Strata 2012 Schedule

Below are the confirmed and scheduled talks at Strata 2011 (schedule subject to change).

Customize Your Own Schedule

Create your own Strata schedule using the personal scheduler function. Mark the tutorials, sessions, keynotes, and events you want to attend by clicking on the calendar icon [calendar icon] next to each listing. Then click on "personal schedule" below and get your own customized schedule generated.

Mission City B1
10:40am Is this normal? Finding anomalies in real-time data Theo Schlossnagle (OmniTI/Circonus)
1:30pm Mining Unstructured Data: Practical Applications Alyona Medelyan (Pingar), Anna Divoli (Pingar)
2:20pm Migratory data: the distributed data you carry with you Alasdair Allan (The Thing System, Inc.)
4:00pm Humans, Machines, and the Dimensions of Microwork Daniel Tunkelang (LinkedIn), Claire Hunsaker (Samasource)
4:50pm Big Data and Bibliometrics: Crowdsourcing the World's Largest Database of Research Jan Reichelt (Mendeley Ltd.), William Gunn (Mendeley Research Networks)
Mission City B4
10:40am Democratizing BI at Microsoft: 40,000 Users and Counting Kirkland Barrett (Microsoft)
11:30am Helping Banks Build Better Relationships Schwark Satyavolu (Truaxis)
1:30pm Data Jujitsu: The Art of Turning Data into Product DJ Patil (Greylock Partners)
4:00pm Big Data Meets Big Weather Siraj Khaliq (The Climate Corporation)
4:50pm Improving Productivity Using Real-Time Data Jacomo Corbo (QuantumBlack)
Ballroom AB
10:40am Video Graphics - Engaging and Informing Max Gadney (After The Flood)
11:30am Rich Sports Data and Augmented Reality Ryan Ismert (Sportvision, Inc)
1:30pm Visualizing Geo Data Jason Sundram (Facebook)
2:20pm Beautiful Vectors: Emerging Geospatial technologies in the browser Mano Marks (Google, Inc. ), Chris Broadfoot (Google)
4:00pm From Big Data to Big Insights Robbie Allen (Automated Insights, Inc.)
4:50pm Exploring the Stories Behind the Data Cheryl Phillips (The Seattle Times)
Ballroom CD
11:30am Hadoop Analytics in Financial Services Stefan Groschupf (Datameer)
1:30pm Using Map/Reduce To Speed Analysis of Video Surveillance JP Morgenthal (EMC Consulting)
2:20pm Beyond Map/Reduce: Getting Creative With Parallel Processing Ed Kohlwey (Booz Allen Hamilton)
4:00pm Petabyte Scale, Automated Support for Remote Devices Ron Bodkin (Think Big Analytics), Kumar Palaniappan (NetApp)
4:50pm Big Analytics Beyond the Elephants Paul Brown (Paradigm4 Inc.)
Ballroom E
10:40am If Data Wants to Be Free, is Privacy a Prison? Alexander Howard (O'Reilly Media), Jim Adler (inome), Solon Barocas (New York University)
11:30am Pretty Simple Data Privacy Kaitlin Thaney (Mozilla Science Lab), Betsy Masiello (Google), John Wilbanks (Kauffman Foundation for Entrepreneurship)
2:20pm It's Not "Junk" [Data] Anymore Kaitlin Thaney (Mozilla Science Lab), Mark Hahnel (FigShare), Ben Goldacre (Bad Science)
4:00pm Big Data for the Common Good Virginia Carlson (Urban Rubrics), Jake Porway (DataKind)
4:50pm Personalized Medicine and Individual Cancer Care, it is a data problem Peter Kuhn (Scripps Physics Oncology)
GA J
1:30pm Analytics from 330 million smartphones Sean Byrnes (Flurry, Inc.)
2:20pm Connecting Millions of Mobile Devices to the Cloud James Phillips (Couchbase, Inc.)
4:50pm Mapping social media networks (with no coding) using NodeXL Marc Smith (Social Media Research Foundation)
Ballroom G
10:40am What's Next for Apache Hadoop Arun Murthy (Hortonworks Inc.)
1:30pm Big Data and Machine Learning: A Reality Check Alexander Gray (Skytree, Inc.)
2:20pm Big Data Big Costs? Vineet Tyagi (Impetus Technologies)
Ballroom H
11:30am Big Data and the Social Firehose Nick Halstead (DataSift)
1:30pm Big Data Applications in Action Gary Lang (MarkLogic)
2:20pm Start Innovating! Crowdsourcing and Big Data Max Yankelvich (Crowd Computing Systems, Inc.)
