Getting the most value out of Big Data (part 1)
Data has always been a useful asset within the business world but it is only in recent times that the concept has been fully harnessed. Whether it be online shopping, bank transactions or social media, each byte of information can be stored, analysed and inferred from by companies to improve their products or services. Undertaking a big data initiative can be daunting at first but by creating a comprehensive plan and staying focused along the way, a business can outmanoeuvre their competitors.
The first step for any company is to come up with a detailed strategy of how they will take on their big data initiative. This can include what resources will be needed, incorporating new employees who can provide their expertise and most importantly, what questions will be asked. Many businesses can fall into the trap of doing too much, too soon and trying to answer all of their most important questions at once but this can lead to confusion. By choosing a smaller number of critical questions, the overall process is much more manageable and can act as building block to further initiatives.
The type of data that is analysed is also important, quantitative information in the form of graphs or trends is of course useful but businesses shouldn’t ignore the value of qualitative sources. It may be that a large block of numbers can only make sense when looked at in the correct context e.g. a drop in sales could be explained when looking for patterns within customer complaints.
Certain environments can be more conducive when looking at large amounts of data, this has led to many companies using ‘’analytical sandboxes”. These sandboxes provide a setting in which analysts can experiment with data, independent to the production process and all the accompanying pressures. This process is usually quite rapid but can sometimes provide new insights into information that was previously overlooked.
In part two we will look at what happens further in to the big data initiative and how businesses can utilise the information they gain from analysis.