Show off your data visualization skills while competing for prizes!
ABOUT THE SUBMISSION:
This visualization allows users to view and analyze data about unicorn startups in a graphical and interactive format. This dashboard includes bubble charts, bar charts, treemaps, sunburst charts, and other types of visualizations that provide insights into the location, industry, funding, and other characteristics of unicorn startups. It can be used to track the performance of individual companies, as well as to compare and contrast different groups of companies. They can also be used to identify trends and patterns in the data, and to explore relationships between different variables. Bubble charts, tree maps, and sunburst charts were used to specifically describe metrics like valuation and geographical spread which provides an easily interpretable visual distinction.
Insights:
1. Of all the unicorn companies, approximately 75% are located in the United States, China, and India.
2.San Francisco,New York, Beijing are the top locations in the world w.r.t number of unicorn startups present and in terms of combined valuation of the startups too
3. The number of companies becoming unicorn startups significantly surged (by 389%) in 2021 after the recovery from the Covid-19 pandemic, as depicted in the plot
4. There appears to be a quadratic relationship between the valuation of unicorn firms and the number of investors. As the valuation of a unicorn firm increases, the number of investors also tends to increase at an increasing rate.
This project was made using Canva and Flourish.
ABOUT THE SUBMISSION:
To understand the evolution page by page, we have simple visualisations at the beginning and more you progress on the dashboard more you analyze deeply the data.
The first page presents some key words to understand the dashboard and one statistic about people with disabilities (DAX measure). The goal is to give key information to understand the dashboard and with the first visualization make users wanting to go further. The map uses a mapbox visual and gives a vision of the statistic by country. The Pacific is still an area who is not well known, so this type of map tends to give viewers a better idea of the Pacific region.
On the second page, you’ll find an overview of people with disabilities by country, by sex and by degree of urbanisation. The map is a shape map based on a Json file.
On the third page I wanted to showcase the difficulty for people with disabilities to work and some key figures about employment in the disability world. One good insight is you can see a lot of workers with disabilities are own-account workers.
Throughout the Dashboard you'll also see different icons to facilitate the navigation on the Dashboard. Two buttons are based on the use of bookmarks. Some charts have dynamic titles because it allows the user to see all the filters selected and understand the figures he/she is looking at.
ABOUT THE SUBMISSION:
This visualization was born out of my interest in supply chain and in the negative impact of fast fashion. The metaphor of "follow the thread" is depicted by the yellow string that carriers readers through the dashboard. This metaphor is meant to help the reader imagine they are following their clothing back to its source, and uncovering more information the further they go back. I used multiple sources for the information in the dashboard but relied heavily on the research and data from KnowtheChain.org, which I urge readers of the dashboard to visit. I also used illustrator to create all of the art work (string, woman sewing, material icons) that you see in the dashboard which I thought added a personal touch and made the content a bit more engaging. Overall, this dashboard is meant to get readers more interested in where their clothing comes from so that we can make more sustainable and beneficial decisions as consumers and investors. One interesting takeaway that I had from this visual was that high end fashion companies may not be free of guilt- just because something is expensive does not mean their supply chain is free of abuse.
ABOUT THE SUBMISSION
Inspired by both the competition, and the Tableau community ‘Real World, Fake Data’, my submission represents my return to Tableau following a 6-year break, during which I’ve been developing Power BI & AWS QuickSight skills. I chose the Emergency Room dataset to draw on my health sector experience.
The dashboard represents a glimpse into the business intelligence world of hospitals, where administrators need to know core KPI’s at a glance, such as how many patients are coming through the doors, average wait times and percent of patients seen within 15mins – all of which are real-world NHS KPIs. These managers also need to see how these KPIs change over time – are interventions having an impact? To address these requirements I styled the top row of visuals to ensure this information is first thing users digest. As I explored the dataset I decided to focus on the rich demographic information available, specifically creating age groups, such as paediatric & geriatric, which are reflective of hospitals’ patient care cohorts, using colour as a visual cue to aid understanding. I also took special care with chart interactions to ensure that a little exploration yields the maximum possible insight.
My two key insights from the dashboard are the obvious – action needs to be taken to improve the KPI ‘% seen under 15mins’, and the absent – this dataset does not have any patients waiting over 60mins – which in today’s NHS would be seen as either miraculous or, more likely, erroneous!
ABOUT THE SUBMISSION:
The dashboard I have created is based on Cargo Theft from the year 2013-2021. I was curious to know if the COVID outbreak had any impact on the thefts and crimes. The trend shows that there is an increase of stolen value from the year 2019. I believe the dashboard should answer the questions 'What', 'Where', 'When', Who' and 'How'. Keeping this in mind I have created four sections : Overview (The overview of what has happened), Cargo Theft & Stolen Value ( The YoY trend), About the offender (Who is the culprit), More About the offense ( Where did it happen , who was the victim , how did it happen) and few insights and recommendation which I felt will be useful to reduce the theft. Some filters are also provided on the dashboard (location, state , city and year) in case any deep analysis is required.
In this visualization we talk about a fundamental resource for human life: water. In many countries people drink bottled water and are discouraged from using tap water. We have decided to analyze it in an exhaustive way by analyzing the business of water sales (analysis of the most important companies, water consumption in Europe and Spain), the problems that microplastics cause to health, the environmental impact and so on.
Check out the Full Submission Here!
ABOUT THE SUBMISSION:
This is a dataviz project made to show the Life Satisfaction Value of the Top 10 Happiest and Saddest countries in the world and the relation with their Population and their GDP per capita. I took this opportunity to experiment a little bit with a different style from the one I'm used to :)
ABOUT THE SUBMISSION:
The data visualisation aim is to spread awareness about people dying whilst fleeing their homes in search of safety. Missing migrant is an NGO that collect and tracks people who have died or gone missing en-route, this is reaching record level number. Despite this refugees and asylum seekers are constantly dehumanised and the aim of my data visualisation is not only to humanise the topic but to spread awareness about the current human emergency crises we're facing.
ABOUT THE SUBMISSION:
This visualisation was built for Women’s History Month 2022. Women and their achievements have often been ignored, in particular, in science. We see evidence of the The Matilda Effect throughout history - the effect used to describe bias against the achievement of women scientists in favour of their male colleagues. With this viz - which was built in Tableau - I aimed to shed light on the Matilda Effect - to honour and bring to light the achievements of some brilliant women scientists.
ABOUT THE SUBMISSION:
My parents, brother and I have been playing Wordle and sharing our results in a group text for about a year. I started collecting the data and keeping it in a spreadsheet after finding myself doing Wordle on a mountain top in Maine instead of enjoying the view.
I didn’t have a particular visualization in mind when I started collecting the data, but with nearly a year of data I did want to include a radial chart of some sort. Radial charts are tricky in that they’re not always the best chart choice, but I also find that they have potential to be so beautiful! I settled on a sunburst chart as my center piece, and it shows the average number of guesses for our Wordle games. The days that were the hardest for us and those that were the easiest really shine in the sunburst. Throughout the rest of the visualization, I explore how my family has done in our quest to master Wordle, whether we’ve gotten any better with time, which words are harder to guess, and I even pose the question “Who is the best?” Thankfully, I didn’t start any family drama with my visualization and if anything, the game has brought us closer. For now, we’re still playing!