8:45am Plenary
Room: Mission City Ballroom
Welcome Alistair Croll (Solve For Interesting), Edd Dumbill (Silicon Valley Data Science)
8:50am Plenary
Room: Mission City Ballroom
Democratization of Data Platforms Jonathan Gosier (metaLayer Inc.)
9:05am Plenary
Room: Mission City Ballroom
5 Big Questions about Big Data Luke Lonergan (Greenplum, a division of EMC)
9:15am Plenary
Room: Mission City Ballroom
The Trouble with Taste Coco Krumme (MIT Media Lab)
9:25am Plenary
Room: Mission City Ballroom
Embrace the Chaos Pete Warden (Jetpac)
9:35am Plenary
Room: Mission City Ballroom
Open Data and the Internet of Things Usman Haque (Pachube.com)
9:45am Plenary
Room: Mission City Ballroom
Big Data’s Next Step: Applications Gary Lang (MarkLogic)
9:55am Plenary
Room: Mission City Ballroom
Using Google Data for Short-term Economic Forecasting Hal Varian (Google)
10:10am Morning Break
Room: Exhibit Hall
12:10pm Lunch - Exhibit Hall Sponsored by Shared Learning Collaborative
Room: Exhibit Hall
Thursday Lunchtime BoF Tables
3:00pm Afternoon Break Sponsored by VMware
Room: Exhibit Hall
8:00am Coffee Break sponsored by IBM
Room: Mission CIty Ballroom Foyer
10:40am-11:20am (40m) Data Science
Is this normal? Finding anomalies in real-time data
Theo Schlossnagle (OmniTI/Circonus)
In today's environments, we're often forced to collect data before we know if it will be useful. This tendency leads toe seas of data, flowing in real-time with very little structure or understanding of what the data means. Given that, how can you tell when data "is normal?" Let's find out.
11:30am-12:10pm (40m) Data Science
From Predictive Modelling to Optimization: The Next Frontier
Jeremy Howard (Kaggle)
In "The Evolution of Data Products", O'Reilly Media's Mike Loukides notes: "the question of how we take the next step — where data recedes into the background — is surprisingly tough." Jeremy Howard will show why this is tough, and what to do about it. He will show how predictive modelling, simulation, and optimization can be combined to deliver results instead of just delivering data.
1:30pm-2:10pm (40m) Data Science
Mining Unstructured Data: Practical Applications
Alyona Medelyan (Pingar) et al
In this session we discuss approaches to mining unstructured data that gradually find their way into the real world. Text mining and analytics algorithms strive to identify documents’ categories, main topics, mentioned names and other entities; they summarize and detect sentiment. We describe case studies that take advantage of such algorithms in the legal, forensics and healthcare sectors.
2:20pm-3:00pm (40m) Data Science
Migratory data: the distributed data you carry with you
Alasdair Allan (The Thing System, Inc.)
Big data isn't just about multi-terrabyte data sets hidden inside eventually-concurrent distributed databases in the cloud. It's also about the hidden data you carry with you all the time. This talk will discuss the data that you carry with you all the time; the data on your cell phone and other mobile devices, along with the possibilities for making use of that hidden data.
4:00pm-4:40pm (40m) Data Science
Humans, Machines, and the Dimensions of Microwork
Daniel Tunkelang (LinkedIn) et al
In this talk, we will analyze various dimensions of microwork that characterize applications, tasks, and crowds. Drawing on our experience at companies that have pioneered the use of microwork (Samasource) and data science (LinkedIn), we will offer practical advice to help you design crowdsourcing workflows to meet your data product needs.
4:50pm-5:30pm (40m) Data Science
Big Data and Bibliometrics: Crowdsourcing the World's Largest Database of Research
Jan Reichelt (Mendeley Ltd.) et al
Mendeley is a New York and London-based startup that has crowdsourced the world's largest database of academic literature. Over 1M researchers strong, Mendeley is taking academia to the cloud.
10:40am-11:20am (40m) Business & Industry
Democratizing BI at Microsoft: 40,000 Users and Counting
Kirkland Barrett (Microsoft)
A high level overview of Microsoft IT's BI strategy and it's various applications, focusing on Self Service BI, Scorecards and Dashboards, Data Visualizations, and Leadership Decision making through robust BI tools.
