In a week where adjectives were flying around to describe a certain relationship between a President and a Prime Minister (is it "special" or now "essential"?), it would appear that in the world of data warehousing and analytics, a few adjectives are also being thrown around to describe the huge challenge that faces organizations as they try to make sense and derive competitive advantage from their ever-increasing corporate and customer data volumes.Is it a case of "big" data? Or "large" data? "Massive" data or "extreme" data? Or is the adjective used to describe the issue at hand just plain irrelevant? After all, it's all relative and it's more than just a size issue. Hence the title of this blog; for one man's big data is another man's small data mart. Indeed, just how much is considered as "big"? And how do you quantify "massive"? You can't. Surely, the question is how you approach the whole issue at hand. How do you even begin to get value from such an amount of data when it is more than just a case of volume. There's the issue of complexity - just how many disparate data types do you have? Where are they located in your business, across multiple systems perhaps? Then comes the question of variety - what do you exactly want to get from your data? A marketing professional will want very different information from what the CFO demands. Then you have to think about velocity - how quickly do you need or want to get to all of your data, and how fast does your business need to get the insight in order to remain competitive?
Therefore, it's all much more than a case of size and therefore ego. Whether GBs, TBs or PBs, it's not the adjective that is important, it's what you need from your data and how you can perform the analytics on it that is much more essential.
