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How Big Data is creating opportunities for Africa and the role of the data scientists
According to an article published on CIO East Africa, the rising star and biggest buzz word around the technology community today is ‘big data’, touted by many to be the next untapped ‘natural resource’. But data, like any other commodity, only has real value when it’s refined: in this case combined with enhanced analytics to provide insights that help identify opportunities or develop solutions.
Here in Africa, ‘big data’ has taken a form, somewhat unique to other parts of the world. For the most part, the external data we draw from is generated from a single source - mobile devices. And with more than nine million new mobile subscriptions being added every month across Africa, this represents an exponentially complex array of data available for analysis, prediction, and wide-scale improvement to businesses and human communities alike.
So just how is Africa harnessing the power of big data and analytics today, to tackle some of our continent’s most pressing challenges?
Forecasting a brighter future
Predictive analytics is the common factor in almost every successful Big Data project on the continent thus far. These projects span the widest range of areas possible: from traffic to healthcare, water access to e-commerce.
Take Nairobi and its efforts to reduce congestion and augment public transport services using Big Data and analytics. Together with IBM, the city is considering an approach that will collect and analyse data from the Kenyan capital’s transport grid to predict and identify delays; automatically reroute transport to optimal pathways; and notify commuters via live SMS and mobile app updates – all based on a similar approach developed by IBM for Singapore’s transport network.
However, as Kenya’s infrastructure lacks the coverage of sensors and monitoring infrastructure which the Singaporean system relies on for success, IBM has adapted the Singapore solution by drawing on algorithms and mobile phone data, allowing the base platform to deliver equal – if not better –results. In other words, enhanced analytics techniques have compensated (and may even exceed) for the less-than-optimal hardware conditions in Kenya’s urban environment, accelerating the delivery of benefits for citizens in the process.
The potential to use data and analytics to improve productivity are also immense, and are already being tested in one of Africa’s most critical areas of production: food and agriculture. IBM is exploring how to apply Precision Agriculture to help farmers access this information such as precise weather forecasting down to a particular field on a particular farm via mobile devices to help advise them when to plant, fertilise, irrigate, harvest, and then which methods and routes to transport the produce to market.
Regional grocery store, Nakumatt, is already utilising predictive analytics to determine the buying habits of its customers across East Africa, to better target them with products they desire. The loyalty card that earns these customers points as they shop, also stores and shares information on purchasing trends allowing Nakumatt to target and personalise the offers they make.
A cure to miscommunication
Having access to medication is but one of the many challenges facing Africa. With the contagious diseases that seem to be rife amongst our communities, being able to accurately recognise and quickly effect appropriate management systems to minimise the spread (and subsequent casualties) has proven elusive in many instances. Such management requires many often-disparate organisations and teams to share information and work together.
However, shared data and powerful analytics can not only reveal patterns and trends overlooked by the human eye, but also help predict or identify early where, and when, diseases strike certain populations. By combining new and existing data sets with predictive analytics, Africa’s healthcare industry may find itself able to pre-empt and even prevent outbreaks and clusters of many of the diseases which currently affect the nation.
Just across the Red Sea, the Ministry of Health in Saudi Arabia has already put in place just a solution, having successfully implemented IBM’s cloud-based Panorama public health solution for disease management. This solution provides public health professionals across the Kingdom with a secure, easy-to-use application to collect, share and analyse health information critical in managing public health outbreaks such as SARS, influenza or any other communicable diseases. In turn, it will allow for far better communication among public health professionals and tools when responding to epidemic-prone and emerging disease threats, helping minimise the impact on people’s health and on provincial and national economies.
Apply this to any country in Africa and the impact could be transformational. Apart from the ability to record and forecast immunisations across multiple health centres, communities and regions, the technology can also be used to track the exact location of vaccines to ensure constantly accessible supply –down to their physical locations in hospital refrigerators or clinic supply-rooms. Upon detection of patterns which could indicate the outbreak of a serious communicable disease, the system would alert the appropriate public health officials who could plan and direct actions to protect our most at risk people.
New opportunities for young Africans
As demand from across organisations grows for predictive analytics to help improve decision making, it is becoming increasingly apparent that the skills required don’t necessarily exist today. And according to Gartner, with Big Data demand anticipated to call for 4.4 million jobs globally by 2015, the prediction is that only one-third of those jobs will be filled.
For African people in the workforce today or planning their studies, this represents a massive opportunity. Already IBM is working with a number of universities and institutions to help develop new programs and courses to enable our young people to take advantage of these career paths.
So what skills will be needed to keep steering Africa on a course where we use data and predictive analytics to truly transform the way we live, work and play?
Enter the Data Scientist – new career opportunity that blends art, science and business
One such path that is starting to be discussed is that of a data scientist. More mindset than actual profession, the concept of the data scientist represents an evolution from the business or data analyst role. It places renewed emphasis on the solid technical foundations of computer science, modelling, statistics, analytics and math. But it also requires strong business acumen, coupled with the ability to communicate findings to both business and IT leaders in a way that can influence how an organisation approaches a business challenge. The ideal data scientist does not just address business problems, but selects those that have the most value to the organisation.
The data scientist can be described as “part analyst, part artist.” A data scientist is somebody who is inquisitive, who can stare at data and spot trends. They’re akin to a Renaissance individual who really wants to learn and bring change to an organisation.
Whereas a traditional data analyst may look only at data from a single source – a CRM system, for example – a data scientist will most likely explore and examine data from multiple disparate sources. They’ll sift through all incoming data with the goal of discovering a previously hidden insight, which in turn can provide a competitive advantage or address a pressing business problem. A data scientist does not simply collect and report on data, but also looks at it from many angles, determines what it means, then recommends ways to apply the data.
Instead of individual “data scientists”, we may see teams of specialists who work closely together to fulfil these myriad tasks and objectives around the analysis of data. Or we may see existing business analysts up-skill to incorporate data and predictive platforms into their workflows. But whatever practical form the idea of the data scientist takes, its people will need to be inquisitive: exploring, asking questions, doing “what if” analysis, questioning existing assumptions and processes, and communicating informed conclusions and recommendations to our continent’s business and social leaders.