Variability

This vector of big data derives from the lack of consistency or fixed patterns in data. It is different from variety. Let's take an example of a cake shop. It may have many different flavors. Now, if you take the same flavor every day, but you find it different in taste every time, this is variability. Consider the same for data; if the meaning and understanding of data keeps on changing, it will have a huge impact on your analysis and attempts to identify patterns.

Now comes the final and an important characteristic of big data—value.