Big Data doles out big opportunities and organizations of all kinds are excited about the revolution that it has spurred in such less time. Analytical results derived from real-time, swift data can drive business performance in ways unheard of before. So much so, that McKinsey calls big data “the next frontier for innovation, competition, and productivity” in one of its reports in 2011.
Although there is a lot of fervor about big data, the concept is new, and most people are still unsure of what it exactly means. We found the following myths clouding the concept:
Using big data requires fancy technology
While big data does require the right technologies, what is more important is having the right organizational culture. Organizations that adopt big data in a competitor-driven frenzy without clear objectives and a robust approach hardly get the returns on their investment. The main role that technology plays is to enable smart decision making using big data.
- It is easy to quantify the benefits that accrue from big data-Not true again. Everyone in the organization may not understand the implications and findings that derive from analytics.
- Big data is definable-The truth is, there is no clear cut definition of big data. It is a cross-sectional bundle which takes data from various disciplines. Big data scientists have lots of things to say about it, and the concept encompasses all, which makes it rather ambiguous at this point in time.
- Big data is a new concept-Big data has been around for quite a while. It is just that organizations are realizing its potential now that some of them have harnessed benefits from using it.
Big data is expensive
A very common myth. The truth is that even small and medium sized organizations can leverage the power of big data. The only challenge lies in finding skilled people for this task, as there is still a dearth of experienced professionals who can handle and derive analytical results from big data.
These apart, there are lots of myths and questions that surround the true picture of big data. As it matures further, new myths will be found and busted along the way.