Data goes through a life cycle. When a company collects information, that data is in motion, fresh and ready to speak of the world as it is. Then, that data passes through the system to its new home on a storage block somewhere, becoming data at rest. This information is the bedrock on which analytics is built. The trick is that in the modern business world, companies have to consider both kinds of data, at rest and in motion, to get the most from their technology. This requires an integrated system capable of handling data no matter its speed.

To get an inside look at this world of shifting data, John Furrier (@furrier) and Peter Burris (@plburris), cohosts of theCUBE from the SiliconANGLE Media team, joined Wei Wang, senior director of product marketing at Hortonworks, Inc., during the BigDataSV 2016 event in San Jose, California, where theCUBE is celebrating #BigDataWeek, including news and events from the #StrataHadoop conference.

Building the data loop

The conversation started with the topic of devices and systems for handling data. “I truly think it’s all connected,” Wang said. Companies are looking for a connected data platform that works with data in motion and data at rest. Think of the data streaming in, Wang said, a company needs actionable intelligence immediately. Meanwhile, data at rest is a platform for long-term analytics and analysis. The insights from analysis, she continued, have to feed back into the data in motion part to improve the intelligence of the system.

These new data technologies also demand some attention to the human element. Most people who work with this data will be same folks who dig into new technology, Wang said. Still, new skill sets will be required for systems that allow a company to do entirely new things.

Applications and context  

The discussion then turned toward data applications. Wang felt applications came down to the specific use-cases. Some uses, she said, could be completed on the in motion side, while others focused on the at-rest arena. The difference was important. Data, she said, has a useful lifetime. Information needed immediately is no good four hours later.

This also brings up the benefit of an integrated system. Wang pointed out that the context of data can change; in an accident, for example, data from an hour ago might become immediately important. An integrated system can handle that change much better than other data technologies.

Watch the full interview below, and be sure to check out more of SiliconANGLE and theCUBE’s coverage of BigDataSV 2016. And make sure to weigh in duringtheCUBE’s live coverage at the event by joining in on CrowdChat.

Photo by SiliconANGLE