Sourcing a data-driven story is a complicated process. The magnitude of the information that is now available in even medium-sized datasets makes it difficult to know exactly what vein of information contains the most impressive or significant story, no matter how good a person may be at pattern recognition or spotting trends. Even if you believe you have found something insightful and original, there might be an even more interesting take on the same data that was only visible when the data is viewed at its most granular level.
Databases and data visualisation tools have become invaluable when finding the narratives in big data; the technical constraints of such tools mean that the larger a dataset is, the further the data needs to be shrunk to become manageable and to reduce processing time. This sacrifices crucial data granularity to the extent that interesting stories which rely on high levels of detail are lost.
So, what can be done? Let’s look at a real-life example of how all of the data can come into play when you have the right tools available, and why the most detailed data can be the most valuable.
For Full Story, Please click here.