Africa’s Richest: Who Topped the List in 2024?

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Every year, the Forbes Africa Billionaires List provides a glimpse into the wealthiest individuals on the continent.

Based on this, we have created a report that reveals the net worth of Africa’s richest people and also offers insights into the sectors driving economic growth and the countries fostering these financial giants. Following the trends revealed in this report, we can derive valuable insights into Africa’s economic future. Africa has so much potential, and the next generation of billionaires could come from surprising sectors and regions.

REPORT OVERVIEW

For 2024 top 20 billionaires, their combined net worth has risen to $82.4 billion, a 2.36% increase from last year’s total net worth of $80.5 billion. This report shows an increase of $1.9 billion compared to 2023, a positive sign for Africa’s economic trajectory. 

Interestingly, the average age of these billionaires also sits at 69.6 years. This year, South Africa claims six spots on the ranking, followed by Egypt with five and Nigeria with four. Algeria, Tanzania, and Zimbabwe have one billionaire on the list each, while Morocco has two.

These billionaires cut across different industries, including; the Manufacturing industry ($22 billion), the Metals & Mining industry ($14 billion), the Fashion & Retail Industry ($11 billion), the Construction & Engineering Industry ($9 billion), and the Telecom Industry ($6 billion). It also sheds light on the rise of billionaires in the Media & Entertainment Industry, the Finance & Investments Industry, Food & Beverage (at $3 billion each) and the Energy Industry ($1 billion).

This diversification is a positive sign for the continent’s economic stability, indicating a move away from reliance on a single sector.

NET WORTH BY LOCATIONS

South Africa holds the top spot with a $29 billion combined net worth (including billionaires from South Africa and Zimbabwe), followed by West Africa with a combined net worth of $28 billion – with 4 billionaires from Nigeria). In addition, North Africa holds its billionaires with $24 billion spread across Egypt, Algeria, and Morocco. Lastly, East Africa has the least wealth concentration with only one billionaire from Tanzania.

HIGHLIGHTS FROM THE REPORT

  1. Femi Otedola’s Return

The 2024 list welcomes back a familiar name – Femi Otedola of Nigeria. Otedola’s strategic shift from oil (Forte) to power generation (Geregu)  positions him back on the list, as Nigeria’s newest billionaire landing him the 20th spot with a net worth of $1.1 billion.

2. The Brotherhoods of Egyptian Wealth

In the landscape of African billionaires, Egypt boasts two prominent brotherhoods with great financial strength; The Sawiris Brothers and the Mansour Brothers.

  • The Sawiris Brothers

Leading the charge are the Sawiris Brothers, Naguib Sawiris and Nassef Sawiris. With a combined net worth surpassing billions, they have diversified their investments across various sectors. Naguib Sawiris, with a  $13.8 billion fortune. Meanwhile, Nassef Sawiris, with an impressive $8.7 billion in wealth.

  • The Mansour Trio

Egypt continues to be a breeding ground for wealth. Adding a touch of family wealth, Egypt also boasts three billionaire brothers who solidify the nation’s presence on the list. On the list we have, Youssef Mansour ($1.3 billion), Yasseen Mansour ($1.2 billion), and Mohamed Mansour ($3.2 billion). 

  1. Dangote Retains the Crown

Perhaps, the most consistent presence on the list is Aliko Dangote of Nigeria. Dangote retains his title as Africa’s richest person, securing the number one spot for a record-breaking 13th consecutive year. His net worth increased to $13.9 billion, solidifying his position as a dominant figure in the African industry.

4. The biggest and lowest gains

The list also showcases the biggest and lowest gains. Nassef Sawiris from Egypt enjoyed the biggest gain, adding a significant $1.5 billion to his net worth, thanks to a rise in Adidas shares (which he partly owns) and dividends from his family conglomerate. On the other hand, Algerian industrialist Issad Rebrab experienced a substantial decline of 45.65%.

5. Highest Billionaires: South Africa boasts the highest number of billionaires (6), showcasing a diverse pool of wealthy individuals. However, Nigeria tops the list in terms of total wealth value with its 4 billionaires. This highlights the economic potential within both regions.

A LOOK AHEAD

The 2024 Africa Billionaires list paints a promising picture of Africa’s economic landscape.  With a growing pool of diverse billionaires and a focus on sectors beyond traditional resources, Africa will experience continued financial growth. As we move forward, it will be interesting to see how these trends evolve and which new names emerge on the 2025 list.

Will the number of billionaires increase significantly in the next few years?

Which sectors will emerge as new breeding grounds for wealth creation?

Share your thoughts with us!

Florence Nightingale- First Woman to Pioneer Data Visualization

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In the spirit of Women’s History Month, it’s time to spotlight Florence Nightingale, a remarkable woman whose impact transcends generations.

While many know Florence Nightingale as the caring nurse who tended to wounded soldiers during the Crimean War, Nightingale also contributed to the innovative use of data visualization. This blog post discusses how the famous nurse Florence Nightingale used charts to demonstrate her life-saving work to her target audience.

