For some boot camp learners, projects are a means to an end. For others, they’re a spark that ignites something much, much bigger.
Cole Fingerut, Chris Hanafin, David Hoff, Carly Kelly, and Yasir Omar first crossed paths at GW Data Analytics Boot Camp — each one driven to further their career through the power of data. Once they discovered the potential of their group dynamic, they stuck together for the duration of the course.
The team’s final project — an interactive, map-based dashboard synthesizing 20 years of conflict across the continent of Africa — culminated in an awe-inspiring display of their individual and collective strengths.
Here are the highlights.
Getting their concept off the ground
The project started with a single theme: War.
“We asked ourselves, ‘What would cause war between countries?’” explained Yasir. “But we quickly realized the data we’d need to answer a question that big would be too convoluted. We scaled it down. We looked at conflict within singular countries — conflict being anything from peaceful protests to civil violence. We decided to focus on the African continent.”
The project would analyze the determinants of conflict in Africa — including everything from economics and ethnicity to population size and politics. The first step was mapping it out.
Part 1: The Conflict Profiles
The team’s first task was sourcing the dashboard’s data. Cole took the lead, drawing from his background in policy, trade analysis, and foreign policy analysis. Leveraging a variety of sources, from the U.S. International Trade Commission in Africa to the World Bank to the African Development Bank, he honed in on the sources used by top political scientists and compiled the most consistent data set he could find — cleaning, standardizing, and integrating each swath along the way.
“It was complex,” said Cole. “I wanted to own the process from the first step to the finished product, and it was more than just sourcing raw data — it was compiling and presenting it in a way that told a story. On top of that, we wanted to demonstrate our ability to expound upon the data later on, especially if we received the opportunity to share it with relevant stakeholders.”
Next, the team turned to designing the now-populated conflict map — and making each country’s profile visually accessible.
David spent the former part of his career in communications and journalism, driven to the boot camp by an interest in using data to improve communication and knowledge sharing. Especially adept at Tableau, he worked on the front end design of the map.
As a user scrolls over the map, the sliders to the right adjust to reflect the past 20 years of conflict data for each African country — with the entire map conflict-coded by color to identify regions of low, medium, and high intensity. To select a specific year or zoom in on a particular country’s history, the user simply inputs their desired data through the module on the bottom right corner of the dashboard.
“I was mostly freeform in designing the map,” said David. “I knew the data we had, and I knew I had freedom to play around with it. I worked through six levels of data in Tableau to get to this final stage. Through it, I was able to experience the process of truly mastering a language.”
Part 2: The Interactive Map
Chris, previously a market research manager at a brokerage firm with experience in commercial real estate, was driven by a passion for storytelling‚ transforming ideas into results, and facilitating effective teamwork. He helped across every aspect of the project, pitching in wherever extra hands were needed. The majority of his work, however, landed on the interactive map. Leveraging his especially strong Python skills, Chris pushed the entirety of the map’s data from Python to AWS.
“I organized a Zoom room that was constantly open,” said Chris. “Our team came in and out on their own time, spending hours of unstructured time a day collaborating. We did a really good job of driving and alternating workflows.”
The map-building team was rounded out by Yasir, an analyst at the American Chemical Society who worked on the business side of tech for the past eight years.
“I wanted to make sure that everything on the map was related,” said Yasir. “I took responsibility for ensuring that it updates regularly and gives the user a refreshed news feed every time.”
Everything came together beautifully. When a user selects a country, they’re able to view an automatic scatter plot displaying the number of conflict events, fatalities, and more, according to a range of conflict determinants — from ethnic diversity scores to economics, GDP, and corruption. The map plots the points and feeds the user recent news articles related to their input, running on tools like Plotly and facilitating API integrations and web scraping.
Part 3: The Predictive Models
Finally, the project’s predictive modeling portion called for a full group effort. Powered by machine learning, this tool looks at the most important political factors within a country, identified above, and builds individualized models based on user input. Users can manipulate each factor on a sliding scale, and the model outputs precise conflict predictions. This can be used to isolate certain aspects of a country’s conflict profile — or to test the consequences of different socioeconomic and political shifts.
“There’s a huge potential for tools like this in the world we live in,” said Cole. “People are more internationally conscious. They’re interested in risk management and economic development. Tools that are easy to play around with can get essential data in the hands of decision-makers.”
“The space is extremely data-driven,” he continued. “But it’s driven by data that’s not as frequently updated as decision-makers would like. Because of the way we built our dashboard, it’s a launching pad for more. We could easily add more data and world issues — and we only spent two and a half weeks on it. Think about the potential for a year-long or even part-time capacity. Foreign policy researchers and analysts could use a dashboard like this as a baseline.”
Wrapping up the work of a lifetime and looking ahead
Through every stage of dashboard development, the team updated a goals list denoting the deliverable they wanted to create, who would work on it, and when they wanted it done by. One item lingered on the list for the entirety of the project: the microphone. Yasir wanted to build a microphone that enabled voice command, allowing users to simply say “Angola,” for example, if they wanted to view or interact with the Angola profile.
“Every few days, someone would ask me how the microphone was going,” said Yasir. “We’d laugh. It was a joke — we knew it wasn’t going to happen.”
Two and half weeks later, on the night before Demo Day, the team had checked off every item on their goals list, barring the microphone. They all went to bed satisfied — except Yasir.
“I didn’t tell anyone what I was doing, because I didn’t want to be embarrassed if it didn’t work,” laughed Yasir. “I stayed up all night building the microphone. When the team woke up for our presentation, it was complete. It was the cherry on top. Everything we set out to do was done, and we hadn’t crammed. It wasn’t stressful — it was smooth. It was about as flawless as it gets, and there’s a lot going on in that map. This team wasn’t randomly put together. We wanted to work together, and we owed it to each other to get to the finish line and be able to say, ‘We did it.’”
Now, Carly is in the initial phase of her first data role at JDSAT Operations Research & Big Data Sciences. “I presented this project as part of my final interview,” she said. “My career change wouldn’t have happened without this team.”
Cole works as a researcher at the Hudson Institute, where he employs his experience in international political and economic analyses every day. David is the owner of his own company — DavidJHoff — where he works as a consultant to government agencies and nonprofits, using words and data to tell stories. Yasir is applying his new skill set to his continuing work at the American Chemical Society, and Chris is working on various data projects of his own, while training potential employees.
“At the end of it all, we know that working together is something we want to continue doing in some capacity,” he said. “It’s just a matter of determining what that looks like.”
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