Why do we need thick data?

Traditional business intelligence technologies have helped the organizations to gain deeper insight from their data. With the help of intuitive charts, KPIs, verified numbers and facts, business can analyze customer choices, business trends, buying behaviors and preferences. Analytics have helped to predict the pattern for the future as well. This is great, thanks to the big data, analytics, and business intelligence technologies.

But, what next?

One key question these technologies were unable to address is: 

  • Why do customers make those choices
  • Why some behaviour patterns are more common than others?

This is where a more qualititative approach can help the business, precisely what thick data is all about.

Big Data vs Data warehouse

I have often came across this question - at times as a direct question from few of my coleagues and also at times as a point of discussion while designing business intelligence system for the clients.

Data warehousing is the buzzword for the past two decades and big data is hot trend in the recent decade. Lets find out what could be the answer for this question. 

Big data analytics word cloud

Year 2017 seems to be an exciting time for big data professionals. Big data vendor landscape is evolving rapidly and at the same time products that are on the offering are more stable and matured. 

However, from all the mess that is created in the big data space over the past few years, where are we gearing towards?