Did you know that Data Visualization has it origins in military healthcare reforms?

Going Down Memory Lane…

Born in 1820 in Florence, Italy, Florence Nightingale defied societal expectations to pursue her passion for nursing. Despite facing numerous obstacles, she became known as “The Lady with the Lamp” for her dedicated care of soldiers during the Crimean War, earning widespread admiration for her compassion and dedication to healing.

While Nightingale’s nursing skills were widely recognized, her approach to addressing healthcare challenges went beyond the patients’ bedside. Recognizing the dire conditions in military hospitals and the alarming mortality rates among soldiers, Nightingale turned to Data Analysis to understand the root causes and drive meaningful change.

Amidst the chaos of war, Nightingale devised a method of Data Visualization—the Rose Chart.

The Famous Florence Nightingale Rose Chart.

This innovative chart transformed complex statistical data into a visual representation, illustrating the leading causes of soldier mortality during the Crimean War. With each segment of the chart representing a different cause of death, Nightingale effectively communicated the urgency of sanitary reform in military hospitals to policymakers and the public.

Nightingale’s use of the Rose Chart wasn’t just about presenting numbers; it was a call to action. With visual evidence, she advocated for improvements in sanitation, nutrition, and healthcare infrastructure, ultimately revolutionizing military medicine practices and saving countless lives.

Female Inlusivity in Data Analytics.

This is a throwback to 1854, but this woman’s move still stands the test of time. During Women’s History Month, we celebrate Florence Nightingale’s legacy in both nursing and statistics. Her innovations paved the way for future generations of women in healthcare and STEM fields, inspiring us to continue advocating for gender equality in all spheres of life.

In Data Analytics, ringing the bell for gender equality is not only necessary but also essential for driving innovation and progress. Much like Florence Nightingale pioneered the use of data visualization to advance healthcare, we must champion diversity and inclusion in the data field to ensure that all voices are heard and all perspectives are considered.

Just as Nightingale’s groundbreaking work transformed healthcare practices, promoting gender equality in the data field can lead to groundbreaking insights and solutions. By embracing diverse perspectives and experiences, we can uncover biases, identify overlooked trends, and develop more inclusive and equitable strategies for leveraging data.

If you’re interested in enhancing your visualization skills to effectively communicate data insights, consider enrolling in our Data Analytics Mastery course. Whether you’re a beginner or seeking to become an advanced professional, our course will refine your abilities in this critical field.

We not only teach the technical skills needed to excel in the field but also emphasize the importance of diversity and inclusion. By creating an environment where everyone feels valued and empowered to contribute.

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HOW I FELL IN LOVE WITH DATA ANALYTICS

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Discovering a passion for data analytics isn’t just a career choice; it’s a love story in itself. In our conversation with Joseph Eriwha, Head of Business Development at Maison Atlantic,  we explore how he found himself captivated by the power of data analytics. His story of how data analytics became a vital tool in reviving businesses is a tale worth sharing.

ABOUT JOSEPH ERHIWHA

Holding a bachelor’s degree from Middlesex University, majoring in Information Technology and Business Management Systems, I would classify myself as a seasoned business development expert with a wealth of experience in converting strategic plans into achievable business goals. In over 8 in business development, I have explored various industries and sub-sectors in the technology, power, logistics and hospitality space.

Connect with Joseph Erihwa on LinkedIn.

Was it love at first sight with Data Analytics?

For short, the answer is yes. So I’ve been in business development for eight years in various sectors from financial technology, health technology, logistics technology, information technology and the like. 

And the first time I saw Data Analytics, I saw the influence it has on internal business processes. It has a lot of focus on internal business processes, more than the conventional tools that we use as business development officers which include SWOT analysis, Porter 5 forces, PESTEL and the like.  It takes into account external factors that we an organisation do not have control over such as your competitors, and force measure. So yeah, I would really say with Data Analytics it was love at first sight.

What sparked your interest in Data Analytics initially?

So I used to be the sales manager for what I will call the biggest telemedicine platform in Nigeria and we saw that we were not really making a lot of growth in terms of customer base. So we had to crunch our numbers to also see the types of people that we have (types of enrollees) on our platform. We saw that the majority of them were working class, and we were able to switch our business model because we utilised Data Analytics.

We were able to switch our business model from B to C to B to B, and easily forecast our financial numbers,  also the enrolees base we plan to have within the year, which was easier to do with B2B. So that streamlined our sales activities to achieve individual organizational goals.

Can you share a memorable project or experience that solidified your passion for Data Analytics?

Yes, let me use my most recent place of work, somewhere I currently consult for. It’s in the logistics technology sector and I’ve been able to utilise Data to understand our high-traffic areas, high-traffic customers, the form of demographic and also the psychographic data on why they purchase our products. That way we’ve been able to push our energy to areas that we have a lot of others coming from.

So we are going to have better customer service in terms of speed, pricing and pick up time. It has affected affected our business positively. So instead of just using our numbers or our efforts to capture the whole of Lagos, we try to streamline it to various geographic locations.

