Data Visualization

Blog of the Data Visualization & Communication Course at OSB-AUB

This is my favorite part about analytics: Taking boring flat data and bringing it to life through visualization” John Tukey

Software Business Unit

To share some insights into our business unit’s performance and the exciting potential that lies ahead. Our team has been working diligently, and I am proud to say that we have achieved favorable outcomes. However, it is essential to acknowledge that these results are not uniform across all units. As we meticulously analyzed the data and engaged in forecasting and budgeting for the year 2023, a remarkable opportunity came to light. We discovered that by putting more emphasis on our software business unit, we can unlock substantial growth potential and significantly increase our profits. The world around us is evolving at a rapid pace, and software plays a pivotal role in shaping industries and driving innovation. We have witnessed numerous success stories in this realm, with companies achieving unprecedented heights by harnessing the power of software solutions.
Our business unit’s performance has been commendable, but by aligning our focus and resources towards our software division, we can tap into a burgeoning market and secure a more prominent position.

In the Link Below, kindly find the Data visualization that lead us to derive the above conclusion.

Final Project | Tableau Public

Exploring Economic Prosperity and Labor Market Health

Exploring Economic Prosperity and Labor Market Health

Hello Readers,

Today, I am excited to share with you a unique exploration of global economic indicators. We often hear about GDP per capita and unemployment rates in various news outlets and economic discussions. These two metrics are commonly used to measure a country’s economic prosperity and the health of its labor market. But, have you ever wondered about the relationship between them?

In my latest project for my Data Visualization & Communication course, I’ve delved deep into this topic. Using the World Development Indicators dataset provided by the World Bank, I’ve constructed a comprehensive data visualization that probes the relationship between GDP per capita and the unemployment rate.

But why focus on these two indicators? Well, they provide a snapshot of a nation’s economic status and its labor market health. Understanding their relationship can offer valuable insights for policy makers, economists, and the public alike.

The goal of this project is not just to present data, but to tell a story through it. By visualizing this data, we can make more sense of what these economic indicators mean and how they interact.

 

 

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Is Lebanon a Sustainable Country?

Is Lebanon a Sustainable Country?

Meeting our current requirements without sacrificing the potential of future generations to satisfy their own needs is what is meant by sustainability. It entails striking a careful balance between social advancement, economic expansion, and environmental preservation. We can build a prosperous society that guarantees a good standard of living for its residents while maintaining our natural resources and safeguarding the environment by embracing sustainability.

Perfect Match

In Lebanon, sustainability is an urgent call to action rather than just a trendy concept. Numerous issues confront the Lebanese people, including socioeconomic inequality, resource depletion, environmental degradation, and climate change. To overcome these obstacles, we must reevaluate our tactics and policies, use cutting-edge techniques, and collaborate to create a more sustainable future.

AUB ranked among the most sustainable worldwide

But attaining sustainability requires collaboration. Government, corporations, civic society, and every person must work together to achieve this. It calls for the creation and use of efficient policies, the inclusion of sustainability principles in our decision-making procedures, and the active involvement of all stakeholders.

Lebanon is far from being a sustainable country, although some startups have proven to be leaders in sustainability. But this example has to be spread among all the Lebanese society, to make sustainability a habit and a lifestyle for all the Lebanese people.

https://public.tableau.com/views/AliGhassani202372002/LebaneseSustainability?:language=en-GB&publish=yes&:display_count=n&:origin=viz_share_link

Inequality of Life Expectancy

Inequality of Life Expectancy

I will be tackling an important key metric that concerns the entire community, It is the large inequality of Life Expectancy across the World. Through our visualizations, we will discover the major conditions standing behind this problem. Life expectancy is the average age of death in a population, and it highly depends on the country’s conditions. This map showing countries in different colors can validate the inequality of life expectancy that has been around for many years.

