data Harmonization Engine facilitates these new capabilities thanks to the integration of Spark 1.2 in-memory technology, and an improved user interface featuring a new guided model.

Vaibhav Nivargi, Co-founder and Chief Architect at ClearStory, said the new release allows users to control and visualize how they can harmonize multiple data sets, leading to a significant reduction in time and complexity when preparing data for analysis.

“This release strikes a new balance between the power that intelligent data harmonisation brings to business users and the level of precision and control that more data-savvy users typically prefer,” said Nivargi. “These new capabilities guide users to the best data to blend together to ensure that the resulting harmonised data can deliver fast, accurate and meaningful insights.”

Other new features in the release include intelligent semantics to measure the overlap of individual attributes across multiple datasets, plus the ability to collect extra datasets. In addition, ClearStory said its software is now better able to trace the origins of data, regardless of source, parent dataset, data structure or shape.

ClearStory data’s main offering includes a front-end app that sits atop of numerous data sources, plus a back-end that runs on Apache Spark. The back-end serves to carry out data inference and profiling, spotting relationships between different sources of data. It can then present that blended and harmonized data to users via the front-end application, allowing multiple users to explore company data simultaneously or add data without carrying out any additional modelling.

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