In our case, we are using local governments as a basis to look at how to grow our numbers and that is working for us instead of just having scattered sales activities around Lagos.

How has your love for Data Analytics influenced your career and personal growth?

Well, to be honest, I will say it has affected me. In the past, in some of my past activities, we’ve utilised the services of what we call data analysts consultants, people who are not under the payroll but are at our beck and call, based on request.

Now having that skill at hand gives me an edge in the market because most business development officers I know have no knowledge about data. So it gives me an edge because of that skill set. Being able to analyse businesses, the strengths and weaknesses of businesses based on the data they’ve gathered. So informed decisions are made better.

What is your favourite thing about being an Analyst?

I would say it’s something people shy away from, but data cleaning is very important. From my personal experience, just to give you a rough estimate might not be the exact numbers, but roughly about 90% of the time I spend with data analysis is on data cleaning.

You have to have clean data to have accurate results. So spending a lot of time on data cleaning, it’s it’s I think has been my core strength. It’s something I’m still developing because there’s room for growth, but it’s my core strength currently as a Data Analyst. Utilising Excel and PowerBi, I’m currently working on that for SQL and it’s going pretty great so yeah!

We hope you enjoyed reading this article as much as we enjoyed writing it. Our discussion was truly enlightening, emphasizing the incredible potential of data. It’s amazing to see how data can change lives and revolutionize business practices.

If you’re eager to share your own experiences with data analytics, send us a message! We’d love to hear from you.

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Free Datasets for your next project

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Whether you are adding a data project to your portfolio or you’re starting your first project as a paid Data Analyst, your first task will be to find a suitable data set. In this article, we’ll go over the basics of what a data set is, how to find them, and ways to determine their quality.

So, what is a Data Set?

A data set is simply a collection of information. Usually, datasets are not always organized in a way that is immediately useful, and it will need a bit of work on your part to make it usable. Datasets can come in various forms, such as spreadsheets, databases, JSON files, or even text files. They serve as the foundation for Data Analytics and visualisation.

So where do you find them?

In this article, we’ll highlight a few repositories where you can find data on everything from business to finance and even crime.

Kaggle

Kaggle is one of the largest platforms for data science and machine learning competitions. It hosts a vast repository of datasets across a wide range of topics, including healthcare, finance, social sciences, and more.

   – Type of data: Various types of datasets, including structured, unstructured, and time-series data, covering topics such as healthcare, finance, natural language processing, computer vision, and more.

  – Access: Users can access datasets through the Kaggle platform by creating a free account and browsing the dataset repository. Some datasets may require participation in competitions or adherence to specific terms and conditions.

UCI Machine Learning Repository

The UCI Machine Learning Repository is a collection of databases, domain theories, and datasets widely used by the machine learning community.

   – Type of data: Datasets suitable for machine learning research and experimentation, including classification, regression, clustering, and recommendation systems.

   – Access: Datasets are freely available through the UCI Machine Learning Repository website. Users can browse datasets by category, view dataset descriptions, and download data files in various formats.

Data.gov

Data.gov is the official open data portal of the United States government, providing access to a vast array of datasets from federal agencies.

   – Type of data: Governmental datasets from federal agencies covering diverse topics such as demographics, economics, healthcare, environment, public safety, and more.

    – Access: Datasets are accessible through the Data.gov portal, where users can search, browse, and download datasets for free. Data.gov promotes transparency and collaboration by providing open access to government data.

Google Dataset Search

Google Dataset Search is a specialized search engine developed by Google to help users discover datasets across the web.

-Type of data: A wide range of datasets from various sources, including academic repositories, data providers, government agencies, and research institutions.

   – Access: Users can search for datasets using keywords, topics, or data formats through the Google Dataset Search website. The search results provide direct links to the source repositories or websites hosting the datasets.

GitHub

GitHub is a popular platform for software development, collaboration, and version control.

   – Type of data: Datasets shared by researchers, data scientists, organizations, and communities on the GitHub platform, covering diverse domains and topics.

   – Access: Datasets are accessible through GitHub repositories tagged with “dataset” or by searching for specific datasets using keywords. Users can explore repositories, view dataset files, and download data for free.

Are these quality datasets?

Determining the quality of a dataset is crucial for ensuring the reliability and validity of your analysis. Here are some factors to consider when evaluating dataset quality:

  1. Research the source of the data and the methods used for its collection.
  2. Confirm whether the dataset contains all the necessary variables and observations required for your analysis. Incomplete datasets may lead to biased or inaccurate results.
  3. Verify the accuracy of the data by cross-referencing it with other reliable sources or conducting validation checks.
  4. Ensure consistency in data formatting, units of measurement, and coding schemes across the dataset.
  5. Evaluate the relevance of the dataset to your specific research question or analytical objectives.

After choosing a suitable dataset, the next step is to clean, visualise and generate insights. You can learn how to do that by registering for our next training here.

Comment if you want a part 2 with more sites to check out!