Dashboard Insights: Analyzing Billionaire Trends with Cognos

Assignment №4 – Dashboard and Story Development Using Cognos Analytics University of Maryland Global Campus DATA 610 – Decision Management Systems – Fall 2023 Assignment №4 – Dashboard and Story Development Using Cognos Analytics Lovet Anye fru - lanyefru@student.umgc.edu Laila Moretto November 21 st , 2023

Dashboard and Story Development Using Cognos Analytics The billionaire dataset is a precious resource, regardless of the current unpredictable state of the global economy. This paper will analyze the data by creating dashboards and developing stories that provide insights into successful billionaires and identify patterns in their activities across different countries and over time. The dataset includes rankings of billionaires over several years, their net worth, industry and personal traits, the contributing company, and how each billionaire became ultra-rich. All variables and descriptions are presented in a table, making it easy to navigate and explore (see Table A). The dataset contains 2,615 rows of data, which can be observed in a partial screenshot (see Figure 1); it was sorted in descending order to show the last observation row. Figure 1 Snapshot of dataset Dashboard Presentation and Discussion Upon analyzing the billionaire's data, some critical insights were found and visualized using IBM Cognos Analytics. The top ten billionaires were visualized by plotting the name column against the rank column and filtered using the year column. Depending on the year selected in 2

the filter, the bar chart shows the top ten billionaires, with rank one being the highest ranking (see Figure 3). Furthermore, a definite chart visualizes the primary source of wealth, and the pie chart shows the various wealth sources and the distinct count of billionaires in each category. It can be concluded from the pie chart that most billionaires inherited their wealth (see Figure 4). Besides the source of wealth, looking into the sector with the most investment, based on the sum of worth in billion columns, a bar chart provides the top ten most affluent sectors. The wealthiest real estate sector is worth 618 billion (see Figure 5). Another insight into the wealthiest industry is based on the sum of worth in billions for each sector; the bar chart below provides the top ten most affluent industries. The consumer industry is the wealthiest (see Figure 6). Next, we look at an insight into the representation of all the countries where billionaires hold citizenship was visualized using a map; green color was used to represent the countries with billionaires, with the intensity of the color showing the level of available billionaires; the darker the color of the country on the map, the higher the billionaires with citizenship in that country. The USA has the highest number of billionaires with citizenship (see Figure 7). Also, it was interesting to see the growth of the billionaires over time. Using a line chart to visualize the trend of billionaires’ worth over the years, the graph shows that billionaires' wealth has increased over the years (see Figure 8). Looking into the age of billionaires by age count, the column chart shows the number of billionaires in a specific period. This provides insight into the age range of most billionaires (see Figure 9). 3

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From the age of the billionaires, it is also essential to see the gender numbers. Looking into the gender of the billionaires, a pie chart was used to visualize the division, and most of the billionaires are male (see Figure 10). Finally, it is worth highlighting that the decision tree suggests a strong positive correlation between the GDP and "worth in billion" columns. This finding could have significant implications for understanding how wealth is generated in different countries and industries. It may be worth exploring this relationship further to gain deeper insights into the factors that drive economic growth and create wealth (see Figure 11). Developing An Insightful Dashboard The dashboard shows the worth in billions of industries (a bar chart of industry and the total worth), distribution based on the source of wealth (a pie chart of the various wealth types), worth in billions of sectors (a bar chart of industry against worth in billions), a text denoting the total of worth in billions, and a filter bar which is applied to all the charts included in the dashboard. The filter bar enables easy interaction with the dashboard (see Figure 12). In 1996, 55.3% of billionaires inherited their wealth, owning $50.2B of $105.4B in real estate. By 2014, inheritance fell to 30.6%, self-made billionaires rose to 20.8%, and founders with non-finance backgrounds rose to 28.3%. The dashboard reveals that the real estate sector has the most self-made billionaires, accounting for 24% of their net worth. Another dashboard for billionaires' citizenship and ages filtered by country. It is worth noting that the USA has the highest number of billionaires, followed by Russia. Analyzing the distribution of wealth across various countries can be valuable information. Interactive Dashboard Summary 4

