In most enterprises, data access is a fait accompli: 72% of global data and analytics decision makers say that they can access the data they need to obtain insights in a timely manner.  However, even the most modern BI that make data more accessible still require significant subject matter expertise to find the right data, ask the right question, and interpret the results correctly in order to achieve tangible business outcomes. A majority of data and analytics decision makers (52% on the business side and 6% on the technology side) say that they to recruit people with advanced data skills to support their enterprise data-driven initiatives. But even if you did have these data experts, they still feel challenged navigating and interpreting the data.  The current generation of BI tools has gaps that prevent BI pros from fully leveraging them for valuable insights. Today’s BI technologies are:

  • Not designed for nondata professionals
  • Not extending the value of predictive analytics
  • Hitting the wall with how to interpret rich data visualizations
  • Still dependent on a lengthy, often unreliable process to get to insights
  • Providing insights based only on a small subset of data
  • Separated from of record and of engagement that make insights actionable

For more details on what these gaps are, and most importantly how can latest artificial () based technologies close these gaps, please read Forrester detailed AI Unlocks The Business Intelligence In BI report. Remember: AI does not replace BI, nor is BI becoming an alternative to AI, but BI tools that leverage AI technologies will replace BI tools that don’t.


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