What happened? The story of Descriptive Analytics

 The oldest know data analysis consists of two things-aggregating or summarizing data and  data mining.

The majority of a company's investment in data analytics is focused on aggregating data-- what was the sales, by month, by region for example.Comparing to previous time periods gives an understanding of where the company is going for instance the sales have increase 20% compared to previous quarter. It is an important tool for analysis of the performance of a company. Different types of data are then mixed and matched to provide further insights such as :

ROIC--Return on Invested Capital takes  three datasets--net income,dividends and capital .This allows us to compare performance of two or more companies.

On a similar vein, company annual reports are descriptive analytics in action . They tell the story of what happened in the past. These reports are mostly derived from spreadsheets and ancillary sources such as ERP tables .

Data mining techniques allow you run the group aggregated data and look for logical conclusions to understand customer behaviour. A grocery chain may use data from its loyalty card program group to analyze what are some of the fast moving items in the produce section.

Banks are one of the best examples of the descriptive analytics mindset. They are so focussed on the historical aspects which is important since they are custodians of our money. The problem is both legacy systems and the lack of new data mindset is making it very hard for them adopt the newer types of data analytics