The last two decades can above else be considered the age of data. Never before has there been so much data gathered, processed, and analyzed. The term “data lake” was never a thing until we started measuring and logging everything and anything.
Worldwide, we create 2,000,000,000,000,000,000 bytes of data every day. This is an absolutely staggering amount when you think of it. This data includes everything from our shopping habits, to you friend requests, and email reads.
Businesses have shifted to using big data analytics for a many of their critical decisions. Governments are also increasingly using data analytics in their decision making processes.
So it’s clear that data has become hugely important in all of our lives. But as we base more and more critical decisions on data analytics, so does the impact of any errors or mistakes.
We almost never look at the raw data because it’s simply impossible to derive any meaningful trends from it. So we rely on processing and machine learning to make our data readable and understandable. This is where the first potential for errors comes from.
A tiny difference in processing or weighting can drastically change the output. If we are making million-dollar decisions, it’s extremely important to avoid mistakes here.