Big data is a popular business buzzword today, and it signals exciting possibilities in the ability to store deep and complex information and to mine this in a sophisticated manner to reveal key insights into transactional behaviours and patterns.

From business and banking, to health, agriculture and even disaster management, the opportunities to exploit data to benefit business and societies alike appear to be infinite.

There is a dearth of research into Africa’s adoption of big data. More has been written on the huge potential that big data could provide for the continent, especially around social development. In this instance, scenarios have been described about how global funders could access information at the click of a button that would otherwise take months of intensive fieldwork and research (at a considerable cost), to examples of how rural farmers could leverage important agricultural information to manage their resources.

But perhaps we are getting ahead of ourselves. While the potential of big data in Africa undoubtedly opens up opportunities, it should not be viewed as a miraculous tool that will necessarily change the face of business or the development sector. Data must be physically captured and stored before it can be analysed and constructed into meaning. The need for accurate information gathering – from the broad national level in the form of population census (new data lacking in many African countries) to ensuring sustainable technology or mobile-enabled data-collection models at the business level – is still a key link in the chain that ultimately can produce big data sets.

Data analysis

Big data refers to the manner in which data is stored and analysed, once it has been gathered. Using techniques like knowledge management and systems such as Enterprise Resource Planning (ERP) allows for powerful flexibilities in terms of analyses and the prediction of future trends. While traditional datasets consisted of rows and columns of particular information that were essentially sequential and ultimately fragmented like bits of a puzzle, now, using powerful data warehouses, a variety of different data can be stored, including multimedia objects like pictures, voice, spatial patterns, etc. These need not be sequential and the various parts can be integrated to reveal a full puzzle picture.

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