The arrival of big data and the importance of data as a product heralded what's been touted as the hottest job of the decade, "data scientist".
Combination of statistician, programmer, entrepreneur and storyteller. DJ Patil in "Building Data Science Teams" (http://radar.oreilly.com/2011/09/building-data-science-teams.html
) characterizes their role in companies:
* Decision science and business intelligence
* Product and marketing analytics
* Fraud, abuse, risk & security
* Data services and operations
* Data engineering and infrastructure
Patil characterizes a data scientist as having:
• Technical expertise: the best data scientists typically have deep expertise in some scientific
• Curiosity: a desire to go beneath the surface and discover and distill a problem down into a very clear set of hypotheses that can be tested.
• Storytelling: the ability to use data to tell a story and to be able to com- municate it effectively.
• Cleverness: the ability to look at a problem in different, creative ways.
In essence, the change is this: you can't put analysis in a box. A large BI vendor told me that their biggest problem tended to be the organizational structure of their customers, analysts were isolated in their department, throwing reports over the wall.
Google, Facebook et al not only have better tools, but they are organized around the importance of data to their organizations. Reaping benefit from data may well be as simple as sitting your analyst next to the business team.