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Thursday, April 23, 2015

Four challenges to pulling value from text data

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IBM April 2015  
Charting your Analytical Future
  Dear Alejandro,

As a significant component of your big data, text data can give you a wide range of insights that aren't available from other data...if you properly prepare your text data for analysis.

What defines effective text data preparation?  What challenges will you need to address to make it happen?

Read this Gartner paper for a thoughtful discussion of the unique challenges associated with getting text data ready for analysis, and for a detailed look at their recommendations.  You'll learn why:

  • Prep of text data cannot be practically managed through traditional data modeling
  • It's easy to underestimate the effort needed to prep and contextualize text data
  • Contextualizing semantics are critical understanding and interpreting text data
  • The gap between technological capabilities and user knowledge inhibits decision making

Download and read "Four Data Preparation Challenges for Text Analytics" today!

Thanks for subscribing to Charting Your Analytical Future!  This is your newsletter.  If you have topics you'd like us to cover or have comments about the content we bring you, please let us know at chethanshetty@in.ibm.com.

Gartner, Four Data Preparation Challenges for Text Analytics, Alan D. Duncan, 6 January 2015.



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