In the digital age, data is growing exponentially across all business sectors. Telecommunications, banking or insurance: more and more companies are collecting information from connected objects, computer networks and social networks.
By connecting to the internet everyone is producing data and the trend is that more and more people are producing data. In fact, smartphones, computers, tablets and other connected objects today collect masses of information that is too bulky to be processed and analyzed. This by human capacity alone or by traditional data management technologies.
The storage and exploitation of this mass of information subsequently led to the emergence of a new application. We speak of “Big Data”. Big Data refers to a very voluminous set of data characterized by their variety and speed of acquisition and which is automatically and massively generated by our electronic devices.
Big Data has become a lever for economic growth. Particularly in the delivery of digital services. Big Data is a source of employment. Especially in the digital professions such as: Traffic Manager, Data Scientist, Web Architect, Web Ergonomist and Web Media Trader.
In the United States and Europe, companies and public institutions have been taking the necessary steps to take advantage of Big Data for several years now. The African continent lags behind in this direction with the exception of certain countries such as: Nigeria, Kenya, Morocco and Egypt.
However, the African continent has been experiencing the most dynamic digital growth in the world for several years now. The mobile phone revolution in Africa alone is an extremely voluminous source of data.
How can Africa leverage and value their data capital?
Big Data can be used to solve many problems in different areas in Africa.
In Africa, sectors such as education, health, agriculture, finance and transport are the main areas where Big Data offers great opportunities.
In November 2013, the Big Data Africa Congress opened in Cape Town, South Africa. That was the first African event dedicated to the popularization of the new concept (Big Data), which is a boon to the world of business and development.
Big Data makes it possible to bring forward models and behaviors from the analysis of data and new data sources in order to predict, improve, automate and innovate.
Big Data therefore requires new methodologies and technologies for processing these new types of data with a view to improving insight and strategic decision-making within companies and governments.
Big Data is at the basis of most of the technologies that are revolutionizing the world today, such as: Cloud Computing, Artificial Intelligence, Machine Learning and the Blockchain.
When we talk about data, we generally have two main components:
• Data management: Covering all modern data exchange platforms and technologies for loading and transferring data between different systems in order to collect and organize data for analysis purposes.
• Data analytics and exploitation: Covers all work involved in designing and implementing data analytics solutions.
The different levels of data analysis leading to effective decision making include predictive and prescriptive. For example:
• For example, with predictive analytics, marketing departments can significantly reduce the percentage of customers who leave the company to go to the competition. Phone operators also use it to understand why certain subscribers go to the contest and to save money.
• This is also the case for insurance companies: who can use predictive analytics, based on the exploitation of mass data, to streamline the processing of policyholder claims and most importantly to identify potentially fraudulent claims.
• In the area of risk management and natural disasters, we can use Big Data and Artificial Intelligence to do modeling and to know which areas are at high risk and which areas will have more disasters than others etc.
• The prescriptive analysis allowed the problems of the personnel management to be solved. Particularly with resource planning which has always been a critical issue.
• In healthcare, for example, collecting, storing and analyzing patient data can reduce response time and predict behavior or symptoms. This will help save lives, restore health and provide much more optimized services.
• Geolocation, with which data on population flows can be obtained to make choices for investment locations. For example, to locate gas stations, roads or hospitals.
• Mobile phone operators also use data streams from their networks to convert them into statistical indicators to analyze the use of geographic areas, population movements, etc.
• In the field of agriculture, Big Data enables the farmer to make the best cultivation decisions and thus optimize his yield thanks to reliable information about the weather and knowledge of the nature of the soil. This makes it possible to practice smart agriculture. Precision agriculture that takes into account reliable climate data.
• Big Data in the agricultural sector can still enable all actors in the agricultural value chain to have high-quality and accurate information to plan the financing or logistics for the distribution of agricultural products. This information can enable the government to carry out, for example, so-called “disaster risk financing”. That is, even before a flood occurs, for example, we are able to estimate the likely risks and allocate the corresponding budget to tackle the phenomenon.
Challenges:
Unfortunately, it is clear in Africa that Big Data is still in an embryonic stage, partly due to a number of major challenges:
• The lack of training of qualified African workers capable of taking advantage of this mass of data
• Lack of data accessibility
• Lack of suitable infrastructure
• Lack of internet access in some corners of the continent
• In addition, many African countries do not have data protection laws.
To meet this challenge, it will be necessary to prepare human resources with a training offer, adapted by an incentive, to learn science and technology from primary education. This is because the implementation of Big Data requires new skills at the intersection of mathematics and computer programming and analysis.
There is also a need to acquire appropriate infrastructures, especially data centers, as Big Data analysis requires a lot of computing power. However, these data centers are hosted in other countries outside of Africa (in the US, in Europe and in Asia) and there are very few of them in Africa. This rather uneven distribution greatly weakens the digital sovereignty of the continent.
Médiatrice Nkurunziza
