Forrester moves past hype and gets real with big data recommendations

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The one blog post that stuck out for me in this year’s annual onslaught of New Year’s predictions posts was published by Forrester Research, Inc.

Big Data Predictions For 2013* by Forrester’s Mike Gualtieri offers solid and realistic advice amidst the hype surrounding big data.  Gualtieri’ main predictions are:

  1. Firms will realize that “big data” means all of their data.
  2. The algorithm wars will begin.
  3. Real-time architectures will swing to prominence.
  4. Naysayers will fall silent.

Add to that the January 3rd  release of The Forrester Wave™: Big Data Predictive Analytics Solutions, Q1 2013, and it’s clear Forrester has done its research in this area. Naturally, their inclusion of SAS as a leader is high on my radar, but the report provides insights worth reviewing beyond that important nugget.

Specifically, the predictive analytics process that Forrester proposes, while not entirely new for big data, is quite useful.

Image courtesy Forrester Research, Inc., The Forrester Wave™: Big Data Predictive Analytics Solutions, Q1 2013

To understand who handles that analytical process best for big data, Forrester evaluated each vendor’s current offerings, strategies and market presence. I’ll leave it to you to read the full report and glean your own insights, but be sure to watch for the “unshakeable leaders” and the “analytics powerhouse.” I think you’ll recognize the name.

*source: Forrester Blog published on January 2nd, 2013

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About Author

Alison Bolen

Editor of Blogs and Social Content

Alison Bolen is an editor at SAS, where she writes and edits content about analytics and emerging topics. Since starting at SAS in 1999, Alison has edited print publications, Web sites, e-newsletters, customer success stories and blogs. She has a bachelor’s degree in magazine journalism from Ohio University and a master’s degree in technical writing from North Carolina State University.

2 Comments

  1. Interesting to read Forrester's predictions. The link is broken so I couldn't read more but the fact there seems to be nothing about how to find and retain analytic talent or data scientists? That surprises me a bit.

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