The term ‘big data’ was first used to describe databases that were so large that relational database management systems (RDBMS) couldn’t return results quickly enough using the traditional tables, rows and columns lookup approach.
Companies like Google, Facebook and NASA truly have big data and may require non-relational databases to analyse their data, but there are very few companies in the world for which an RDBMS will not suffice.
I hate buzzwords, but maybe it won’t last. Hopefully big data will soon become very big data, or even bigger data.
We have been hearing quite a lot about big data this year. Vendors are coming with products and extensions that they claim can give you access to big data and theoretical analysis. Various analyst organisations cannot stop talking about it. When it initially started I was taken by it as well. However, if you stop and think about it, and I mean really think about it, and get beyond the marketing spin, it is just another data source that can be integrated with other data to drive insight and action. And as with all data sources it should be used only if it is relevant and it will drive insight and action.
More and more people involved in practical implementation of BI solutions are saying “Can’t we just call it data?!” Yes please I say.
In reality, most organisations are still struggling to consolidate and take advantage of their own data first and taking advantage of data generated by Google, Australian Bureau of Statistics or other external data sources is a long way off for them. So while it is good and important that we can say ‘me too,’ it is worth considering ‘why’ first. The focus should always be on the business issue or opportunity we need to address.
Have a read of Stephen Few’s blog. Stephen is a well-known data analysis and data visualisation blogger and has written a number of books on the subject. I think his blog is quite realistic.
I like Stephen’s conclusion the most:
“Look past the marketing hype for analytical (data sensemaking) products that actually work. It doesn’t matter whether they’re called big data, analytics, or just plain data analysis tools. What matters is that they help you find the signals that exist in the midst of all that noise in your data and make it possible for you to understand those signals and use that understanding to work smarter than before. Demand that vendors show you how their tools can be used to glean real value from your own data. Ignore their claims and demand evidence. Make them show you how you can make better decisions using their products and services. Unless they can provide that, you don’t need what they’re selling.”
Blog written by Chris Pennington, Consultant to PA. The opinions expressed here are the personal opinions of the writer. Content published here does not necessarily represent the views and opinions of Professional Advantage Pty Ltd.
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