#BigDataMN: Minnesota's Field Guide to Analytics

We live at the intersection of Data, Math, Tech, & Business. Meaningful knowledge organizations can use as they navigate the massive landscape of information.

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This is an all day multi-track event presented by MinneAnalytics. We expect 700+ participants.

General Analytics & Basic Big Data
Hadoop & NoSQL,
Predictive Modeling
Retail, Marketing & Customer Insight Analytics
Social Media Analytics
Data Visualization


First Floor Atrium, 3M Auditorium (CSOM 1-115), Classroom CSOM 1-114, and the Executive Center.

Photos: http://www.carlsonschool.umn.edu...
View floor plans: http://www.carlsonschool.umn.edu...

Auditorium 1-115 and Classroom 1-114
View floor plans: http://www.carlsonschool.umn.edu...

Executive Center
Photos: http://www.carlsonschool.umn.edu...
View floor plans: http://www.carlsonschool.umn.edu...

60 speakers

9 sessions

Carlson School of Management

United States United States / Minneapolis

321 19th Avenue South Minneapolis, MN, 55455 - Photos and Room Maps: http://www.carlsonschool.umn.edu/about/facilities/reserve-space.html

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73 known attendees

  • Miezan Echimane
  • Sean Larson
  • Dan Atkins
  • Dennis Still
  • GraemeThickins
  • Donnie Berkholz
  • Kristina D.
  • Edward Chenard
  • shawndra hill
  • Peter Clark
  • Dave Fowler
  • brocknoland
  • Chris Malone
  • Lizzy Wilkins
  • Ward  Tongen (Wardo)
  • Lara Rubbelke
  • CH_MM
  • Tom Dow
  • Saeed Rahimi
  • Mark Pitts
  • JM Bertoncelli
  • shivani khanna
  • John Hudzina
  • Bill Preachuk
  • sai okabayashi
  • Paul DeBettignies
  • Alex Jokela
  • Nitin Mayande
  • Matt Hixson
  • Bill Hoffman
  • Carolyn Parnell
  • Jaideep Srivastava
  • ravibapna
  • Dan McCreary
  • Todd Graham
  • James Ostheimer
  • Matt Hurewitz
  • David Mathias
  • Erik Iverson
  • Leila Tite

10 people tracking this event

  • Kevin Edwards
  • james fuller
  • Benjamin Guillet
  • Joe Crowther
  • Leonardo Garrido
  • Ethan Jewett
  • Charles Nguyen
  • David Smith
  • Phil Wolff
  • Nicholas Loch

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Related books

  • Big Data: Does Size Matter?
  • Data Science at the Command Line
  • Bootstrapping Machine Learning
  • Big Data: Understanding How Data Powers Big Business
  • The Big Data Revolution
  • Lean Analytics

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