On July 16 the first-ever Data Jawn conference took place in Philly, hosted by startup RJ Metrics at the Chemical Heritage Foundation in Philadelphia. The intention of Data Jawn was to bring together local data nerds to talk about the cool and innovative ways they’re using data. But what struck me most was how people have used data for centuries, and how important it’s been in shaping so many aspects of our lives.
Data Jawn kicked off with the presentation, Rise of the Data Hero. During this talk, RJ Metrics co-founder Jake Stein discussed historical perspectives on data and the evolution of data-driven people. Stein made it clear that data-driven thinking is not bound to the technology and tools at our disposal, and cited several examples of prominent data users from throughout history. One example he gave was of 18th century physician James Lind, who performed the first clinical trial as he tried to find a cure for scurvy. He tested different groups of sailors using several potential treatments, including apple cider, sulfuric acid (yes, a dose of sulfuric acid), vinegar, seawater, oranges, and barley water. The test resulted in the discovery of citrus fruits’ ability to prevent scurvy and thus save hundreds of thousands of lives.
Florence Nightingale was another notable figure who used data to improve the quality of human life. In the 19th century, hospitals in India and other Asian countries were seeing abnormally high mortality rates. Through meticulous data collection, statistical analysis and handwritten data visualizations, Florence Nightingale discovered that poor sanitation and overcrowding were the causes of the high death rate. One of the coolest remainders of this data analysis is the below visualization, which was created in 1856. It is what one might call an older version of Google Analytics as it utilizes modern aspects of data analysis such as segmenting and factoring in seasonality. This put Florence Nightingale way ahead of her time in terms of problem-solving, and enabled her to identify the importance of good sanitation in hospitals.
Data is clearly nothing new. But programs such as Google Analytics have made it significantly easier to collect it and analyse it. In fact, the granularity with which you can look at site performance today might have saved Florence some time (but she is clearly still a trend-setter).
So what are some of the problems currently facing data analysts? One talk, titled Most Common Mistake People Make with Data, claimed that the most common mistake is that too often we as data users are solution focused. Speaker Madeleine FitzGerald argued that we should focus on the problem itself and not the solution to the problem—at least initially. So instead of asking “What can I do with this data?” the question should be “How can data be used to solve my problem?” We should first identify the problem, find what we want to achieve, and then build the analysis that will address those needs.
Another presentation that touched on current challenges for data analysts was titled Overcoming Cognitive Biases & Making Data Driven Decisions. This presentation highlighted the importance of data visualization over textual displays from a cognitive perspective. In addition, Data Jawn offered a discussion panel featuring prominent figures in the Philly tech scene who talked about the ongoing challenges the Philly data community faces such as transitioning out of legacy systems and into newer technologies that are equipped to handle larger data sets.
So, where is data headed? I bet that James Lind and Florence Nightingale never in their wildest dreams could have imagined the tools we have access to today. But evolution doesn’t stop here!
Data Jawn offered an intriguing glimpse into the future capabilities of data and the people that use and analyze data. It was especially enjoyable since the overall event focused on Philly and positive societal impact. One such example is Azavea, a Philly company that provides advanced GIS solutions. Azavea is using public data to develop risk assessment models that predict when and where crimes will occur. This type of analysis can increase operational efficiencies, such as workforce planning, within law enforcement agencies. More importantly, this project may reduce incidents in a city that consistently ranks among the worst for crime.
In recent history, data analyses cases have often had nothing to do with social benefit. Instead, analytics tools and techniques have largely been used to solve complex business problems, which is great for the stakeholders of that organization, but no one else. It is especially exciting to see a public institution such as the City of Philadelphia use these techniques to identify and solve problems in our community, which is something we all can benefit from and an excellent direction for data analysis.
Overall, Data Jawn was a unique event that covered a good portion of the data analysis spectrum. The speakers were engaging and informative without dragging out their presentations. I look forward to next year’s Data Jawn to see how these innovative practices have evolved and the impact they will have had on the city of Philadelphia.