The once-common practice of collecting customer or business data into a data warehouse and then analyzing and acting on it weeks—or even days—later has become passé. As Eric Kavanagh, DM Radio Host at Information Management Magazine, pointed out in a recent podcast on the “Rise (and Assimilation) of the Analytics Databases,” end users “have a much more fluid relationship now with data as it is still in motion.”

The podcast, which was hosted by Information Management Magazine, was an interactive discussion that included dialogue about the evolution of analytics databases by industry vendors, as well as recommendations on selecting an analytics platform. The podcast included Mark Madsen, CEO of Third Nature, Inc.; Zahid Akhtar, Senior Manager of Deloitte Consulting; YY Lee, Chief Operating Officer at FirstRain, Inc.; and Mike Boyarski, Director of Product Marketing at TIBCO Analytics.

Mike Boyarski spoke primarily about the choices made by analytics buyers between mega vendors that offer all-encompassing solutions and best-of-breed companies that offer unique capabilities to enable organizations to distinguish themselves through speed of execution, and deep analytical and visualization capabilities.

“More and more (end-user) companies have application development divisions that are becoming sophisticated and are using open source technologies to meet their needs,” said Boyarski.

When choosing between analytics platforms, “it comes down to what you’re trying to solve as a business,” said Boyarski. “If you’re trying to differentiate on the analytics and provide analytics ‘better, faster, cheaper,’ then it’s best to opt for a best-of-breed solution that can provide real-time responses.” Many analytics customers are seeing strong value in partnering with an analytics vendor that can provide expertise that the client lacks in-house, Boyarski added.

Still, there’s a class of analytics user companies that aren’t looking for the best solution available on the market. “For these companies, it’s about using ‘just good enough’ technology,” said Boyarski. “But for companies that are looking to differentiate, they have to find a solution that meets their requirements for real-time decision-making.”

This includes financial services and retail companies that are attempting to detect fraud in real time, Boyarski noted.

“We’re increasingly seeing use cases where the need to act on data in real time is imperative, as opposed to letting (the data) sit for a day or a week or a month,” said Boyarski.

“It used to be that it (took) days or weeks or a month to get data into a data warehouse (for use) and that (time lag) is just not going to cut it anymore,” said Kavanagh. “There are just so many opportunities for using data when it’s in motion and when people (customers) are in motion.”

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