1. Analytics vs Statistics the problem is…
Bob McQuaid
Decision Sciences Institute Meeting
November 21, 2016

2. Scientist or Analyst?

3. Which is the egg?
Statistics
Analytics

4. Big Data: If just one of these?
Volume – is lots of columns and rows of text/numeric data “Big”
Variety – if lots of different kinds of data; think of all the data in a “house” at one point in time
Velocity – is monitoring one stock price every 2 seconds “big”
Veracity – if inspection is not 100% accurate, can this ever be “known”?

5. Live vs Lots vs Big

6. Programming not Analyzing?
FROM R-PROJECT.ORG:
an effective data handling and storage facility,
a suite of operators for calculations on arrays, in particular matrices,
a large, coherent, integrated collection of intermediate tools for data analysis,
graphical facilities for data analysis and display either on-screen or on hardcopy, and
a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.

7. Continuous vs Categorical?

8. Hypothesize or Datamine

9. Semantic Analysis or Number Crunch

10. Advertising Analytics
What’s in a name?
Predictive Analytics
Marketing Analytics
Customer Analytics
Advertising Analytics

11. Limited “engaged” hours…
BREADTH
DEPTH