WTF is Data Analytics?

“Data Analytics” is quite the buzzword, with over 70,000 job postings on Indeed containing this phrase. On the surface, it sounds like something vague that wouldn’t be part of an average job. But how is it being used in today’s workplace? And Whiskey Tango Foxtrot IS data analytics?

‍

Broadly defined, data analytics is the process of analyzing raw data to find insights, trends, and answer questions. Data analytics is a tool used across multiple industries and disciplines to answer a myriad of pressing questions that need an exacting and insightful answer.

Data analytics can be broken down into four types.

1. Descriptive analytics — Descriptive analytics provides you with a snapshot in time of what happened within your data set. Has revenue increased? Have views gone down? What was the number of returns last month?

2. Diagnostic analytics — Diagnostic analytics will tell you what went wrong with the last batch you ran. Or what went right. It tells you the why behind a change in the data and can help users better understand certain variables that might be more sensitive to a particular outcome. This pulls down the readout from descriptive analytics and digs in deeper to provide these insights. Did revenue increase because of the new marketing campaign?

3. Predictive analytics — Predictive analytics looks at historical trends, and then extrapolates what might be coming in the future.

4. Prescriptive analytics — The readout from prescriptive analytics may be the most valuable of the four different types. This will give the user options to help solve their problem by combining the insights from all the above analytics. Looking at historical data and what has happened before, what is our best course of action?

Using data analytics to take the guesswork out of everyday decisions has a place in every job! Simply using Excel spreadsheets is an easy way to harness the power of data and provide incredible insights. Which type of data analytics would make your job easier?

‍