Schedule: Order of Magnitude Shifts sessions

Location: Westside Ballroom Level:
Monica Rogati (Data Natives)
When it comes to big data insights, how do you know you’re asking the right questions? Hiring data scientists is a good start - we’re seeing their growth both on LinkedIn and at LinkedIn. But even data scientists are not immune from the myriad of hidden pitfalls that keep your key insights out of sight. Read more.
Location: Westside Ballroom Level:
Jodee Rich (PeopleBrowsr)
By using social media metrics, TV networks can now get ratings for their programs in real time. Read more.
Location: Westside Ballroom Level:
Kristian Hammond (Northwestern Computer Science)
As the world of data expands, the challenge of understanding it expands as well. Narrative Science is addressing this challenge with a software platform that uses data to drive the generation of compelling narratives that tell the stories contained within it. The technology tells the stories that are hidden in the numbers. Read more.
Location: Westside Ballroom Level:
Sean Gourley (Primer)
Today's high tech industries are fast-paced, with value created and destroyed at speed. Data can help where traditional intelligence approaches are expensive and slow. Read more.
Location: Westside Ballroom Level:
Michael Driscoll (Metamarkets)
Digital media publishers sit astride torrents of data about their content, audiences and advertisers. Every day, the world's two billion internet users visit millions of pages, and are exposed to more than one hundred billion online advertising impressions. Publishers of digital content need to crunch this data to predict who will visit tomorrow, and how to price the ads those visitors see. Read more.
Location: Westside Ballroom Level:
Kyle Cranmer (New York University)
Even the biggest commercial datasets can't rival those produced at CERN, home of the Large Hadron Collider. As scientists research the conditions that created our universe, the volume of data captured is truly staggering. Read more.
Location: Westside Ballroom Level:
Ariel Seidman (Gigwalk)
We all need clean, useful, validated data-- but most of us don't have an easy way to gather it and the data we do have is messy. Hear some of the numbers behind these crowds and how startups like Gigwalk are changing the way we work. Read more.


  • Aster Data
  • EMC Greenplum
  • GE
  • Lexis Nexis
  • MarkLogic
  • Tableau Software
  • Cloudera
  • DataStax
  • Informatica
  • DataSift
  • Splunk
  • 1010data
  • Amazon Web Services
  • Connotate
  • Media-Science
  • Microsoft SQL Server

Sponsorship Opportunities

For information on sponsorship opportunities at the conference, contact Susan Stewart at

Press & Media

For media-related inquiries, contact Maureen Jennings at

Contact Us

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