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Richest People in the World: Forbes Billionaires 2024.

Each year, Forbes unveils its highly anticipated list of the world’s billionaires. This ranking doesn’t just highlight wealth—it reveals power, influence, and the shifting currents of global economics. The 2024 list continues this tradition, showcasing the top 20 individuals who stand out across various industries, innovations, and remarkable achievements.

The Forbes Billionaire list offers detailed profiles of these ultra-wealthy individuals, including their net worth, sources of wealth, and notable accomplishments. It covers a range of categories—from self-made entrepreneurs and inherited fortunes to tech giants. Updated regularly to reflect market changes and financial activities, the list gives us a snapshot of global wealth and the major players shaping the financial world.

Inspired by the Forbes list, we created a detailed analysis to dive deeper into the world of billionaires. Our analysis examines not only the top 20 billionaires but also explores wealth distribution by age group, gender, and other relevant categories. By dissecting these elements, we aim to provide a more comprehensive understanding of global wealth trends and the diverse backgrounds of the individuals shaping today’s financial landscape.

Our analysis draws inspiration from these stories, aiming to show more insights into the dynamics of extreme wealth.

Forbes top billionaires in the world.

Here are some insights we picked up from our analysis;

1. Age and Wealth: A Generational Divide;

Examining billionaires by age reveals clear trends. The 60-79 age group holds the majority of global wealth, totaling a staggering $3.3 trillion. This age group represents the peak of wealth accumulation over a lifetime.

Next are the 80-99 year-olds, with a net worth of $1.4 trillion. Their wealth reflects the long-term success of early investments and effective family wealth management. The 40-59 age group, often at their peak earning years, have accumulated $1.3 trillion. Their wealth underscores their crucial role in generating and managing wealth.

2. The Role of Family Dynasties;

Family legacies play a major role in maintaining and growing vast fortunes. Among the top 20 billionaires, four prominent families stand out:

Bernard Arnault & Family: With a combined net worth of $233 billion, the Arnault family is a symbol of luxury and successful family businesses in fashion and retail.

Carlos Slim Helu & Family: The Slim family’s wealth totals $102 billion, highlighting their influence in telecommunications and investments.

Jim Walton & Family: At $78 billion, the Walton family’s wealth showcases Walmart’s retail empire’s lasting success.

Rob Walton & Family: With $77 billion, the Walton family benefits from Walmart’s growth and global reach.

These family dynasties highlight the power of long-standing business ventures and the importance of managing wealth across generations.

3. Gender Disparity: A Persistent Gap

Gender disparity remains a significant issue among the world’s billionaires. Of the 200 billionaires, only 22 are women, making up just 11% of the total. In the top 20, this gap is even wider, with only one female billionaire—Francoise Bettencourt Meyers. This imbalance underscores ongoing challenges in achieving equal opportunities for women in wealth creation and leadership.

While progress is being made, the path to closing this gap is still long and complex.

4. Comparing the Forbes Billionaires Lists: 2023 vs. 2024

It is intriguing to see how the world’s richest people have changed over the past year. Forbes’ billionaires list for 2023 and 2024 offers a fascinating snapshot of these shifts. Here’s a look at who stayed on top, who dropped off, and who made a new appearance.

-People Who Appeared in Both Years:

Several billionaires have managed to keep their place in the top ranks from 2023 to 2024:

Zhang Yiming: Founder of ByteDance maintains his position.

Bernard Arnault & Family: Chairman and CEO of LVMH, continues to lead as one of the wealthiest people globally.

Elon Musk: The CEO of Tesla and SpaceX remains a fixture at the top.

Jeff Bezos: Founder of Amazon stays strong in the rankings.

Bill Gates: The Microsoft co-founder holds his position.

Warren Buffett: The investment guru and CEO of Berkshire Hathaway remains prominent.

Larry Ellison: Co-founder and CTO of Oracle is still on the list.

Mark Zuckerberg: CEO of Meta Platforms retains his spot.

Larry Page: Co-founder of Google remains influential.

Sergey Brin: Also a co-founder of Google, continues to be among the top.

Mukesh Ambani: The chairman of Reliance Industries keeps his place.

Steve Ballmer: Former CEO of Microsoft is still included.

