Big Data – From Descriptive to Prescriptive

April 5, 2014 — Leave a comment

What if:

… you could identify which employees are likely to turnover in the next 6 months?

… you could understand which transformers are likely to fail during our next major storm?

… your call center agents could delight customer with the best next-step recommendations?

Big Data is the catch phrase of the day.  Everyone has heard of it, most have a vague idea what it means, some have a clear grasp of what it can really do, and few can execute it effectively.  I’ve been doing a lot of reading on Big Data and there is certainly no lack of resources on the topic.  As I read through many reports, white papers, press releases, magazine articles and company presentations (all available via a quick Google search) it occurred to me that visually communicating the value of Big Data is challenging because of the need to convey different concepts simultaneously.  The most popular category by far are plot charts on an X-Y axis.  These charts plot analytical complexity against some sort of business value measurement in a positive correlation that looks entertainingly similar to human evolution charts we’ve all seen, with man becoming more upright and intelligent with time.

Less popular, but also useful, are a bulls-eyes, Venn diagrams and an stacked area triangles. Regardless of graphic representation, they all follow the progression from What Happen(descriptive analytics), Why Did It Happen (correlation analytics), What Will Happen Next(predictive analytics), and What Should I Do About It (prescriptive analytics).  Which one do you prefer

 

Why We Like It: This chart is unique in that it goes all the way back to the beginning when data is first created and gathered in raw form.  So much of the resources needed to develop prescriptive analytics takes place in the very early stages of the process, and it’s nice that this graphic gives it a mention.  The overwhelming majority of data available for analysis does make it to the final predictive/prescriptive model.  If each circle represented the amount of actual data at that stage, the raw data circle (and cleaned data circle) would dwarf all the others, so thank you SAP for giving data its due.

 

Read More: http://www.miprofs.com/big-data-descriptive-to-predictive/

 

 

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