Last Wednesday, OLC sat in on a fireside chat with Lauren Tabot, presenting her lessons learned as a 'data diva' at Gilt offices in New York. Formerly the Chief Programmer for the Financial Crimes Task Force for the Mayor's Office of Data Analytics, Lauren shared her experiences working on a variety of New York City based government projects.
One example of Lauren's forays in data dealt with improving geo-coding software for better data integration. She cited an After Action Use Case as an example where she and a small team were tasked with matching phoned-in downed trees to the 311 system in the aftermath of Hurricane Sandy. The team needed to know the number of downed trees in order for government to inform and deploy necessary resources to a specific location in the city. They faced a number of challenges including how to grapple with often obsolete systems utilized by for instance, the NYPD in-data collection across precincts. Their team was handed thousands of truncated addresses and asked to geo-code them to automate a system for more efficiency.
Lauren spoke of hacking a database to automate an outdated system in order to fill in the information they were given: truncated addresses and precincts. Ten hours later, Lauren and her team hacked a semi-automated system geo-coded to get the necessary information to the New York City Parks Department signaling locations requiring help.
When asked about typical challenges working with government agencies, Lauren admitted to struggles with government agencies often averse to technological change. “You need to get leadership buy-in” in order to implement change utilizing the best technology, she says. “It's hard to gain users' buy-in without their full understanding what you are doing without compromising too much complexity in the process.”
Lauren was recently admitted to Cornell NYC Tech, the first Masters class for Cornell's Innovation Institute based out of Google's NYC Office.