Defining Deep Data: What It Is and How to Use It

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Adopt a Data-Centric View

A final key element in implementing a data strategy is to encourage adoption of a data-centric view at every level of the organization. As part of this, it is important to democratize access to data. This allows different individuals or departments to leverage the data for uses that best fit with their needs, while also enabling new avenues for innovation because of collaboration across the company.

In the era of Big Data, businesses across all industries struggle to efficiently and effectively manage data overload. Many organizations do not know how to pinpoint and extract the value embedded within the heaps of data available to them, and consequently find themselves stuck in the "data hoarding" trap – capturing every piece of available information, rather than focusing on the data that is providing the greatest business value.

Instead of just thinking "big" when it comes to data, companies need to start thinking "deep." The Deep Data framework is based on the premise that a small number of information-rich data streams, when leveraged properly, can yield greater business value at lower cost than vast volumes of data. For example, organizations can use the Deep Data framework to better understand a customer's behavior and provide actionable, scalable insights that simultaneously improve customer engagement and drive economic value of that company's data investment.

What do you need to know to effectively implement a Deep Data strategy? In this slideshow, Badri Raghavan, CTO and chief data scientist at FirstFuel, has outlined valuable insight organizations should consider.

 

Related Topics : Vulnerabilities and Patches, Resellers, Broadcom, Broadband Services, Supercomputing

 
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