Gartner Research

Four Data Preparation Challenges for Text Analytics

Published: 15 January 2018

ID: G00338324

Analyst(s): Alan D. Duncan , Nigel Shen


The success of text analytics is predicated upon having a significant and meaningful set of data on which to operate. To derive business value from text analytics, data and analytics leaders must prepare text data in such a way as to draw out its inherent business context prior to analytics usage.

Table Of Contents
  • Key Challenges



  • Establish a Contextualizing Data Structure
  • Achieve Semantic Disambiguation and Decoding of Textual Content
  • Ensure Semantic Reconciliation and Consistent Interpretation
  • Promote Data Quality and Veracity
  • Deriving Analytics Value

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