Demonstrating the Future of Data Science at the Strata Conference
A wise man once said only a fool would attempt a live demonstration (anyone remember Bill Gates and Windows 98?). Apparently I am that fool. Last month at the Strata Conference, my cohort Matt Neglay and I presented a talk, “Demonstrating the Future of Data Science.” As we demonstrated to the standing room-only crowd, data science is changing.
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“More Hands Than Our Own”: Greenplum’s Logan Lee on Opening Chorus
Data science is a team sport that thrives upon collaboration, quick iteration, and a healthy amount of collegial competitiveness. These characteristics also drive development in the open source software community. So it’s fitting that Greenplum announced the release of Chorus, its social platform for collaboration on predictive analytics projects, as an open source project last week at the Strata Conference in New York City.
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OpenChorus and Greenplum’s Kaggle Partnership in the News
This week’s announcement that Greenplum is open-sourcing its collaborative data science platform Chorus and partnering with Kaggle to connect OpenChorus users with the data scientist elite has generated lots of press. Announced at this week’s O’Reilly Strata conference in New York City, OpenChorus and the Kaggle partnership will enable customers, partners, developers, and data scientists to collaboratively realize the predictive potential of Big Data. Here’s a roundup of some of the responses in the media:
The New York Times Bits blog: Creating Big Data’s Talent Mart
Scott Yara, a co-founder of Greenplum and now its senior vice president of products, said his company already has a dedicated staff of 25 data scientists but has more work than it can handle.
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Greenplum and Kaggle Partner to Connect OpenChorus Users with the Data Science Elite
The high demand for data scientists is an significant challenge for increasingly predictive enterprises. It’s is a sophisticated vocation, requiring a range of specialized skills. Kaggle, the online platform for data science competitions, is unique in that it has attracted a community of thousands of skilled practitioners.
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Can an Algorithm Beat Simon Cowell at His Own Game?
It’s a romantic myth that the intangible feelings evoked by a song defy analysis. How can a person or algorithm predict what song will inspire a distinct feeling—the freedom of a bygone summer, the sensation of first love? Of course, selling records has always relied on prediction, requiring an army of A&R representatives capable of intuiting the winning formula of melody, sentiment, and image, to find the next big hit.
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How Can Data Science Serve the Public Good?
Over the course of four seminars, the Big Data for the Public Good series presented a rare opportunity for leading data science thinkers, innovators, and practitioners to explore how the field can serve the public interest. Presented by Code for America and sponsored by Greenplum, the series hosted Michal Migurski and Eric Rodenbeck of Stamen Design, Jake Porway of DataKind and formerly The New York Times, wiki inventor and Nike Code for a Better World Fellow Ward Cunningham, and Jeremy Howard, President and Chief Scientist at Kaggle. Though the diverse selection of speakers explored the topic from a variety of perspectives, a set of recurring themes arose during the talks.
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