Satyam Priyadarshy, chief data scientist, Halliburton, speaking at the symposium. (Amar D. Gupta | Siliconeer)

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IEEE Computer Society concluded its second Silicon Valley big data event, drawing nearly 200 attendees to Rock Stars of Big Data Analytics at the San Jose Civic Auditorium in Silicon Valley. A Siliconeer report.

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The one-day gathering of well-known data analytics authorities explored all aspects of analytics, including building a data-driven culture, launching data platforms, and ensuring privacy. The event included case studies, discussions, lunch roundtables, networking, a cocktail reception – and a live deejay, in keeping with the event’s signature “Rock Stars” format.

“Excitement levels were high and the audience was really engaged with the content,” said Chris Jensen, IEEE Computer Society director of marketing and sales. “There was that proverbial buzz you always hope to find when you come to a conference; a lot of great questions and insightful answers, and even during the breaks, attendees continued the discussions.”

Speakers at the event included:

  • Mike Ames, director of analytics, product management, and Hadoop strategy, SAS
  • Greg Arnold, data infrastructure engineering director, LinkedIn
  • Grady Booch, chief scientist of software engineering, IBM
  • Mark Davis, distinguished engineer, Dell
  • Matthew Denesuk, chief data science officer, GE Software
  • Dan McClary, principal product panager for Big Data and Hadoop, Oracle
  • Chris Pouliot, VP Lyft, Netflix former director of analytics
  • Satyam Priyadarshy, chief data scientist, Halliburton
  • Mike Rosenbaum, CEO, Catalyst IT Services
  • Guido Schroeder, senior vice president of products, Splunk, and
  • Stuart Williams, vice president of research, Technology Business Research Inc.

The speakers tackled big data analytics opportunities and challenges in a variety of industry sectors from social media, ridesharing, and human relations to technology research, and the Industrial Internet. Companies ranged in size from fast-growing startups such as Lyft to well-established companies like IBM, GE, and Oracle.

In his talk, The Limits of Big Data, Grady Booch, chief scientist of software engineering, IBM, addressed the spectrum between the potential of big data for discovery and damage, what’s possible and what’s not, and ways to engage the engines of big data analytics effectively and positively. Greg Arnold, data infrastructure engineering director, LinkedIn, discussed scaling self-service analytics, the challenges involved in building a self-serve analytics ecosystem by integrating storage and compute platforms, data acquisition and management, and reporting and visualization tools. Matthew Denesuk, chief data science officer, GE Software, presented on the growth of the new industrial revolution that’s emerging as information technology increasingly joins with human minds, machines, and business processes, resulting in dramatic improvements in productivity, living standards, and efficient use of resources. A panel discussion explored the question, “How far can we trust big data?” and the potential and power of big data for the good and the not-so-greater good. This compelling discussion took aim at the intersection of big data analytics, business practices, social norms, and ethics to help provide guidelines for meaningful action for business executives, developers, and users.

Lunchtime roundtables were delivered by David B. Jackson, founder and CTO of Adaptive Computing, and Peter Hoopes, VP and GM BIRT Analytics Division at Actuate Corp.

IEEE Computer Society is the world’s leading computing membership organization and the trusted information and career-development source for a global workforce of technology leaders including: professors, researchers, software engineers, IT professionals, employers, and students. The unmatched source for technology information, inspiration, and collaboration, the IEEE Computer Society is the source that computing professionals trust to provide high-quality, state-of-the-art information on an on-demand basis.

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