Jim Walton: Walmart heir and Arvest Bank chairman remains on` the list.

Alice Walton: Walmart heiress stays prominent.

Rob Walton: Another Walmart heir is still featured.

Françoise Bettencourt Meyers & Family: L’Oréal heiress continues to be in the top ranks.

Michael Bloomberg: The founder of Bloomberg LP is still on the list.

A few notable billionaires did not make the list in 2024. These include:

Sam Walton: The Walmart founder, whose descendants still feature, is no longer in the top 20.

S. Robson Walton: Another Walmart heir who was listed in 2023 but did not appear in 2024.

-New Faces in 2024

Several new billionaires have emerged in 2024 who weren’t on the 2023 list:

Carlos Slim Helú & Family: The Honorary Chairman of América Móvil joins the list this year.

Amancio Ortega: The founder of Inditex (Zara) makes a new appearance in the top 20.

The Forbes 2024 Billionaires List offers a fascinating glimpse into how wealth is shaped by age, family legacies, and gender.

But what do you think? Are there any trends or stories that surprised you? Share your thoughts and join the conversation in the comments below!Want to read more reports? Check out our Top Billionaires in Africa Blog post.

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Breaking Down the Most Streamed Songs on Spotify.

Music has always been a universal language, connecting people across cultures and generations. In today’s digital age, the way we consume music has changed drastically. Gone are the days of cassette tapes and CDs. Now, streaming platforms like Spotify are where we discover new tunes, revisit old favorites, and share our playlists with friends.

Among the millions of tracks available on Spotify, certain songs have risen to the top, becoming the most streamed songs of all time. But what makes these tracks so special, and why do they resonate with so many listeners?

Our Spotify analysis takes a closer look at some of the most streamed songs on Spotify. We’ll explore the artists behind these hits, the stories they tell, and why these songs have become anthems for people around the world.

The New Way We Experience Music

Before we dive into the list, it’s worth noting why streaming has become such an important part of the music industry. Spotify, which launched in 2008, has grown into one of the biggest music streaming platforms in the world, with over 500 million active users. Unlike traditional radio or album sales, streaming allows listeners to access virtually any song, anytime, anywhere. This convenience has made it easier than ever for songs to reach massive audiences, with some tracks racking up billions of streams.

Streaming data also reflects what’s popular in real time. Unlike album sales, which could take weeks or months to build up, streams are counted the moment someone presses play. This immediacy has led to the rise of viral hits that dominate the charts for weeks or even months.

So, what are these most streamed songs that have captured the hearts and ears of millions? Let’s take a look at a few of them:

  1. “Blinding Lights” by The Weeknd

It’s no surprise that The Weeknd’s “Blinding Lights” tops the list. Released in 2019, this song became a defining track of the early 2020s. It was released in November as the second single from The Weeknd’s fourth studio album, After Hours. It spent four weeks at No. 1 on the Billboard Hot 100 and was the first song to remain in the chart’s top 10 for an entire year.

According to Variety.com, The weeknd’s “Blinding Lights” is the first song to pass the 4 billion stream mark on Spotify. The Weeknd’s smooth vocals paired with the song’s upbeat tempo make it a track that you can’t help but move to. “Blinding Lights” has also been featured in countless TikTok videos, further boosting its popularity and earning it billions of streams.

2. “Shape of You” by Ed Sheeran

Another mega-hit is Ed Sheeran’s “Shape of You” . Released in 2017, this catchy tune quickly became a global sensation. Its blend of pop and dancehall rhythms, combined with Sheeran’s smooth vocals, made it an instant hit.

The song’s lyrics, which tell the story of a blossoming romance, are simple yet relatable, making it a favorite for many listeners. As of now, “Shape of You” has over 3 billion streams on Spotify, cementing its place as one of the most popular songs of all time.

3. “Someone you love” by Lewis Capaldi

When Lewis Capaldi released “Someone You Loved” in 2018, he might not have anticipated just how deeply the song would resonate with listeners around the world. What started as a simple ballad quickly catapulted Capaldi from being a relatively unknown artist to an international superstar. With over 3.4billion streams, the song explores the themes of love and loss which are what almost everyone can relate to.

