Big Data Analytics
Oracle White Paper (2014) described data analytic as the systematic computational analysis of data or statistics, by extracting knowledge that can commercially be exploited in some form. Whereas, Issues Paper (2013) said that Big Data Analysis provided profound insight into a number of key areas of society including health care, medical and other sciences, transport and infrastructure, education, communication, meteorology and social sciences. The Paper also highlighted the key areas that Big Data Analytic may influence included the data management, personalisation of services, problem solving and predictive analytics, productivity and efficiency. The Paper further stressed that a successful Big Data Strategy was expected to assist in realising each of the priority areas observed in the ICT Strategy such as the delivery of better services, improved efficiency of Government operations, and open engagement. Wayne, R. (2011) explained that organisations embarking on an enterprise data strategy needed a broad-based portfolio data management tools to support various data integration and quality tasks and automate processes where possible. Actually, the Wayne, R. (2011) emphasised that executive must recruit business managers and analysts to formulate and oversee a data strategy, define rules, policies and procedures to maintain the accuracy, completeness and timeliness of critical data elements, and partner with IT to execute the programme.
Actually, Peason,T., at el. (2013) narrated that early adopters of Big Data Analytics had gained a significant lead over the rest of the corporate world. He reported that more than four hundred (400) large companies examined were found that those with the most advanced analytics capabilities were outperforming competitors by wider margins. He vividly outlined the four (4) areas where analytics could be relevant and these included: improving existing products and services, improving internal processes, building new products or service offerings, and transforming business models. He also expressed that Big Data leaders work on developing a horizontal analytics capability by learning how to overcome internal resistance, and create both the will and the skill to use data throughout the organisation. He further cited some prosperous firms such as the Nordstorm which elevated responsibility for analytics to a higher management level in its organisation, pushed to make analytical tools and insights more widely available and embedded analytics-driven goals into its most important strategic initiatives. The other example is about the electronic company which added incentives for senior executives to tap Big Data capabilities, and firm’s leadership had reinforced that approach with a steady drumbeat of references to the importance of analytics in delivering business results.
In view of the above, Carl, W. O. at el., (2012) argued that the Big Data Analytics was not new, but what has changed was the awareness that analytics could create competitive advantage if the right information was provided to the right decision makers at the right time using the right tools.