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
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Additional Reading
- What statisticians think about data scientists
- Data Science Compared to 16 Analytic Disciplines
- 10 types of data scientists
- 91 job interview questions for data scientists
- 50 Questions to Test True Data Science Knowledge
- 24 Uses of Statistical Modeling
- 21 data science systems used by Amazon to operate its business
- Top 20 Big Data Experts to Follow (Includes Scoring Algorithm)
- 5 Data Science Leaders Share their Predictions for 2016 and Beyond
- 50 Articles about Hadoop and Related Topics
- 10 Modern Statistical Concepts Discovered by Data Scientists
- Top data science keywords on DSC
- 4 easy steps to becoming a data scientist
- 22 tips for better data science
- How to detect spurious correlations, and how to find the real ones
- 17 short tutorials all data scientists should read (and practice)
- High versus low-level data science
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