Today I had to give students in a seminar introduction to big data analytics -- I chose a recent presentation by Robin Bloor (from slideshare). Bloor states that the term "data science" is a misnomer, since all science is empirical and involves analysis of data. This is true for many of the sciences, still if my memory does not mislead me Einstein did not use empirical analysis of data to come with the relativity theory. It also goes to the discussion of causality vs. correlation in science. In any event, Bloor asserts that data science is actually a multidisciplinary efforts involves software engineering, statistics and domain knowledge.
BI, according to this presentation, is partitioned to:
- Hindsight: regular reporting
- Oversight: dashboards etc,
- Insight: data mining & statistical analysis
- Foresight: predictive analytics
He does not get as far as prescriptive analytics, and puts the heavyweight on the insight.
The second part of the presentation gives fast introduction to machine learning. Overall, it gives introductory level insights on insights from big data, and is well presented as such.