For years, cities have relied on official food inspections as their primary defense against shady restaurants and questionable dishes. But the city of Chicago is raising the stakes through predictive analytics, which not only helps officials catalog offenders, but also identifies high-risk restaurants for citizens and inspectors.
Chicago CIO Brenna Berman and Chief Data Officer Tom Schenk completed a pilot program this month that takes data sets from the more than 15,000 restaurants in Chicago and its surrounding neighborhoods, and estimates which eatery is most susceptible to health issues. Data scientists from AllState Insurance contributed to the project, and data was gathered from the city’s WindyGrid system, a data repository that collects real-time information from city departments at a rate of 7 million rows per day.
