Big Data is now the next big thing, expected to change everything about how businesses understand their customers, generate strategy, and go to market. While there is certainly a great amount of hype, Big Data and the associated technologies and tools do bring a lot of value to most organizations, and in many cases transformative impacts.
First though, it is important to understand that Big Data does not mean the same thing to every organization, and therefore the benefits of Big Data processing may be very different from organization to organization. While Big Data refers to very vast datasets that are being generated at high speeds, there is no one consensus on how big is “Big”. For any organization, the point at which existing infrastructure is not able to handle the volume of data being generated and needs to be stored is really when it needs to start looking at technology that can handle much higher volumes of data. Big Data is also not just about volume, it’s also about variety – data that is being collected is much more than transactional data, it could include a wide variety of data points like customer reviews in text formats, facebook likes, and images and videos. Traditional database systems are not built to handle data that is in unstructured format, and so newer Big Data technologies are required to handle non-traditional data.
So how can Big Data tools help organizations? First, the speed at which analysis is performed and insights are generated can be increased dramatically, with real time analysis as opposed to retrospective analysis. This is enabled by sophisticated new Big Data technology that allows much faster querying and processing of even extremely large datasets
Second, Big Data analysis outcomes are much more powerful because they are generated using a much wider set of information that includes more than the traditional data contained in transactional databases. For example, in healthcare, doctors are increasingly able to generate evidence based treatment programmes that not only take into account previous medical history of a patient but also such data as daily fitness activities and diet components over time.
Third, Big Data algorithms and analytics have increased predictive accuracy because of a fundamental shift in approach that has been enabled by the availability of vast volumes of data. The new approach to predictive analysis is based on Bayesian statistics, which essentially allows analytical algorithms to constantly improve accuracy based on newer data.
There are many examples of Big Data success stories and Big Data enabled high impact strategies across organizations across many sectors and industries. While large companies have been quick to embrace Big Data and have invested heavily in Big Data programmes and manpower, in anticipation of big returns, even smaller organizations should plan and generate a Big Data strategy to survive and thrive in an increasingly data driven environment.