Is big data becoming a major concern for African companies? It is well known that the African continent has been experiencing one of the most dynamic digital growths in the world for several years. The main indicators are steadily increasing as shown in the infographics below. This dynamism coupled with a growing digital transformation of African companies and administrations leads to the production of phenomenal amounts of data.

These data from heterogeneous sources (databases, videos, images, e-mails, etc.) are so voluminous that they are impossible to process using human capacity alone, or using existing conventional database management technologies.

This is paradoxical because data in its most heterogeneous form can be a very valuable resource. How can African companies and public authorities exploit and value their data capital? What are the main types of analysis available?

It is to these questions that we will try to answer through this article.

There is really no precise and/or universal definition of Big Data and associated concepts. We will try to give you simple and practical reference definitions…

Big data, concept & definition

Big Data refers to very large data sets that are difficult to process with traditional database and information management tools. According to Gartner, Big Data is characterized by the 3Vs that define it: Volume, Speed and Variety.

Volume of data to be processed

The astronomical amount of data generated by individuals, companies and communities is constantly evolving, making traditional data processing mechanisms obsolete. Only Big Data technologies can adequately address them.

Velocity of data creation, collection and sharing

With the profusion of digital tools, data is generated, collected and shared at ever-increasing speeds and frequencies.

Variety of information

The diversity and heterogeneity of Big Data are among its most important characteristics. These include texts, e-mails, sms, videos, images, social network feeds, connection geolocation information, etc. The unstructured nature of these types of data makes their integration into conventional database management tools complex, if not obsolete.

Big Data therefore requires new methodologies and technologies for processing these new types of data, with a view to improving understanding and strategic decision-making within companies and public authorities.

Big Data came into being thanks to technological innovations linked to modern data storage (Cloud computing), and to the processing and exploitation of this data (unstructured databases, parallelism, etc.).

Generally speaking, when we talk about Data, we have two main components:

• Data Management: This covers all the modern data exchange platforms and technologies for loading and retrieving data between different systems that companies need to acquire in order to collect and collate data for analysis.
• Data analysis and exploitation (BI & Analytics): Involves all the work involved in designing and implementing data analysis solutions (management, reporting, etc.).

Analytics at the service of companies

The advantage of investing in Big Data for businesses and local authorities is that they can use it to make decisions that will improve their economic and social performance.

The different levels of analysis leading to effective decision making are predictive, prescriptive and analytical…

To illustrate our point, let’s consider the following analytics use cases:

Predictive analysis applied to marketing

Marketing is one of the most mature core businesses in terms of data exploitation. However, the digital transformation within companies is forcing marketing departments to review their concepts. In fact, the diversification of digital channels (social networks, e-commerce site, IoT, …) provides enough data to analyze, enabling a customer profile to be established.

This customer-centric approach maximizes the conversion rate (percentage of prospects becoming customers) by offering the right product, to the right person, at the right time, thanks to predictive analysis.

In addition, predictive analytics also allows marketing departments to significantly lower their churn rates (percentage of customers leaving the company to go to the competition). Telephone operators, for example, use it to understand why some subscribers go to the competition and to save money. Marketing departments are tending to invest in data-driven solutions in order to become more competitive.

Prescriptive analysis applied to human resources management

Through prescriptive analysis, the problems of human resource management could be solved. Workforce Planning has always been a crucial issue for companies. Over- or under-allocation of resources can result in high costs. Analytics can also be used to drive recruitment.

Thus, any emotional or subjective factors will not be taken into account, so recruitment is more efficient. In Human Resources, analytical uses are expanding rapidly. In fact, 3 out of 4 executives believe that steering HR activities based on data analysis will have a positive influence. In this age of digitalized exchanges, the need to use HR Analytics to manage human capital is no longer a fiction, as it provides human resources departments with a tool to solve their daily headaches.

Analytics applied to finance

In order to control the cost of their investments, finance departments are putting considerable effort into retrieving and collating data from disparate sources. In order to carry out simulations on the impact of investments in terms of raw materials or labor, they need a tool that enables them to measure the impact their investments could have on the company’s bottom line.

Analytics is also used to calculate financial statements to determine hypothetical results under different scenarios. To do this, tools such as ETLs (Extract Transform Load) can be used to automate data retrieval, thus considerably accelerating the analysis cycle. In addition, thanks to the BI tools available and the Data Visualization technologies, interactive dashboards facilitate the simulations necessary for cost control. Analytics is evolving and the financial industry needs to keep up with the trend in order to improve performance.

Big Data for African growth

According to Valuates Reports, the global big data and analytics market size was valued at $171.30 Billion in 2018. This huge market is expected to reach USD 512.04 Billion by 2026, growing at a CAGR of 14.80% between 2019 and 2026. That is to say a multiplicative factor of 3 between these two periods.

A better exploitation of mass data produced on the African continent would not only allow to take advantage of this market, to amplify the local impact of innovations but also to amplify in a concrete way the contribution of digital in the growth of the continent (GDP, governance…). Many initiatives and use cases of Big Data and analytics are already underway in many African countries and in many sectors of activity (telecommunication, banking finance insurance, health, tax, transport, tourism, agriculture, citizens, natural resources, commercial activities …). This list is obviously not exhaustive.

Big data is no longer an option for African companies

African companies and public authorities could further improve their ability to collect and exploit the gigantic amounts of data produced locally, in order to take advantage of this enormous market, if measures are put in place to overcome the existing difficulties (massive investment in local data centers, reinforcement of legislation on data sovereignty and protection, creation of training courses specialized in data management, etc.).

The development of Big Data and Analytics is an economic, societal and sovereign necessity for the entire continent. The question is no longer whether to go there, but rather how much to invest?

SQORUS is a Digital Services Company specializing in Council and the modernization of information systems. With more than 240 employees, we have been working for 30 years with a large number of key accounts in various sectors (Banking, Insurance, Industry, Energy, etc.) on strategic and international projects (development strategy, selection assistance, integration, Business Intelligence & Analytics, Data Management, continuous improvement and change management, etc.).

SQORUS now aims to be a trusted partner in the digitization of information systems for African companies via our African subsidiaries.

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