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Big Data Tech 2016 has ended
Sessions are categorized to help you find the technical level you are looking for. Mild sessions are less technical, while spicy sessions are very technical. 
RS

Ryan Stellmaker

Polaris
Data Scientist
Tuesday, June 7
 

9:00am CDT

HDFS/Hadoop Training Lab (2nd floor)Brock Noland

10:00am CDT

High Volume Streaming Data: How Amazon Web Services is Changing Our Approach P0806 (1st floor)Michael Krouze

10:45am CDT

Learning from History's Largest Source of Knowledge: The Promise and Pitfalls of Mining Wikipedia P0806 (1st floor)Shilad Sen Exploratory Data Analysis and Tag Identification with LDA model for Stack Overflow Data P1808 (2nd floor)Sona Maniyan • Ramesh Ramanujam Spark Training Lab (2nd floor)Brock Noland

11:45am CDT

Making Anyone a Hadoop User: Full-text Search with Apache Solr and Hadoop Made Easy P0806 (1st floor)Karl Lacher • Mac Noland

12:30pm CDT

Analytics for Impatient People P0806 (1st floor)Ryan Hedlund • Joe Kelleher Lunch with Data Science Teachers and Learners Garden Room (1st floor)

1:15pm CDT

Data Analysis Using Spark and Cloudera Impala Garden Room (1st floor)Kasaba Bharathi

2:00pm CDT

Developing Fast and Scalable Customer Intelligence Solutions on AWS Redshift P0838 (1st floor)Jakub Jez Using Streaming Technology to Enable Real-time Applications P0808 (1st floor)Marc Fabbo Introduction to Scala and Spark Auditorium (Fine Arts F2265)Brad Rubin

3:00pm CDT

Neural Networks for Newbies P0808 (1st floor)Theo Kanning The Benefits of Spherical Cows (Hypothetical Modeling) Garden Room (1st floor)Scott Ernst

3:45pm CDT

Counting People With a Camera and Computer Number Tables: A Talk Using Only the 1000 Most Simple Words In Our Language P0806 (1st floor)Pat Delaney