11:30am-12:10pm (40m) Business & Industry
Helping Banks Build Better Relationships
Schwark Satyavolu (Truaxis)
By charging interchange fees for retailers and account fees for customers banks have taken a ‘combative’ approach for revenue generation. However, technologies are emerging that enable financial institutions to leverage big data drawn from the transaction data stream to provide new, pro-consumer revenue streams.
1:30pm-2:10pm (40m) Business & Industry
Data Jujitsu: The Art of Turning Data into Product
DJ Patil (Greylock Partners)
What does it really take to build a data product? Recall and relevancy are only parts of the challenge. In fact, an entire new approach is required to build consistently great data products.
2:20pm-3:00pm (40m) Business & Industry
Data Marketplaces for your extended enterprise: Why Corporations Need These to Gain Value from Their Data
Piyush Lumba (Microsoft) et al
One of the most significant challenges faced by individuals and organizations is how to discover and collaborate with data within and across their organizations, which often stays trapped in application and organizational silos.
4:00pm-4:40pm (40m) Business & Industry
Big Data Meets Big Weather
Siraj Khaliq (The Climate Corporation)
Due to recent advancements in Big Data, cloud computing, and network maturity it's now possible to work with extremely large weather-related data sets. The Climate Corporation CTO Siraj Khaliq discusses how to apply big data principles to the real-world challenge of protecting people and businesses from the financial impact of weather.
4:50pm-5:30pm (40m) Business & Industry
Improving Productivity Using Real-Time Data
Jacomo Corbo (QuantumBlack)
Measuring productivity remains a notoriously difficult problem. We will show how real-time collaboration data are being leveraged to measure, model and forecast organizational productivity and performance in the innovation teams at Boeing and in 3 Formula One teams. On the back of these forecasts, we will show how investment yields were improved by 15% and productivity raised by nearly 20%.
10:40am-11:20am (40m) Visualization & Interface
Video Graphics - Engaging and Informing
Max Gadney (After The Flood)
The use of video to communicate data is on the rise, but what is the most effective way to do this? Highlighting our current work with the BBC in this field we will look at best practice from storytelling principles to choosing the right visual treatment.
11:30am-12:10pm (40m) Visualization & Interface
Rich Sports Data and Augmented Reality
Ryan Ismert (Sportvision, Inc)
Long a staple of broadcast sports, augmented reality (AR) effects (like the virtual "1st and 10" line) are increasingly being driven by digital records of sports events (DREs), collected and distributed live, such as NASCAR's race car tracking system and MLB's PitchFX. The next generation of DRE-derived data will expand the use of AR to more effectively show key "invisible" elements of the game.
1:30pm-2:10pm (40m) Visualization & Interface
Visualizing Geo Data
Jason Sundram (Facebook)
With the explosion of mobile devices, there is a plethora of geo-tagged data available for mining and visualization. To make compelling visualizations, it is often necessary to build tools that allow users to easily explore, mine, map, and market this data. This talk will focus on how to use several open-source frameworks to build such visualizations.
2:20pm-3:00pm (40m) Visualization & Interface
Beautiful Vectors: Emerging Geospatial technologies in the browser
Mano Marks (Google, Inc. ) et al
Beautiful, useful and scalable techniques for analysing and displaying spatial information are key to unlocking important trends in geospatial and geotemporal data. Recent developments in HTML 5 enable rendering of complex visualisations within the browser, facilitating fast, dynamic user interfaces built around web maps. This session will examine emerging technologies that will shape the geoweb.
4:00pm-4:40pm (40m) Business & Industry
From Big Data to Big Insights
Robbie Allen (Automated Insights, Inc.)
The ultimate utility of Big Data is transforming it into Big Insights. Charts, graphs, and tables of aggregated data are useful but still require interpretation by the end user. With advances in linguistic algorithms and data processing it is now possible to derive meaningful insights from data and present them in digestible narrative content.
4:50pm-5:30pm (40m) Visualization & Interface
Exploring the Stories Behind the Data
Cheryl Phillips (The Seattle Times)
A story or report on a subject by its very nature summarizes the underlying data. But readers may have questions specific to a time, date or place. Visualizing the data and providing effective, targeted ways to drill deeper is key to giving the reader more than just the story.
10:40am-11:20am (40m) Hadoop & Big Data: Applied
Mining the Eventbrite Social Graph for Recommending Events
Vipul Sharma (Eventbrite)
This talk will go in details, architecture and challenges of building a recommendation system on a massive social graph. The talk will describe how we applied learning on large datasets using Apache Hadoop and how we scaled millions of reads and writes. We will also showcase Eventbrite's data platform architecture.
