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Where big data could really help

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As corporates increasingly harness the power of big data analytics to improve productivity, gain market share and a competitive edge, there are sectors that are lagging behind by not fully capitalising on data to produce actionable insights.
According to Yudhvir Seetharam, head of analytics at FNB Business, global business challenges and developments are putting more pressure on key sectors that are sensitive to economic cycles. As a result, insight gathered from big data can help solve some of the biggest challenges currently facing businesses.
He says there are five sectors in South Africa that should consider incorporating big data analytics into their operations.

Agriculture
The agricultural industry can utilise data predominantly to increase operational efficiency. Faced with drought conditions, South Africa more than ever requires the agricultural sector to optimise what it has, with the assistance of big data.
Seetharam says it is not complex to implement a system that can inform large scale farmers when their equipment needs repairs or fuel. This can be combined with data on weather patterns, soil conditions as well as crops to be planted, to develop a formula to determine the best time and place to plant and harvest. Even the most optimal route to plough the field can be gathered from the insight, leading to increased productivity and revenue.
“Apart from supply side efficiency, farmers can use big data to forecast demand for their crops, yield on their crops, as well as potential land size and usage of the land. This data will significantly help individual farmers when aggregated across geographical regions,” Seetharam says.

Financial services
Financial institutions have  a mountain of data accessible to them via  their customers. This can intelligently lead to better sales and service strategies, within the constraints of responsible usage.
Banks, insurance providers and asset managers can utilise analytics to increase their revenue, decrease costs and increase customer satisfaction and retention.

Healthcare
With the emergence of day hospitals, the healthcare sector is looking for ways of increasing accessibility and affordability while maintaining costs. Once again, big data can be used to determine the best geographic location to place these hospitals, along with insight into trends and potential solutions in medical research.
The prediction of epidemics, assistance in finding a cure for diseases and an overall increase in the quality of living can be extracted with the use of big data.
Seetharam says not only do we have apps and devices that monitor our health, but there are now apps that even assist in self-diagnosis of medical conditions – within reason. This data is pollinated across industries, such as insurance companies, who build health and fitness reward programmes for the clients, and monitor this data through these apps and devices.

Retailers
From a demand perspective, consumers are attracted either to the brand of a retailer, the price of a product, or the necessity of that product. Retailers can take advantage of big data to increase their branding in the minds of consumers with smart marketing strategies, along with positioning of products within their stores.

Franchising
The surfacing of multinational franchises in the fast food and restaurants sector has intensified competition, putting local franchises under pressure. These franchises have been using big data analytics for some time and capitalise on the insights when expanding to emerging economies.
Many local franchises are already visible online and can easily use software to gather actionable insights. Big data can also be useful for franchises expanding into new locations as they can find out where competitors are located, helping them to indentify the best location for a new store.
“Businesses that want to remain relevant and stay ahead of competitors should be using big data. It is no longer a matter of if, but rather when,” Seetharam adds.

  • DataH

    Big data can surely help in every industry today. Many uses of big data have a measurable positive impact on outcomes and productivity. Areas such as record linkage, graph analytics deep learning and machine learning have demonstrated being critical to help in the applications you mention as well as to fight crime, reduce fraud, waste and abuse in the tax and healthcare systems, combat identity theft and fraud, and many other aspects that help society as a whole. It is worth mentioning the HPCC Systems open source offering which provides a single platform that is easy to install, manage and code. The built-in analytics libraries for Machine Learning make it easy for users to analyze Big Data. The free online introductory courses allow for students, academia and other developers to quickly get started. For more info visit: hpccsystems.com