Interpreting Big Data involves identifying trends from millions of data points and turning any interaction possible into a data point, even if the purpose isn’t understood straight away. Collect the data first, process it second.
Big Data started with algorithms helpfully scouring vast amounts of data to find patterns. These days it feels a bit like Big Brother. Using machine learning and AI to tweak algorithms, companies are now able to deliver profound insights from datasets once considered impossible to compile.