Data Analytics, Data Scientists - Nature of work, Academic Background Required, Industries that use it

From http://blogs.msdn.com/b/brunoterkaly/archive/2014/07/24/fundamentals-of-machine-learning.aspx :

Excerpt:

How to think about the analytics spectrum

One great way to think about machine learning is to break down analytics into 3 questions:

1. What happened?
   • Historical
2. What will happen?
   • Predictive
3. What should I do next?
   • Prescriptive

How to think of the personas doing analytics

1. The information worker
   • Typically using a self-service approach using Power BI.
     • Power BI for Office 365 is a self-service business intelligence (BI) solution delivered through Excel and Office 365 that provides information workers with data analysis and visualization capabilities to identify deeper business insights about their data
2. IT professionals
   • Involved in data transformation, data warehousing, creating data merchant cubes for analytics, and data modeling
   • Work for GM's are directors
3. Data scientists
   • Deeply technical and skilled not just with code, but with mathematics, statistics, and probability
   • Can use a variety of techniques to apply probability to predictions (ie, there is a 42% chance that prices will go up in the next 18 hours)
   • Like Monte Carlo simulations, parameterizing the model
   • What to look for in a data scientist
     • Domain Knowledge
     • Clear Understanding Of The Scientific Method
       • Objectivity, Hypothesis, Validation, Transparency
     • Strong in Math and Statistics
     • Intellectual Curiosity and Critical Thinking
     • Visualization and Communication
     • Advanced Computing And Data Management

Academic backgrounds

If you were to go to school, went to study to be a data scientist, what courses would you take?

1. Applied Mathematics
2. Computer Science
3. Econometrics
4. Statistics
5. Engineering

Industries that really benefit from that of science

1. Financial Services
2. Telecommunications
3. Information Technology
4. Manufacturing
5. Utilities
6. Healthcare
7. Marketing