From the interactive dashboards, some critical features noted but not limited to the growth of the wealth of billionaires over time, their nationality, the source of their wealth, and the industry/sectors in which they are involved. The number of billionaires who inherited their wealth has decreased and is very notable. In Figure 12's dashboard, selecting 1996 and 2014 reveals that the real estate sector was dominant in those years, while the media sector was dominant in 2001, showing the shift in wealth growth by industries. Figure 12's dashboard lets us filter the data by selecting 'USA' in the filter bar. This reveals that most billionaires in the dataset are US citizens and heavily skewed the age range distribution of billionaires. These essential features aid in grasping billionaire data, clarifying the nature and evolution of their wealth. Story Presentation and Analysis. In creating an interactive story with Cognos Analytics, it is essential to note that dashboards are the story's building blocks and are interconnected. The report provides an overview of key findings and delves into the stories of the top ten billionaires. The developed story consists of five scenes (see Figure 2). Figure 2 Storytelling using Cognos Analytics 5

The story's opening scene presents a clear picture of the worth and wealth distribution among billionaires, unequivocally stating that real estate is the most profitable sector, and most billionaires inherit their wealth. The United States of America is the most sought-after country for billionaires to obtain citizenship. Using trends and patterns in wealth distribution and sector performance , assertive investment strategies can create significant returns (see Figure 13). In the second scene, a bar chart presents the net worth of the top ten billionaires. The chart is designed with user-friendliness, allowing users to quickly refine the data by filtering based on the year column. This feature enables dynamic analysis and data comparison over time, making it easy to track changes and trends (see Figure 14). In the next scene, scene 3, it is essential to note that among the top 10 billionaires in the world, per the Billionaires data set, most hold citizenship in the United States. This information provides valuable insight into the various opportunities available in the country that may give billionaires an advantage. Examining each country's total number of billionaires can further aid research and analysis (see Figure 15). Scene 4 presents a helpful table showcasing the top ten billionaires and the sectors they dominate. The visualization is informative, highlighting that two of the top ten billionaires are leading the software industry while two others are in retail. This information can be leveraged to make wise investment decisions or to develop wealth-building strategies. To achieve this, conducting thorough research into the software and retail industries is necessary for investors and wealth builders like billionaires (see Figure 16). It is worth noting that the United States has experienced the fastest rise in self-made billionaires among developed nations. While Europe still sees over half of all fortunes come from 6

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inheritances, a notable decline has occurred from 1996 to 2001. Additionally, over the past decade, other developed nations have slightly decreased the percentage of inherited wealth (Freund & Oliver, 2016). In light of the paragraph above, Scene 5 offers a pie chart that shows the distribution of the top ten billionaires by their source of wealth based on the dataset. After filtering the chart with the year column in the overview, it is evident that, in 1966, most billionaires inherited their wealth. However, the number of billionaires who inherited their wealth decreased as time passed. The chart highlights five top ten billionaires as "founder non-finance." This term typically refers to billionaires who founded their companies and whose wealth is not primarily derived from financial activities such as investments, hedge funds, or traditional finance-related businesses. Overall, this information offers valuable insights regarding the distribution of wealth among developed nations and can inform future discussions around economic policies and opportunities (see Figure 17). Discussion of Specific Business Area The interactive narrative based on the billionaire dataset is an excellent resource for those interested in wealth management and investing strategies. It provides extensive information on billionaires' sources of wealth, associated variables, and financial trends over several years. This data can help investment experts and wealth managers customize their approach, leading to better-informed decisions and, ultimately, more successful outcomes (Patel & Shah, 2022). A critical insight is that wealth managers can utilize various insights to make informed investment decisions and maximize returns. One such understanding is analyzing the distribution of billionaires' wealth over time, area, and industry to identify high-growth areas and sectors. By 7