11:30am-12:10pm (40m) Hadoop & Big Data: Applied
Hadoop Analytics in Financial Services
Stefan Groschupf (Datameer)
This session discusses financial services use cases and challenges in using Hadoop analytics including long-term storage and analytics of transactions, identifying cross and up sell opportunities by analyzing web log files and customer profiles, value-at-risk analytics, and understanding the SLA issues and identifying problems in a thousands-of-nodes, big-services oriented architecture.
1:30pm-2:10pm (40m) Hadoop & Big Data: Applied
Using Map/Reduce To Speed Analysis of Video Surveillance
JP Morgenthal (EMC Consulting)
Hundreds of hours of video recordings culled from multiple cameras. Most of these recordings hold little value as the scene does not change for extended periods of time. For organizations that must keep the original in tact, analyzing these recordings can be very difficult. Using Map/Reduce we can harness parallel processing to identify and tag useful periods of time for faster analysis.
2:20pm-3:00pm (40m) Hadoop & Big Data: Applied
Beyond Map/Reduce: Getting Creative With Parallel Processing
Ed Kohlwey (Booz Allen Hamilton)
Map/Reduce has created tremendous interest in parallel programming and big data analytics, but it isn't always the right tool for the job. Many new projects have emerged in this space over the last year including two cluster schedulers (YARN and Mesos) and numerous parallel computing environments. We'll provide an introduction to these new technologies, including some you might not have heard of.
4:00pm-4:40pm (40m) Hadoop & Big Data: Applied
Petabyte Scale, Automated Support for Remote Devices
Ron Bodkin (Think Big Analytics) et al
NetApp collects 250 TB per year of unstructured data from devices that phone home. They need to be able to do ad hoc analysis and build predictive models for device support and cross-sales. We discuss our experiences building a Big Data system with NetApp using Hadoop and HBase to improve customer service, drive sales and develop better products.
4:50pm-5:30pm (40m) Data Science
Big Analytics Beyond the Elephants
Paul Brown (Paradigm4 Inc.)
The science and commercial worlds share requirements for a high performance informatics platform to support collection, curation, collaboration, exploration, and analysis of massive datasets. SciDB is an open source analytical database that provides seamlessly integrated massively scalable analytics. We present performance and scalability for non-embarrassingly parallel operations.
10:40am-11:20am (40m) Policy & Privacy
If Data Wants to Be Free, is Privacy a Prison?
Alexander Howard (O'Reilly Media) et al
So much of the privacy discussion is about data access, fear of future dystopia, and the complexities of law. There is a vacuum around how societal norms should be mapped to rapidly growing capabilities of big data, leaving data professionals in a "don’t ask don't tell" privacy conundrum. This conversation will discuss specific use-cases and frameworks to guide data pros.
11:30am-12:10pm (40m) Policy & Privacy
Pretty Simple Data Privacy
Kaitlin Thaney (Mozilla Science Lab) et al
Making sense of the privacy issues around personal data is way too complicated. Pretty Simple Data Privacy builds on the idea that users need three options - Yes, No, Maybe - to control privacy settings on their personal data. We'll explore existing projects and codebases that implement legal and technical tools for all three of the settings.
1:30pm-2:10pm (40m) Business & Industry
OODA Loop: How to Understand the Use Cases for Big Data
J. C. Herz (Batchtags LLC)
This talk uses the OODA Loop concept (Observe, Orient, Decide, Act) as a framework to categorize Big Data use cases and data-driven services and the front-ends to those services. Rather than starting with the underlying technology or the data sources, the OODA loop starts with WHY the user needs information. It answers the question of when a black box beats an analytic tool, and vice versa.
2:20pm-3:00pm (40m) Policy & Privacy
It's Not "Junk" [Data] Anymore
Kaitlin Thaney (Mozilla Science Lab) et al
In a research environment, under the current operating system, most data and figures collected or generated during your work is lost, intentionally tossed aside or classified as “junk”, or at worst trapped in silos or locked behind embargo periods. In the digital age, this does not need to be the case - and it's imperative we change that reality.
4:00pm-4:40pm (40m) Policy & Privacy
Big Data for the Common Good
Virginia Carlson (Urban Rubrics) et al
The “common good” challenge for Big Data is to deliver actionable information that can be used by nonprofits and civic orgs. But that challenge isn’t new. Existing data intermediaries for NGOs have a rich history of working in common-good territory. Let’s discuss. What is this history? What can we take away from it to inform new, perhaps disruptive, approaches to meet this challenge?
