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Saturday, March 14 • 3:30pm - 6:00pm
What Marketers REALLY Need to Know About Big Data

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ATTENTION: This session requires advance signup to attend. For Online Schedule: Please utilize the RSVP link below the description to reserve your seat. For SXSW GO App: Use the RSVP 'Find a Timeslot' link. You must have a SXSW Interactive, Gold, or Platinum badge to attend, and, you must have an activated SXsocial account (social.sxsw.com) to reserve a seat. If you have any issues with signing up, please email support@sxsw.com. VERY IMPORTANT: Because of the limited space, we recommend you arrive at least 15 minutes prior to the published start time of this session. If you have not checked in at the room you RSVPed for at least five minutes prior to the session start time, you may lose your seat to an attendee in the waiting list line.
A passion to learn and an attentive mind is all that’s required. Some experience working with data and some basic knowledge of statistics would be nice, but not required.
What to Bring:
No materials necessary.
Big data has become an ubiquitous term across disciplines – from energy to politics to gaming. Its importance has led to much technological advancement over the past years (e.g. Hadoop, Storm, Impala, Spark, etc.). Although these are essential tools for a data scientist, how much do you need to know about them in order to realize the value of big data if you are a marketer? The answer is surprisingly not much at all. As a marketer, you need to know how to turn big data into information and actionable insights that help you make better decisions. This 2.5 hour long workshop will introduce you to 3 classes of analytics—descriptive, predictive, and prescriptive—that help you extract information and glean insights from your big data. The session will also clear up some big data myths while describing a few key concepts that you need to know (through examples) in order to understand data science, whether you are looking to collaborate with one or to build a data science team.
Key Takeaways:
What is the different between data, information, and insight?
How to extract information and glean insights from your big data?
What is descriptive analytics, how it works, and how to use it?
What is social network analysis (SNA) and what kinds of insights can you get from it?
What is predictive analytics, how it works, and how to use it?
What is sentiment analysis? and what kinds of insights can you get from it?
What is prescriptive analytics, how it works, and how to use it?
What are the 3 layers of the big data processing pipeline?
How to build a data science team?
10min Intro: the power of big data through two case studies
15min Big data myth: data vs. information vs. insight
10min The 3 layers of big data processing and the 3 classes of analytic algorithms
30min Descriptive analytics—social network analysis + 1 application in influencer identification
10min Break
35min Predictive analytics—sentiment analysis + 1 application in predicting election outcome
20min Prescriptive analytics—social media optimization + 1 example
20min How to build a data science team?

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avatar for Michael Wu

Michael Wu

Chief Scientist, Lithium
Dr. Michael Wu is the Chief Scientist at Lithium, where he currently applies data-driven methodologies to investigate the complex dynamics of the social web. Michael works with big data and has developed many predictive and prescriptive social analytics with actionable insights. His... Read More →

Saturday March 14, 2015 3:30pm - 6:00pm CDT
JW Marriott Salon F

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