2012 is proving to be the year of Big Data, demanding the attention of executives, thought leaders, academics, and tech journalists alike. From the Obama Administration’s $200 Million Big Data Initiative to the enterprise, retail to academia, businesses, organizations and governments are increasingly realizing the opportunities posed by the inundation of massive data sets. But this influx of data is only valuable through dedicated and specialized analysis.
The second annual Data Science Summit in Las Vegas on May 22 and 23, 2012, will bring together data scientists, executives, academics, data journalists, and many more to explore the opportunities and challenges posed by Big Data. Featuring speakers including Nate Silver of The New York Times’ FiveThirtyEight political blog, Kaggle’s Jeremy Howard, Nora Denzel of Intuit, Global Viral Forecasting Initiative CEO Nathan Wolfe, Roger Magoulas of O’Reilly Media, and Aryng CEO Piyanka Jain, Data Science Summit 2012 invites a wide range of thought leaders and practitioners to connect, share ideas, and learn from one another.
“The industry has had an opportunity to emerge full-force in 2011 and 2012,” says Annika Jimenez, Greenplum’s senior director of analytics solutions. “There’s a lot of interest in the topic of data science, while still some confusion about what it is and what it can yield in value propositions to the enterprise.” For businesses of all kinds, this is a pressing issue. “I see data science as a disruptive force,” says Jimenez. “It’s shaking up IT’s role and organizational paradigms.”
Addressing this disruptive force will require collaboration between the leading thinkers in data-driven organizations. “Big Data is still a very new and emerging technology so it is important to engage with the community early on,” said Richard Snee, Data Science Summit event chairman in an interview with Mona Patel for EMC’s Big Data Blog. The event aims to “bring the practitioners and vendors together so they can answer the tough questions, share knowledge, collaborate to further evolve the technology and ensure organizations get what they need to be successful.”
The Big Data revolution demands that we become more agile and predictive than ever before. “A lot has happened this year, and the rate of evolution is incredibly fast,” says marketing consultant, Alison McCauley. The Data Science Summit is “a place to understand what is happening with data science, how individuals and businesses are transforming, and what can be gained by prediction.”
As Greenplum’s head of business development and strategy, David Menninger notes that organizations must dedicate resources and commit data science specialists to reap timely and valuable predictive analytics. Citing research conducted while he was vice president at Ventana Research, which he presented at the Mass Technology Leadership Council Seminar in April, Menninger says that organizational satisfaction with predictive analytics is directly related to whether data scientists performed the analysis. “The projects that were done by the data science teams had much higher satisfaction rates,” he says. “When specialized data scientists ran the project the satisfaction rate was 70%. The average was 63%. When you look at who’s doing the projects and who should be doing the projects, not enough organizations are devoting the resources that they should.”
These observations are echoed by Jimenez. “We have the platforms and analytics tools,” she says. “The opportunity at hand is for enterprises to place analytics in the center of their strategy, for companies across all sectors to emphasize analytics as a core differentiator for their companies. That requires people with vision, skills, and a core understanding of where the function is evolving in its nascent state, to move from raw data to true value.”
“Big Data and data science are inextricably linked,” says Menninger. “You can’t browse a billion rows of data to find what’s interesting, it doesn’t scale. These things go hand in glove.” Which speaks to the core challenges facing data-driven organizations: a lack of dedicated resources, adequate training, and data scientist specialists in the field. “The absolute short term solution to address this is to bring in specialists, the second is to train people to develop these skills, and broadly as a market we need to integrate this into our academic and training programs,” he says.
The Data Science Summit provides a venue to professionals across the data community to share information, collaborate, and address these challenges. “How do you share not only the knowledge derived from the findings,” Menninger says, “but also the process of creating these analyses? You need a collaboration fabric to capture all that information.” Such collaboration is crucial as business, communication, and government become increasingly data-driven.
“Data science and Big Data are going to have such a profound impact on our lives,” says McCauley. “We’re all figuring it out right now. We’re all learning at the same time. So, the sharing and networking that can occur at the Data Science Summit is very beneficial.” This vision of creating value through collaboration is shared by Jimenez. Describing the Data Science Summit as a “thought leadership-centric gathering,” she states “it’s about bringing together influencers and folks evaluating their options into an intimate setting to learn what data science can bring about.”
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