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The Big Deal with Big Data Analytics

Overcome the obstacles of big data analytics with object storage. Harness and protect unstructured data to obtain actionable insights.

Types of Big Data
Big Data

Unstructured data is growing dramatically. According to IDC, the world’s data will grow by 50X in the next decade. Historically, all organizations needed to do with this data is store and access it every now and then, but that is no longer the case. In 2014, Forbes predicted that data-driven insight would be a part of at least one business unit across 74% of enterprises. Adding the two together (rapidly growing data sets + the need to continuously analyze information) leads to some pretty big obstacles.

In a new whitepaper, Marc Staimer, President & CDS of Dragon Slayer Consulting, expounds upon the five crucial problems with big unstructured data analytics (a deservedly hot trend in IT today) and how to fix them.

According to Staimer, the biggest obstacles tend to be operational and they include:

  • Reading/linking unstructured data into a NoSQL database or Hadoop framework ecosystem
  • Ingesting unstructured data ongoing
  • Storing unstructured data in a secure, protected, data lake
  • Querying
  • Search

So, how do you overcome these obstacles, harness and protect that unstructured data, and obtain actionable insights? Insights that have the potential to cure diseases, detect inefficiencies, and predict behavior of systems or even humans? Find out by reading the whitepaper.

Download Whitepaper

Adrian Herrera
Adrian Herrera

About The Author

Adrian "AJ" Herrera has over 20 years of experience bringing innovative storage, cloud and media software and services to market. With an MBA from San Diego State University and a BS in Information Systems from Chapman University, AJ serves as Caringo's VP of Marketing.

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