We can see from this visual (Data from 2015), that the lowest life expectancy in the world was 51.1 and the highest is 84.28 years, which means that there are more than 30 years of difference, which is considered a huge difference in another word we can say that people in China, Japan, and Spain live 30 years longer than people in Chad, Nigeria, Central African Republic…

By first looking at these countries, we can see that the top countries with the highest life expectancy are known to be wealthier countries as Spain, Switzerland, Italy, and Australia and the worst life expectancy that is below 60 years is in the poorest countries, this population live in extreme poverty with very limited health knowledge and sanitary precautions. To confirm this analysis, I created a visual to analyze the impact of GDP per capita on some of these ton their life expectancy.

From these visuals, we can see that the countries with the lowest life expectancy are countries with the lowest GDP per capita, which will affect their health systems and life standards, these same countries are suffering from high Neonatal mortality rates, which is considered a major driving factor that leads to a significant decrease in life expectancy. The mortality at an early age is due to the absence of health measures in these poor countries, suffering from a lot of diseases with minimum access to medicines and healthcare facilities.

Unsurprisingly, from this visual, we can observe the link between life expectancy and health expenditure, countries that can spend more on their health can have longer lives than countries with low health expenditure.

Thus, the potential solution is improving the health standards which means developing resilient Health Care systems and supporting those countries, especially during pandemics and natural disasters. What can validate this solution by the progress seen in life expectancy in all countries over the years, and the expectations of the United Nations that people are now expecting to live longer due to improvements in health in preventing neonatal and young age mortality.

My Recommendations to increase life expectancy not only for poor countries, but also globally, and to decrease the gap between wealthy and poor countries are specific medical innovations in case of pandemics like vaccines, improving public sanitation, and increasing healthcare expenditure to achieve equitable population health outcomes. It is always important to keep on examining the factors affecting life expectancy and study the context of each country and build a database of the underlined reasons to be able to take the best approach to reach the highest possible level of equitable life expectancy.

Save Your Children From HIV

Save Your Children From HIV

Unfortunately, there is a high number of children, between ages 0 and 14, living with HIV.  This disease in children manifests in health conditions that stem from impaired immunity. The children that have this disease are unable to fight microbes. As a result, they are at a high risk of getting infections. Moreover, children with HIV are more likely to be diagnosed with cancer at a later stage of their lives. This visualization is evidence of the problem I am discussing today. It shows the average number of children between 0 and 14 years living with HIV in different countries.

As you can see in visualization 1 below, the average number of children with HIV is about 1,950,938. The country with the highest average number of children with HIV is South Africa and the countries with the least average number of children with HIV are Fiji, Georgia, Latvia, Mauritius, and Oman.

One solution to the problem that I would like to propose is putting children with HIV on ARV drugs. In the past, approximately 50% of the children with HIV did not take ARV drugs. Thus, it is vital that we shine a light on this solution that could help increase the span of life for these infected children. Going into the solution details, I recommend early testing and starting treatment from a young age. This will aid in reducing mortality of HIV infected children. In addition, when treatment has begun, the patients ought to take their medications on a regular basis to ensure the highest levels of health possible when they reach adolescence and adulthood.

Plotting the data on a world map, we can identify the countries or continents with the highest average of children infected with HIV. This allows us to know where to start with supplying ARV drugs.

As you can see in visualization 2 below, African countries have the highest average of infected children and are in desperate need for ARV drugs. Therefore, we ought to start with these countries and supply them with the necessary ARV drugs to aid in reducing the high percentage of infected children. Afterwards, we could supply the other countries with lower average numbers of infected children with this disease.

As you can see in visualization 3 below, it shows a comparison between children living with HIV (0-14) and children newly infected with HIV (0-14). As we can see, the countries that have a high average of infected children also have a higher percentage of newly infected children than other countries with lower average infected children.

This proves the validation of my proposed solution. Without early testing and treatment, the number of children getting infected with HIV will increase. Not to mention the fact that about 50% of children with HIV die before the age of 2 and about 80% do not reach the age of 5! Moreover, children with HIV that are not treated with ARV drugs experience many illnesses and diseases.

Hence, the findings/recommendations that I would like to propose is that we should raise awareness about the importance of early testing for children, and then treating them with ARV drugs that have proved to be effective and efficient to a certain extent.