Capaldi’s ability to tap into these universal emotions is what makes the song so powerful.

4. “Sunflower” by Post Malone and Swae Lee

Released in October 2018 as part of the soundtrack for the animated film Spider-Man: Into the Spider-Verse, the song quickly became a sensation, resonating with listeners of all ages. Today, “Sunflower” stands as the 4th most streamed song on Spotify, with over 3.4 billions plays.

One of the key factors behind the success of “Sunflower” is its connection to Spider-Man: Into the Spider-Verse. The film, which was a critical and commercial success, introduced the song to a wide audience. The song’s placement in the movie’s opening scenes made it an instant favorite, and it became the unofficial anthem for the film.

5. “As It Was” by Harry Styles

“As It Was” marked a new chapter in Harry Styles’ career, showcasing his evolution as an artist. It quickly captured the attention of fans and critics alike. The song’s infectious melody, and nostalgic sound have made it one of the most streamed songs on Spotify, earning it the impressive title of the 5th most streamed song on the platform with 3.3 billion streams as at the time of this report.

6. “Starboy” by The Weeknd

Featuring French electronic duo Daft Punk, “Starboy” was the lead single from The Weeknd’s third studio album of the same name. With over 3.3 Billion streams, the seamless fusion of The Weeknd’s soulful vocals and Daft Punk’s legendary electronic soundscapes propelled “Starboy” to the pinnacle of charts worldwide, including the coveted top spot on the US Billboard Hot 100.

7. “One Dance” by Drake ft Wizkid

Drake’s “One Dance” is a track that needs no introduction. Released in 2016 as part of his fourth studio album, Views, “One Dance” quickly became a global sensation, dominating charts and dance floors alike. Featuring Nigerian artist Wizkid and British singer Kyla, the song blends elements of dancehall, Afrobeats, and pop, creating a sound that transcends borders.

With 2.2 Billion streams as at the time of this report, we can all agree that its catchy chorus has earned it the title of the 7th most streamed song on Spotify.

8. “Stay” by The Kid LAROI & Justin Bieber

With over 3.1 billion streams and counting, “Stay” by The Kid LAROI and Justin Bieber has secured the 8th position on the list. Released in July 2021, this collaboration quickly skyrocketed to the top of the charts and becoming a global anthem.

Part of what makes “Stay” so special is the collaboration between The Kid LAROI and Justin Bieber. The Kid LAROI, an emerging star from Australia, had already begun making waves in the music industry and we can say that teaming up with Justin Bieber, a seasoned superstar with a global fanbase enhanced the success of the song.

9. “Dance Monkey” by Tones and I

This breakout hit from the Australian singer-songwriter Toni Watson, known professionally as Tones and I, captured the world’s attention when it was released in May 2019. The song’s rapid rise to fame was nothing short of extraordinary, raising her from a street performer to an international pop star almost overnight. The track quickly topped the charts in over 30 countries and broke records in the process, staying at number one in several countries for weeks on end.

As the 9th most streamed song on Spotify, with over 3.1 Billion streams as at the time of this report, we can all agree that “Dance Monkey” has cemented its place in music history.

10. “Believer” by Imagine Dragons

With a staggering 3.0 billion streams, “Believer” by Imagine Dragons has cemented itself as one of the most impactful songs of the past decade, earning its place as the 10th most streamed song on Spotify. Released in February 2017 as the lead single from their third studio album Evolve, “Believer” quickly became a global sensation.

The song’s energy is infectious, making it impossible not to feel a rise of adrenaline when listening.

What These Songs Tell Us About Modern Music

The success of these tracks isn’t just about catchy melodies or viral moments it also reflects broader trends in music and culture. For one, these songs show the growing influence of global sounds in mainstream music which we can see from Ed Sheeran’s use of dancehall rhythms to The Weeknd’s ‘80s-inspired beats, artists today are drawing from a wide range of influences to create something new and exciting and we love to see it.

In the end, the most streamed songs on Spotify aren’t just hits they’re the tracks we return to time and again, not just for their catchy tunes, but for the way they make us feel. And that’s what makes them truly timeless.

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How To Make Money On Upwork as a Data Analyst.

