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Big data management and analytics will see some significant changes continuing and others beginning to emerge this year.  These include: 

  • Leveraging data in different and more productive ways, effectively moving from the dashboard to a discovery platform and from a retrospective strategy to inherently more predictive one.
  • Cutting through the noise and focusing on the signal. Companies are faced with managing enormous amounts of data, and determining how to identify actionable data amongst all the noise. Expect data driven companies to bring a more tightly focused approach to their data in order to cut through noise and reap greater business benefits. 
  • “Democratization of Data”, where self-service comes of age and people begin to get access and truly “own” their data.
  • Moving away from a DIY approach to turnkey solutions. Today’s approach to big data is still very much a customized solution where companies are tasked with building everything from scratch. 2016 will see a growing demand for out of the box solutions.
  • Commercial success for big data. With Gartner claiming only 3-8% of the potential big data market having been actualized, there is room for ongoing considerable growth, and a true launch of the commercially viable enterprise data warehouse in 2016.  

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Tags: big, data, democratization, of, turnkey


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Comment by Dr. Paul Terry on March 29, 2016 at 1:08pm

Thanks for the comments everyone!  

Peter,  absolutely agree. This is where the democratization of data leads organizations; helping to put data in the hands of everyone.

Maurice, that's a very sensible progression. Making quality data easy to collect, curate, and consume followed by increased usage. Business' realizing value from their data will accelerate the entire system.

Vladimir, great question.  One example of a "cutting through the noise technique" would be identifying a subset of variables that are strong predictors of an outcome that's important, so that your business can understand how to impact operations. For instance, many healthcare organizations today are focussed on the challenge of reducing re-admission rates. Identifying what patient diagnosis, treatment, and outcome variables are strongly correlated can provide data driven insights that help improve processes to increase patient health and reduce healthcare costs.

Comment by Peter Fretty on March 13, 2016 at 3:25pm

Great post. I would say one of the biggest trends we will see is the enablement of business users to explore and experiment with data use. Data needs to move outside the traditional scientist realm if organizations ever want to fully operationalize its use. Peter Fretty, IDG blogger for SAS Big Data Forum.  

Comment by Maurizio Magnani on March 8, 2016 at 5:22am

Very good points. I would guess that point 2 (cutting through the noise and focusing on the signal), point 3 (democratization of data) and point 4 (moving to turnkey solution) are going to have an outlook of significant changes during this year. Instead, I see point 1 (leveraging data in more productive way) and point 5 (commercial success for big data) as a direct result of the above changes and so, only in a second time they are going emerge.

Comment by Vladimir Sevastyanov on March 7, 2016 at 12:04pm


This is a good point. I totally agree. Could you give an example of a "cutting through the noise" technique, please?



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