New York City's first-ever Data Week included more than 100 panels and events related to data and big data, and their impact on the city.
On Monday, Oct. 22, New York City kicked off a weeklong series of events dubbed NYC Data Week. The city’s first-ever Data Week developed in partnership with the NYC Department of Information Technology and Telecommunications (DoITT) and O’Reilly Media, consisted of more than 100 panels and events related to data and big data and their impact on NYC.
“Data is at the core of Mayor Bloomberg’s digital road map for the City of New York, as it enables industry growth, efficiency, and improved service delivery in government,” said Chief Digital Officer Rachel Haot in a statement.
Andrew Nicklin, DoITT’s director of research and development, said because technology conferences (like the O’Reilly Media’s Strata + Hadoop World Conference) were already taking place in New York this week, the city wanted to work in conjunction with those events to promote open data.
“We are super interested in making New York City the tech capital of the world," Nicklin said. "And it seemed fitting with the Strata/Hadoop conference being in New York this week that we would try to do something in conjunction with them to celebrate data and big data."
So what topics and discussions took place this week? Nicklin highlighted four key events from throughout the week and what the IT industry can take away from each.
More than a dozen speakers gave five-minute presentations on various technologies and data. Nicklin said one of the more notable speakers, Hilary Mason, a chief scientist for bit.ly, discussed how she utilized data from around the city to determine where the best cheeseburgers are located.
“I think [Mason’s] talk speaks to the notion that you can use data to make decisions in everyday life,” Nicklin said. “We often make decisions about where we’re going to go to restaurants in the evening and things like that and so we might look at Yelp or City Search or Urban Spoon or any one of those other platforms that are really valuable.”
This panel focused on the use of big data in the financial sector and how financial firms are using new techniques to deal with risk management, stock analysis and investment analysis, Nicklin said. The panel consisted of experts who focus on financial industry growth, and included individuals from the NYC Economic Development Corporation, NYC Investment Fund, Citi Ventures, Accenture and Bloomberg Ventures.
“Large financial companies are innovating in big data, first in their risk management areas and compliance areas because those are the places where the most savings can be made from fraud detection and things like that,” Nicklin said. “But then the use of those technologies does branch out into other areas of the organization to help them perhaps predict where stock prices are going to go or where markets are going to trend and so on.”
But what can public sector take away from this?
Public-sector entities are interested in the area of utilizing big data in financial decisions because big data helps prevent fraud detection and tax evasion, Nicklin said, so applying lessons learned from the financial sector into the way cities, particularly New York operates can be valuable knowledge.
This panel featured speakers from a series of organizations including the New York Genome Center, NBC Universal and DoITT to discuss their data’s history and future.
Nonprofit data liaison organization DataKind (formerly known as Data without Borders) held a meeting during Data Week for data scientists, hackers and other data-driven professions to come together to tackle big questions concerning big data. DataKind typically matches data scientists with nonprofit organizations to have the proper skills on hand to better utilize data within the organization.
Nicklin said many nonprofits have lots of data, but may not have the in-house expertise to properly leverage that data.
During the DataSprint, the organization held a data dive – similar to a hackathon, but without the end goal of producing an app. Nicklin said a data dive typically serves as a way not to develop applications, but to perform analysis on application development and identify answers to questions not yet answered.
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