In an era of data overload, businesses across industries are struggling to efficiently extract value from all the information available to them and use it to steer their organizations forward.

Consider this: according to Forrester Research, the Big Data market will grow three times faster than the overall IT market at a compound annual growth rate (CAGR) of 13 percent over the next five years. This surge of Big Data can be largely attributed to the Internet of Things (IoT). Right now, there are more than 22 billion connected devices worldwide, and with those connected devices come massive amounts of data.

With the IoT market expected to continue growing – Gartner projects that 6.4 billion connected devices will be in use worldwide this year, and will reach 20.8 billion by 2020 – businesses need to figure out how to manage and leverage the increasing amount of data available to them.

While data storage is becoming less expensive, the rate of data growth is such that the cost of processing, auditing, securing and exploiting data is rising faster than any savings accrued through decreasing storage costs. To ensure they’re effectively managing resources, businesses need to rethink how they’re leveraging all this data – and that starts with the introduction of a Deep Data framework.

A Deep Data framework enables businesses to identify and aggregate the most information-rich data streams and leverage that information to secure meaningful insights into their most pressing business issues. Used across industries including energy, financial services and health care, this method is about ignoring irrelevant or less useful data and honing in on the data streams that matter most.

The key elements of a deep data framework are:

  • • Defining their goals and focus on the specific business challenge they are trying to solve
  • • Applying advanced analytics to a small, but information rich, data set, rather than sifting through vast quantities of information
  • • Developing smart strategies to act on unearthed insights

This method has proven to be hugely successful in the energy industry. Looking at data from the utility meter, arguably the oldest and most prevalent IoT device around, utilities can identify ways in which customers have historically used energy.
That intelligence, coupled with data pertaining to weather and geographic factors, enables utilities to determine how customers may use energy in the future. This customer intelligence enables utilities to prepare for shifting energy usage patterns, educate consumers about their energy spend, and engage customers with personalized offerings that meet their individual energy needs.

As more connected devices emerge, the Deep Data approach will not only alleviate stress related to the explosive growth of new data, but deliver meaningful insights that can help decision makers solve their most pressing problems.

(About the author: Badri Raghavan is chief data officer at FirstFuel Software)

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