DIRECTOR UK ENTERPRISE CISCO
WHAT DOES THE INDUSTRY MEAN BY BIG DATA?
Big data refers to data sets that are too large to economically manage and analyse with traditional IT techniques in a reasonable timeframe. Big data is typically in the tens to hundreds of terabytes range, or even much larger. Sources include both human and machine-generated unstructured and structured data. Big data is most frequently associated with large, distributed, internet-based solutions as used by Yahoo, Google and Facebook. However, the term also typically covers newer commercial applications such as using Twitter feeds for corporate sentiment to judge the risk of financial investments.
WHAT ARE THE OPPORTUNITIES HERE?
By 2013, 15 per cent of business intelligence (BI) deployments will combine BI, collaboration and social software into decision-making environments. Additionally, 33 per cent of BI functionality will be consumed via handheld devices, enabling more accurate decisions to be made faster. According to Gartner, data warehousing and business intelligence ranks in the top five of chief information officers’ priorities, identifying the opportunity to create new revenue streams by offering new client services while lowering business risk.
WHAT ARE THE KEY CONSIDERATIONS FOR COMPANIES LOOKING TO CAPITALISE ON THIS PHENOMENON?
It is important to establish an architectural, scalable approach; big data is not simply a bigger traditional data warehouse. There are some differences, and recognising what is required for both server and network solutions is key to a successful deployment. By 2014, 30 per cent of analytic applications will use in-memory functions to add scale and computational speed. Ensure the solution truly meets the business requirements of the organisation, and avoid technological cul de sacs.
Big data is not simply a way to store and serve “a lot” of data. A large file store is one thing, but big data implies analysis – or at least manipulation – of the data set.