Big Data Analytics Simplified – What Your Business Needs To Know

Big Data Analytcs Simplified
Big data analytics simplified

Life is really simple, but we insist on making it complicated” – Confucius

With the seemingly endless increase in the amount of data businesses are now collecting, coupled with the constant evangelising about the strategies, or tech we should be using to deal with this data, it’s no wonder companies are experiencing a certain amount of overwhelm.

It would appear that the situation is only going to get more frustrating over the coming years too. According to a report by the International Data Corporation (IDC), digital data will grow from the 2.8 trillion Gigabytes calculated in 2012, to a mind-blowing 40 trillion Gigabytes by 2020. 

It’s easy to see how businesses can often find themselves drowning in an ever increasing sea of data, yet struggling to gain any meaningful insights from the information they’re collecting.

In their recent report “6 Observations From A New Survey On The State Of Big Data Analytics”, Forbes suggests that a staggering 47% of executives surveyed do not think that their companies’ big data and analytics capabilities are above par or best of breed.

Fact is, the amount of data your business is working with is not the issue. Many companies have fallen into the trap of adopting a ‘data first’ approach, and this can make finding the insights that make a real difference, much harder.

What I mean by ‘data first’, is that a business may have lots of data to play with, and then set about trying to establish what that data can tell them.

A more useful approach, is to clearly establish what questions you want answers to, and then finding the data that gives you those insights. This means you are only looking at very specific metrics within your data, instead of trying to interpret it as a whole in an attempt to get it to reveal its secrets.

The most basic questions you can ask of your data are: who, what, when, where, why, and how. By using these questions as the basis for your analysis, you can easily identify the data you’ll need to look at in order to get the answers you need. If you require further information beyond the basic insights, you can simply add layers of data on top until you get exactly what you’re looking for. 

This approach sounds like it should be common sense, but many companies have been told that data is a complicated thing, or that you need specialist software to make sense of the information you’re collecting.

Truth is, it’s much more useful to strip everything back to the most basic point, and then gradually add in layers of relevancy until you begin to build up a meaningful picture of what’s going on in your business. This allows you to make informed decisions based on solid facts, rather than assumptions.

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