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Data Culture

Data Analytics 101 : Descriptive, Diagnostic, Predictive, and Prescriptive

Have you ever read an article mentioning Data Analytics and thought, “What the heck is Data Analytics and why should I even care?” Or, has your boss ever requested a report on your current sales reps’ wins and then asked you how their numbers could be improved? When you look at the stats behind this requested measurement, you can figure out what is happening and why it happened, then take it up a level and forecast what will happen next. This is called Data Analytics.

Officially, it’s the science of examining raw data with the purpose of drawing conclusions about that information. Data analytics are used in your industry to allow you to make more informed business decisions and make those decisions with confidence.

Data analytics can be broken into four stages: Descriptive, Diagnostic, Predictive and Prescriptive. The trick is to follow your data path from information you have all the way to optimization of that information. The further you walk this path, the more difficult it may become BUT there’s more value to be gained when you get there.

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Here’s a simple breakdown of the four stages of Data Analytics:

Descriptive (business intelligence)

What happened?

Diagnostic (data mining, data discovery)

Why did it happen?  

Predictive (forecasting)

What will happen?

Prescriptive (optimization and simulation)

How can we make it happen?

Descriptive, Diagnostic, Predictive and Prescriptive analytics graphic

What stage is your company in? 

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Do you have lots of data with no clear path to move forward? 

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Are you operating out of your descriptive analytics and ready to move to the predictive phase? 

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Let us know! We love data and we want you to too. 

July 22, 2016
by
Jacey Lucus
in
Data Culture

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