examining the projected growth trajectories of various industries and regions, this information can help direct investment decisions toward these high-growth areas. (Kaplan & Rauh, 2013). By understanding the mechanisms of wealth creation, such as age, gender, and generational inheritance patterns of billionaires, wealth managers can create tailored offerings that cater to the unique preferences of different demographic segments. This approach can optimize investment portfolios and help achieve long-term financial goals. Additionally, wealth managers can evaluate potential investment opportunities by considering geopolitical risks, government policies, and regulatory changes based on the dataset containing details about the political ties of billionaires. Advantages Of Presenting Findings as An Interactive Story 1. Wealth managers can interact dynamically with the data through an interactive tale. They can go into specifics, examine individual data points, and deeply comprehend trends. This interaction improves understanding and judgment. 2. Wealth managers can tailor the interactive story to their interests or clientele's requirements. To customize the insights to their individual needs, they might concentrate on specific areas, sectors of the economy, or demographic variables. 3. Real-time or frequently updated data can be included in interactive tales through design. By doing this, financial managers are guaranteed access to the most recent data, which empowers them to make more prompt and knowledgeable judgments. Disadvantages Of Presenting Findings as An Interactive Story 8

1. Interactive stories may require ongoing maintenance, especially if there are changes in data sources or structures. Keeping interactive elements updated can be challenging and requires regular monitoring and adjustments. 2. Audiences may prefer traditional, static reports or presentations over interactive stories. Presenting an interactive account to an audience that likes static reports wastes time. 9

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References Kaplan, S. N., & Rauh, J. (2013). It is the market: The broad-based rise in the return to top talent. Journal of Economic Perspectives, 27 (3), 35-56. http://doi.org/10.1257/jep.27.3.3 Freund, C., & Oliver, S. (2016). The origins of the superrich: The billionaire characteristics database. Social Science Research Network . https://doi.org/10.2139/ssrn.2731353 Patel, K. J. & Snehal, S. (2022). Investment strategies and wealth management. https://www.semanticscholar.org/paper/INVESTMENT-STRATEGIES-AND-WEALTH- MANAGEMENT-Patel-Shah/59145504ad0de14c8da07a373ec7791776b6dd1f 10

Appendix Table A1 Dataset variables and descriptions Variables Description name The name of the billionaire. rank The rank of this billionaire compared to the rest of the billionaires reported on. A lower class means they make more money. year The year that data about this billionaire was collected. founded The year that the company was founded. Company. name The name of the company. relationship The billionaire’s relationship to the company. Company. sector The business sector, or what segment of the economy they fit into. Company. type The type of business for this company. age The current age of the billionaire. Periods represented as -1 stand for generations unavailable in the collected data. gender A string representing their gender. citizenship The name of the country that this billionaire has citizenship with. country code the 3-letter country code of the country where this billionaire has citizenship. GDP The "Gross Domestic Product" of the country where the billionaire has citizenship. This is one of the primary indicators used to gauge the health of a country's economy. It represents the total dollar value of all goods and services produced over a specific period; you can think of it as the size of the economy. region The region of the world where this billionaire lives. wealth. type The type of billionaire that they are. worth in billions The number of billions of dollars that this billionaire is worth. category A category representing where their money came from. from emerging Whether the money came from emerging markets. industry The specific industry this billionaire profited from. inherited The way that this money was inherited (or not inherited). Inheritance can come from a spouse, the father, or multiple generations within a family (3, 4, or 5+). was founder Whether the billionaire was the founder of their company. was political Whether the money came from politics. 11

Figure A3 Top 10 billionaires Figure A4 Distribution of wealth based on their source. Figure A5 Worth in billions by sector 12

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Figure A6 Worth in billions by industry Figure A7 Billionaires by country Figure A8 The trend of wealth over the years 13

Figure A9 Age distribution of billionaires Figure A10 Billions are categorized by gender. Figure A11 Decision tree for worth in billions (Predictive model) 14 The box shows billionaires are mainly in the age range of 46 and 77.

Figure A12 Insightful dashboards based on the billionaire’s dataset. Figure A13 Overview Figure A14 Top 10 billionaires 15

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Figure A15 Billionaires’ citizenship Figure A16 Billionaires and their sector Figure A17 Billionaires and their source of wealth 16

Assignment4_ANYE_FRU-1[1] REVISION.edited

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