Analytics: Logic and Structure

Analytics are often seen as a technical activity. While this is obviously true at some levels, the most critical aspect of any analytics project is the logic, structure, and intent. Before tools are considered, questions need to first be answered about what an analytics project is intended to address, the problems to be solved, the data sources to be accessed. Only after this work has been done do tools become important.  

For this assignment, develop an analytics model to gain insight into a complex topic using both qualitative and quantitative methods. Select a particular topic or subject area that interests you (current events, historical activities, a learning challenge) and detail how you will "interrogate" this subject using various analytics tools or techniques. Your project can be in the form of a presentation, a blog post, a video, a simulation, or other digital artifact. The important aspect of this assignment is to walk through the processes and considerations that pre-date tool selection.

Basically, you are asked to look at something (a problem, a challenge, an opportunity, whatever) that you would like to understand better. Instead of confining your exploration to what your favorite tools do, play around. Be clear about what you want to achieve. You are creating an analytic model that will later guide tool selection.

There is no set or prescribed way to address that "something". One approach is somewhat linear:

1. What do you want to do/understand better/solve?

2. Defining the context: what is it that you want to solve or do? Who are the people that are involved? What are social implications? Cultural?

3. Brainstorm ideas/challenges around your problem/opportunity. How could you solve it? What are the most important variables?

4. Explore potential data sources. Will you have problems accessing the data? What is the shape of the data (reasonably clean? or a mess of log files that span different systems and will require time and effort to clean/integrate?) Will the data be sufficient in scope to address the problem/opportunity that you are investigating?

5. Consider the aspects of the problem/opportunity that are beyond the scope of analytics.  How will your analytics model respond to these analytics blind spots?