Freelancing has become a popular option for Nigerians looking to make money online, with platforms like Upwork opening doors for professionals across various fields. If you’re a Data Analyst wondering if you can tap into this opportunity, the answer is a resounding yes! Upwork connects freelancers with clients seeking diverse services, including Data Analytics.

In this article, we’ll explore how you can make money on Upwork as a Data Analyst, providing you with practical tips and strategies to succeed on the platform.

Overcoming Misconceptions and Doubts About Freelancing

Freelancing on Upwork often face misconceptions, with one of the most prevalent being that it is not a “real job”. Many people believe freelancing lacks the stability and seriousness of traditional employment. However, freelancing is a legitimate career path that offers flexibility and the opportunity to work with diverse clients across various industries. To overcome this misconception, freelancers should treat their work with the same level of professionalism and dedication as any traditional job.

What is Upwork and How Does It Work?

Upwork is a freelancing platform where clients post projects, and freelancers bid on these projects to get hired. It covers a wide range of services, including Data Analytics, Writing, Graphics Design, Content Writing, Programming, and more. 

Here’s how you can get started on Upwork:

1. Create a Profile: Sign up for a free account and create a detailed profile. Highlight your skills, experience, and what you can offer as a data analyst. Make sure to include any relevant certifications or job experience.

2. Get Hired and Deliver Quality Work: Once a client selects you, ensure you communicate effectively and deliver high-quality work on time. Satisfied clients are more likely to give you good reviews and repeat business.

3. Browse Projects: Search for projects that match your skills. Use keywords like “data analysis,” “data visualization,” “Excel,” “Python,” or “SQL” to find relevant jobs.

4. Submit Proposals: When you find a project you’re interested in, submit a proposal. Tailor each proposal to the specific job, demonstrating how your skills and experience make you the best candidate. Be clear, concise, and professional.

Understanding the Competitive Landscape on Upwork

Upwork is a competitive marketplace, and it is important to understand the platform before diving in. Researching and analyzing the profiles of successful Data Analysts on Upwork can provide valuable insights into their strategies and help you identify areas where you can stand out.

Tips for Succeeding as a Data Analyst on Upwork

1. Build a Strong Portfolio: Your portfolio is your showcase. Include case studies, previous projects, and sample analysis. Show potential clients the value you can bring to their projects.

2. Optimize Your Profile: Use a professional photo and write a compelling bio. List all relevant skills, software proficiencies, and any certifications you have. The more detailed and polished your profile, the more likely clients will consider you for their projects.

3. Start Small and Build Your Reputation: Initially, you might need to accept lower-paying jobs to build your reputation on the platform. Focus on delivering excellent work and getting positive reviews. As your profile grows, you can start bidding for higher-paying projects.

4. Network and Stay Active: Join Upwork groups and forums related to data analysis. Engage with other freelancers and potential clients. Staying active and visible on the platform can lead to more opportunities.

5. Continuous Learning: The field of data analysis is constantly evolving. Stay updated with the latest tools, techniques, and industry trends. Consider taking online courses or earning certifications to enhance your skills and marketability.

Begin your Data Analytics Journey here

Potential Gig Ideas for Data Analysts on Upwork

1. Data Cleaning and Preparation: Offer services to clean and prepare raw data for analysis. Many clients have datasets that need to be organized and formatted correctly.

2. Data Visualization: Create visually appealing and informative charts, graphs, and dashboards using tools like Tableau, Power BI, or even Excel.

3. Statistical Analysis: Perform statistical analysis , help clients understand trends, correlations, and insights from their data.

4. Business Intelligence Reporting: Develop comprehensive business intelligence reports that help companies make data-driven decisions. Familiarity with tools like Power BI or Looker can be a plus.

5. Predictive Modeling: Build predictive models to forecast future trends. This could be useful for clients in finance, marketing, or any field that relies on forecasting.

Succeeding on Upwork as a Data Analyst is not only possible but also rewarding. By creating a strong profile, building a solid reputation, and continuously improving your skills, you can tap into the growing demand for Data Analytics services. Start by setting up your Upwork account, exploring potential gigs, and putting your best foot forward in every project. 

Happy freelancing!

Click here to join our Dataleum Tech community.

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HOW I FELL IN LOVE WITH DATA ANALYTICS

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

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!