Is Big Data too big to fall? Think Again.
Big data has its uses, but not without a catch—the big danger of being carried away by the hype. It is not as if any business can simply implement some Big Data software and a few procedures to boot and become overnight success, gaining instant competitive advantage. The hype runs in two panes: that big data is a magic wand or panacea for all problems and that big data is too big to fall. Hype notwithstanding, big data implementation involves a few essential steps to ensure its success.
1. Have strategic goals in place.
Success with big data implementation requires a goal-oriented mindset. The big data roll out should be with a definite end in mind rather than merely implementing a new – and apparently good – system. Big data works when it is applied to solve problems; using it as a solution in search of problems is an exercise in futility.
Successful big data implementation requires a strategic plan that encompasses coherent goals, strong processes that govern data and the right attitude. It also requires positioning data as the first priority with a revamp of the existing organizational systems and procedures to make data a central business tenet and the core of the overall business strategy.
2. Ensure Effective Data Governance
It is all very well to hold data in high regard and give it a high place in any strategic document. The hard part lies in the implementation. Ensuring the collection of the right data in the right way is always a hard task.
The success of any big data initiative ultimately boils down to the accuracy of the data fed into the analytical engine in the first place. Data accuracy requires effective data governance measures in place.
A small yet highly empowered cross-functional team of data scientists and engineers combined with strategic business planners focused on overwhelming the organizational systems to ensure that they capture the required data and that the captured data is put to the right use always helps.
3. Assuage Security Concerns
It is all very well that big data analytics provides new insights and path-breaking solutions, but such gains may be pyrrhic if it comes at the cost of privacy, security and failure to ensure regulatory compliance.
Big data roll out would fail without an effective connect between the IT that drives big data and the core business that controls strategy and initiatives and also stands to benefit from the big data analytics. But even with effective connect it would still fail, if the rank and file remain too incompetent to pursue these pointers to their logical conclusions.