Getting the most value out of Big Data (part 2)
In part one, we looked at the planning stages of big data initiatives and some factors for companies to consider before undertaking the project. The second part will focus on what can happen further down the line and how businesses can stay on track.
It can sometimes be the case that companies get six or eight months into their project and lose sight of where the initiative is going. If this does happen there are things that can be done to help get things back on track and moving again. Firstly the strategy team behind the development should be balanced and cohesive, this is vital. Another problem that can arise is stagnation, ideas that were so clear at the beginning may not be working out as planned and should therefore be reimagined in accordance with findings.
Once answers are gained from the analysis of the data, the next step is to create a range of hypotheses from these answers in which to investigate. Validation of hypotheses can be made with “test and learn” practices, these involve testing ideas with small customer cross sections. Trialling these ideas with a control group before introducing them to the wider base can provide invaluable information about their efficacy.
The next natural step in the big data movement would be to integrate analytics into operational processes within businesses. As new information is gathered it is automatically tested and organised according to already known patterns, this makes for a much smarter and self-evolving system. This may even help to save money and resources as data analysis doesn’t have to exist as a separate department.
Big data is a concept that is only going to grow as the internet becomes an even bigger part of people’s lives, therefore the path that business take when implanting an initiative could be indicative of their future success.
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