Data are becoming the new raw material of business
The Economist

Data Science in 30 Minutes: Why Big Data Needs Thick Data with Tricia Wang

This FREE webinar took place on June 26th, 2018. Sign up below for the free video!

Tricia Wang, co-founder of SuddenCompass joined The Data Incubator for the June 2018 episode of our free online webinar series, Data Science in 30 minutes: Why Big Data Needs Thick Data.

Why do so many companies make bad decisions, even with access to unprecedented amounts of data? Tricia has the answer: companies are implementing “big data” without what she calls the secret, missing ingredient, “thick data” – precious, unquantifiable insights from actual people – to make the right business decisions and thrive in the unknown. Tricia shared stories and lessons from how her company, Sudden Compass, advises and teaches organizations to unlock insights from big data and turn their big data projects from optimizing the bottom-line to driving growth.

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Why Big Data Needs Thick Data with Tricia Wang

About the speakers:

Tricia Wang is a data science loving tech ethnographer. She co-founded Sudden Compass, a consulting firm that helps enterprises move at the speed of their customers by unlocking new growth opportunities in their big data and digital transformations with human insights. They’ve worked with organizations such as P&G, Kickstarter, O’Reilly, and Spotify. She is a pioneer in popularizing the need for companies to integrate “Big Data” and what she calls, Thick Data, which she describes in her talk on TED. She’s a frequent keynoter at data science gatherings, such as Strata, IBM, and Terradata.. Tricia’s work with Fortune 500 companies have been featured in Techcrunch, The Atlantic, Al Jazeera, Slate, Wired, The Guardian and Fast Company. Tricia gained her data chops while earning her PhD as a Sociologist.

Michael Li founded The Data Incubator, a New York-based training program that turns talented PhDs from academia into workplace-ready data scientists and quants. The program is free to Fellows, employers engage with the Incubator as hiring partners. Previously, he worked as a data scientist (Foursquare), Wall Street quant (D.E. Shaw, J.P. Morgan), and a rocket scientist (NASA). He completed his PhD at Princeton as a Hertz fellow and read Part III Maths at Cambridge as a Marshall Scholar. At Foursquare, Michael discovered that his favorite part of the job was teaching and mentoring smart people about data science. He decided to build a startup to focus on what he really loves. Michael lives in New York, where he enjoys the Opera, rock climbing, and attending geeky data science events.

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