When data is biased, we mean that the sample is not representative of the entire population. Data can be biased but so can the people who analyse the data.

Bias is taken to mean interference in the outcomes of research by predetermined ideas, prejudice or influence in a certain direction. The chief cause of making the wrong decisions is what we call ‘bias’. Decisions made on the basis of such truth can subsequently turn out to have been incorrect. This can lead to the outcome of analysis being mistakenly treated as truth. Results from data and analysis can be deliberately or unwittingly misinterpreted. It is important to remember that decisions are not necessarily guaranteed to be successful just because they are based on data.

This is a positive development, but at the same time it brings with it a number of pitfalls. As such, decisions are considered to be based on insights, supported by adequate data, analytics and research methods & techniques. According to EMC (‘Digital Universe’ report from 2014), the quantity of data is going to see a tenfold increase between 20. There has never been so much data available for making decisions.

What does it mean to be biased