12 Emerging Trends in Data Analytics

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.

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