Big Data Analytics and Storage: Going Nowhere but Up in 2014

By Chris Preimesberger  |  Posted 2014-01-30 Print this article Print

Bachteal gave the example of railroad locomotives, which, once equipped with sensors tied to a data analysis system, allowed customers to more accurately anticipate parts wear to prevent equipment malfunctions.

Trend No. 4: Line-of-Business Employees Fast Becoming Primary Users

Thanks to the continual improvement in user interfaces—specifically drag-down menus, easy to follow wizards and familiarity with such operating systems as Windows and iOS—and increasing availability through the cloud, more and more non-IT staff workers are able to access big data analytics on a 24/7 basis and actually use it to the enterprise's advantage.

Trend No. 5: New Data-Centric Apps Will Become Mandatory

The ability to leverage big data will emerge as the competitive weapon in 2014. More companies will use big data and Hadoop (a fast, new-generation batch processing system) to pinpoint individual consumers' preferences for profitable up-sell and cross-sell opportunities, better mitigate risk and reduce production and overhead costs.

Trend No. 6: Search Emerging as the Unstructured Query Language

There were a large number of SQL initiatives for Hadoop in 2013, and 2014 will be the year that the unstructured query language comes into full focus. Integrating search into Hadoop provides a simple intuitive method for any business user to locate important information. Search engines also are the core for many discovery and analysis applications, including recommendation engines.

As big data analytics continues to become mainstreamed, the sector will require big innovation to develop along with it. New applications and user interfaces will be needed for all the various new devices (read that "wearable computing"); the business opportunities in all of this are astounding. You'd better believe that venture capitalists are all over this sector.

For example, Walmart is considering using crowd sourcing to set product prices and make image selections to accompany product descriptions. Digvijay Lamba, senior director of engineering for Walmart Labs, said the use of techniques such as crowd sourcing at the front end of the decision process completes the big data spectrum.

Existing big data systems are good at analyzing vast pools of data once developed, but are only as good as the data that enters the system. Crowd sourcing represents a way to add additional data at the front end of the big data process and will improve the analytical results. "We need to scale up the front end of the systems," Lamba said.

Yes, big data is more than simply a buzzword—there's a lot happening behind those two simple words. It will be interesting to a lot of IT folks to see how this all plays out over the next year or two.


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