Importance of Context in Data
The amount of data we produce every day is truly mind-boggling. According to Forbes, there are 2.5 quintillion bytes of data created each day at our current pace. In fact we will be generating cosmic proportions of data in future.
However, just having tons of data is not enough. Data, without context is futile. It is plain facts, numbers, words and figures etc. It is only when data is presented with a context that it becomes meaningful.
To quote Jack Dorsey, the founder of Twitter and Square,
“Most of that data is meaningless until someone adds some interpretation of it. Someone adds a narrative around it.”
This is where context comes into play. Context is essential for data. While analyzing data, context plays a crucial role in gaining insights, reaching a valuable conclusion and producing knowledge.
Although simplistic, the idea that Knowledge = Data + Context is pretty accurate too.
Let us look at a real life example to better understand the concept.
We know for a fact that Usain Bolt is the world’s fastest sprinter. However, Bolt’s race time data (9.58 seconds) is meaningless without a context. But once we compare his race time to that of other sprinters in a race, it indicates that Bolt has a winning time. Therefore, adding a contextual background renders the data more relevant and purposeful.
Furthermore, we identify that Bolt’s winning time comes from the final 100m event of IAAF World Athletics Championships. This lead into Bolt being declared the world’s fastest sprinter. As a matter of fact, on comparing Bolt’s race time with prevailing world record, we crown him the fastest sprinter of all time.
Hence, if we continue to provide contextual clues, the data becomes increasingly insightful, transitioning into knowledge.
To sum things up,
Data: Usain Bolt’s race time.
Info: Usain Bolt’s win time.
Context: Usain Bolt is participating in final 100m event of IAAF World
Athletics Championships.
Knowledge: Usain Bolt is the world’s fastest sprinter.
