The Jigsaw of Big Data Analytics

When you open a 5,000 piece jigsaw and look inside it looks daunting and impossible! Especially if the picture is for example baked beans! It may seem an impossible task. Like understanding Big Data Analytics.

But applying some logical structure you can start to build it. First find the corner pieces and the straight edges, before long you have built the frame. Then you turn all the pieces over and start to build the picture.

Basically this is an easy analogy to understand big data analytics. If you think which is the easiest way to look at the jigsaw ? Piled in a heap in the box ,or laid out with the frame built and the pieces clearly turned over and spread out then you can actually see the picture. Big data isn’t just about the pieces, or how many rows or petabytes, its about the context and understanding. As the puzzle starts to take shape we can see what its about and the picture. Now if someone put in some piece’s from a different jigsaw this would cause confusion? You would have to find them and remove them as they don’t belong to the original picture.

Big data analytics uses machine learning and massive analytical systems to find the corner piece’s , build the frame and sort through the pieces. The pieces being the corporate data.

In recent years attention has increasingly focused on the corporate data that lies outside conventional structured enterprise databases. As the realisation has grown that this data is much larger in volume than previously thought,and potentially just as valuable. Here at Whitehall Media we have worked on events to give Companies an opportunity to decipherer and disseminate BDA information they have used to make informative business decisions. Corporate users and vendors have both focused on developing technologies and approaches for capturing and integrating this big data into mainstream enterprise data infrastructures.

Huge volumes of variable data is being generated at dizzying speeds, monitoring and logging software and devices. What are some realistic advantages in the scope of analytics, knowledge discovery, new opportunity identification? What does this mean?

For example, An insurance company used BDA globally to make informed decisions with customers about insurance policies and price? Simply using BDA from world wide weather data to measure risk of floods, hurricanes and other natural disasters. The information allowed accurate and timely data to form a picture, build a weather jigsaw.

Supermarkets are using BDA to track and build a picture of your shopping profile to personalise offers sent out that are more suitable for the individual, therefore maintaining regular custom. Also used BDA information to measure sales of certain goods that were related to popular items. This may bring more financial turn over but wont keep your business afloat. It is the regular returners who come back week in and week out for the more unusual items that will keep your business viable. So BDA is being used to focus executive decisions on deeper analysis of data.

Whitehall Media can help your harness the power of big data to allow you to effectively build your data jigsaw.