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Data Science Central shared its predictions for 2016. More predictions can be found here. In this article, we share Scott Mongeau's predictions. The full version of this (long) article can be found here

  1. Plumbers wanted: data management overhead demands professional data mungers
  2. Hardening models:  increasingly complex models require tighter approaches to diagnostics and validation
  3. The tunnel link: big data engineering and methodological approaches meet in the middle
  4. Change management to the fore: evidence-based decision-making requires management to contemplate new organizational forms
  5. Invisible architectures: enterprise architecture embraces systems management to forge a path through the mist of multi-systems complexity
  6. We’re not in Kansas anymore:  increasingly diffuse models requires a deeper methodological understanding of broader research paradigms
  7. Living with the paradox: coming to terms with irresolvable methodological quandaries
  8. Cyborg enterprise:  industrial-scale analytics ushers in the age of highly integrated, large-scale techno-organizational decision programs
  9. Not for everyone, but necessary none-the-less:  analytics as a service and outsourcing analytics as a function
  10. On-ramping AI: organizational operationalization as a step towards machine automation
  11. Emerging profession: professional computational decision engineers and AI stewardship
  12. Far-future: the birth of the Chief Meaning Officer – equal parts decision scientist, IT manager, storyteller, and organizational anthropologist

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Comment by Deborah Deng on February 24, 2016 at 10:46pm

I like the Chief Meaning Officer. :)

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