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Media Sessions

From targeted advertising to personalized recommendations to product development, companies are just starting to reap the benefits of big data real-time analytics. Learn from the latest case studies of how media companies are employing data technologies.

Related sessions

11:50am–12:30pm Tuesday, 10/29/2013
Adam Kawa (GetInData)
Slides:   1-PDF 
A trip into Hadoop jungle to show the most interesting, exciting and surprising places where we have been to while growing fast from a 60 to 690-node Hadoop cluster. We will expose our JIRA tickets, real graphs, statistics, even excerpts from our dialogues. We will share the mistakes that we made and describe the fixes that finally domesticated this love-demanding yellow elephant and its friends.
1:30pm–1:50pm Monday, 10/28/2013
Amanda Gerdes (Blizzard Entertainment), Brian Griffith (Blizzard Entertainment)
Video game data is as rich and exciting as the player experience it represents. From loot drops in Diablo III to race balance in StarCraft 2 to the entire World of Warcraft, the data is evocative, powerful... and intimidatingly large. This session highlights the critical role of Hadoop in creating and sustaining a rich, agile data environment capable of supporting real-time streaming game data.
1:45pm–2:25pm Tuesday, 10/29/2013
Giorgia Lupi (Accurat)
How can a data-driven visualization tell multiple interplaying stories, and achieve a viable result in an abstract visual composition?
11:50am–12:30pm Wednesday, 10/30/2013
Chris Lintz (Comcast), Gabriel Commeau (Comcast)
Slides:   1-PPTX 
Real-time analytics produced by IP video players help ensure that Comcast delivers the highest quality experience to customers. While ingesting as many messages as Tweets produced every day, these real-time insights are achieved through an in-house architecture leveraging Flume NG and Storm.
1:45pm–2:25pm Wednesday, 10/30/2013
Slides:   1-ZIP    external link
Voice of the customer (VOC) data is a rapidly growing, unstructured, untapped data source – for your web site and across social media sites. Topic discovery through clustering of user verbatims, integrated with decision support data, can unleash valuable, actionable insights from millions of customers.
9:20am–9:30am Wednesday, 10/30/2013
Shawndra Hill (University of Pennsylvania)
In this keynote I will discuss how TV networks and advertisers can derive value from all of the online social activity about TV.
1:50pm–2:10pm Monday, 10/28/2013
Alex Wright (
For most of us who work on the Web, it's almost impossible to imagine a world without browsers. But in the years leading up to Tim Berners-Lee's world-changing invention, several other visionary information scientists were exploring alternative systems that anticipated - and in some ways surpassed - today's Web.
11:50am–12:30pm Wednesday, 10/30/2013
Richard Brath (Uncharted Software), David Jonker (Uncharted Software Inc.)
Slides:   1-PDF 
Visualizations of big graphs often look like spaghetti and can be difficult to use. Working backwards from the analytic questions, we will show some very different 2D and 3D visualizations for social networks. We'll also cover some of the challenges and discuss some open source tools.
9:40am–9:50am Tuesday, 10/29/2013
Claudia Perlich (Dstillery)
Coverage of online advertising fraud finally hit the newsstand a few months ago. But the story really started much earlier. Somewhat surprisingly it was predictive modeling on large data streams from real time bid environment that was the first to pick up symptoms of the yet largest online advertising scam. We tell the tale where models “too good to be true” lead to quite a sinister discovery.


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