Big Data Digest: Rise of the think-bots

With Sumo Logic, an e-commerce company could ensure that each transaction conducted on its site takes no longer than three seconds to occur. If the response time is lengthier, then an administrator can pinpoint where the holdup is occurring in the transactional flow.

One existing Sumo Logic customer, fashion retailer Tobi, plans to use the new capabilities to better understand how its customers interact with its website.

One-upping IBM on the name game is DataRPM, which crowned its own big data-crunching natural language query engine Sherlock (named after Sherlock Holmes who, after all, employed Watson to execute his menial tasks).

Sherlock is unique in that it can automatically create models of large data sets. Having a model of a data set can help users pull together information more quickly, because the model describes what the data is about, explained DataRPM CEO Sundeep Sanghavi.

DataRPM can analyze a staggeringly wide array of structured, semi-structured and unstructured data sources. "We'll connect to anything and everything," Sanghavi said.