By Allie Philpin
Mention Big Data in some circles and you can see business men and women literally ‘quaking in their boots’, even senior management and within the boardroom! But do we really need to be that fearful of what, after all, is just data that your organisation has gathered from various sources over a period of time? CEO of analytics platform provider Opera Solutions, Arnab Gupta, doesn’t think so. He believes that big data projects should be more like a focused business initiative rather than a huge infrastructure project, and has voiced his thoughts on some of those big data myths!
1. Big data is the next business model – change now or you’ll get left behind. Errr, no. Gupta believes that businesses that think and react in this way end up with stockpiles of data, gathered in Hadoop clusters, and still don’t know what to do with the data they’ve collected! He explains: “The problem with first versus last thinking is that you assume that if you’re first, you’re going to get a competitive advantage, but that won’t be the case if you don’t focus business results that will give you a business advantage.” Organisations just aren’t used to dealing with such big volumes of data, and that’s wherein lies the problem. Start with a known problem, then make the changes to analyse your big data to address that problem.
2. It’s IT’s problem, not ours. A trap that many an organisation gets into; it is likely that if it stays with IT, it will become that horrifying, all-consuming, huge infrastructure project you want to avoid! Gupta says: “Most of the investments in big data projects have gone into information management infrastructure. If you start with the business use case, you may still be investing in infrastructure, but it will be for precisely the tools you need to solve a specific business need.”
3. How can we master big data if our data is in such a mess? With so many efficient tools available today that can help your organisation with data management, data visualisation, data governance and data analysis, it is now much quicker and easier to capture, manage, clean and analyse your data , including sifting the good from the bad! Gupta adds: “The huge investments companies have made in data management are now paying massive dividends.”
4. We’re a big company; how can we all agree on a big data project? All projects have common denominators, such as your customers, products, suppliers or partners, and that’s what you need to look for. These common denominators act as focal points around which you can plan big data integration and gather important insight.
5. Big data means data scientists; not many around and expensive! The majority of a data scientists work is finding the patterns, the trends, within your data, i.e. those common denominators, and that’s the time-consuming, and therefore costly, element. The other, much smaller, element – Gupta believes is an 80:20 split – may need the services of a data scientist to choose the right statistical methods and analysis techniques. For example, using a time-series analysis, you could find those patterns within your data; when you’ve done it once, the process is repeatable. Gupta explains: “The mistake people make is starting all over again with each new project. You have to create a repeatable process or it will never scale.”
So, you see, needn’t be as scary as you think; and it’s not all down to one department. Collaborate, communicate and connect with each department; focus on what needs to be addressed and adapt/invest in the infrastructure necessary to gather the information to solve the issue. It is, after all, just data…