Pivotal HD Tips the Time-to-Value Ratio

For many companies, analyzing large internal data sets combined with realtime data, like social data, and extracting relevant insights isn’t easy. As a marketing director, you might need to look at several months of customer feedback on a product feature and compare those comments to ad mentions on Twitter for an ad-spend decision happening…tomorrow. Depending on the capabilities of your platform, this type of analysis could take awhile and you might not have the answers to inform the decision you need make.

This spring, our Plugged In partner Pivotal HD, formerly EMC Greenplum, went through a bit of a transformation that facilitates analysis of big data sets that combine both internal and external data. A combination of EMC Greenplum and VMware, the newly formed Pivotal is a Hadoop distribution that enables enterprise customers to combine both structured and unstructured data in a single cloud-powered platform, rather than operating multiple systems. What does this mean for enterprises and their customers? In a word (or two) it means speed and accessibility. Through this platform, companies can more easily store and analyze giant data sets, including social data, without spending all of their time building data models to do the analysis.

If you’ve read any of our Data Stories, you know we love data analysis here at Gnip, so we thought it was worthwhile to learn more about what Pivotal HD does for big data analysis. We talked to Jim Totte, Director of Business Development and Srivatsan Ramanujam, Senior Data Scientist at Pivotal HD and captured some of the conversation in this short video clip: