Melissa Lee, Emily Fu and Jun Yan Chang studied fire data from thunderstorms to wood waste during their Modern Data mining course at Wharton. Eventually, the team created a data model, a live chart of the relationships between different types of information, for their class project, which they hope to use one day to prevent fires in California. Emily and her colleagues Jun Yang Chang and Melissa Lee, also Wharton alumni, began last year as students of Professor Fu. “Eldorado’s fireworks at a sexual awareness party is 15 miles from my home in California,” said Emily Fu, a Wharton School business analysis student who is now returning to Philadelphia for her her senior year. “So what caused these fires? Most are fires caused by a lightning strike on a tree or forest. When we used this model, it spewed out certain types of vegetation that predicted the size of the fire, such as wood trash or dead branches that fell to the ground and dried up. We can attack them with prescribed fires, which are small controlled fires that burn all the wood trash until summer, so when the fire season comes, there’s not much to burn,” Emily says. Do you do statistics or data analysis in high school? Do you just focus on numbers or do you provide context for the real world? What examples of how data processing projects have become more relevant to you? Describe it in the “Comments” section of this article. “Our team could tell many stories using our data,” says Melissa, who has a career in marketing and business analysis. “Once you have the right data, you don’t just have to build a model,” says Jun, a Malaysian financier. Their work won a place among industry experts, doctors and professors who spoke at the Women in Data Science Conference at the University of Pennsylvania in February 2020. However, when Wharton Global Youth gave a presentation last week, the three junior researchers readily shared some of the benefits of their research. First, data science requires finding the most compelling story behind the numbers. Linda Zhao’s course on modern data mining at Wharton Data Mining is the practice of studying large databases – for example, “forest fires in the U.S. over the past 30 years” – to get new information. They enthusiastically talked about their fire studies, inspired by weeks of data collection and analysis.