4:50pm-5:30pm (40m) Data Science
Personalized Medicine and Individual Cancer Care, it is a data problem
Peter Kuhn (Scripps Physics Oncology)
Metastasis is the lethal form of cancer. Metastasis arises through cancer cells traveling through the blood of the patient and colonizing in other organs. Finding and characterizing these cells enables the prediction and monitoring of response to cancer treatments.
10:40am-11:20am (40m) Hadoop & Big Data: Tech
Apache Cassandra: NoSQL Applications in the Enterprise Today
Jonathan Ellis (DataStax)
NoSQL, Big Data, massive scale, real-time, in the cloud, do I need it, do I want it, how the heck can I even know if it’s right for me? Choosing any database solution is a critical and tricky decision. Navigating the murky waters of NoSQL can be even tougher.
11:30am-12:10pm (40m) Hadoop & Big Data: Tech
Storm: distributed and fault-tolerant realtime computation
Nathan Marz (Twitter)
Storm is an open-source realtime computation system relied upon by Twitter for much of its analytics. Storm does for realtime computation what Hadoop did for batch computation. It has a huge range of applications and combines ease of use with a robust foundation.
1:30pm-2:10pm (40m) Hadoop & Big Data: Tech
Analytics from 330 million smartphones
Sean Byrnes (Flurry, Inc.)
Flurry provides an analytics and advertising platform for smartphone applications. Every month we track over 20 billion sessions across over 330 million devices. This talk will go over the Hadoop and HBase architecture we run and the challenges we face managing a massively growing data set.
2:20pm-3:00pm (40m) Hadoop & Big Data: Tech
Connecting Millions of Mobile Devices to the Cloud
James Phillips (Couchbase, Inc.)
Mobile devices offer boundless opportunities for collection and presentation of temporally- and spatially-relevant data. But there are obstacles: intermittent connectivity as well as processing, storage and other constraints. Featuring real-world apps, this session covers device data collection; device-device and device-cloud data synchronization; and data aggregation and analysis in the cloud.
4:00pm-4:40pm (40m) Hadoop & Big Data: Tech
Open Source Ceph Storage– Scaling from Gigabytes to Exabytes with Intelligent Nodes
Sage Weil (Inktank)
Data storage needs are increasing at an exponential rate. Incumbent storage systems are proprietary, expensive to buy and expensive to maintain. With the advent of the cloud, everyone expects auto scaling. Ceph storage is a massively scalable storage system that aims to fill the distributed storage system void.
4:50pm-5:30pm (40m) Visualization & Interface
Mapping social media networks (with no coding) using NodeXL
Marc Smith (Social Media Research Foundation)
Maps of the complex connections that form when people link, like, reply, rate, review, favorite, friend, follow, edit, and mention one another can reveal important trends. It is possible to create network maps with free and open tools that identify key people and sub-groups in any social media population with just a few key clicks. Can you make a pie chart? You can now make a network chart.
10:40am-11:20am (40m) Sponsored Session
What's Next for Apache Hadoop
Arun Murthy (Hortonworks Inc.)
This presentation will cover the next generation of Apache Hadoop, known as hadoop-0.23. Learn how MapReduce has been re-architected by the community to improve reliability, availability and scalability as well as adding support for alternate programming paradigms. Also learn about HDFS Federation, which allows for significant scalability improvements, as well as other important advancements.
11:30am-12:10pm (40m) Sponsored Session
Solving big data analytics with an emerging data-centric language
David Miller (LexisNexis)
In this session, attendees will learn about a new method for solving big data analytics via HPCC Systems, an open-source enterprise proven platform for Big Data. A case study will be given using patent data to demonstrate how big data can be process, linked, analyzed, searched and delivered to answer various queries.
1:30pm-2:10pm (40m) Sponsored Session
Big Data and Machine Learning: A Reality Check
Alexander Gray (Skytree, Inc.)
Machine learning (ML) holds the key to the most advanced uses of big data. But is ML really possible on big data with state-of-the-art methods, or just simple ones? Can ML really be done in real time today? Is MapReduce the right answer? The cloud? I will review the current state of ML technology both at the research level and the industry-readiness level, and current best solution options.
2:20pm-3:00pm (40m) Sponsored Session
Big Data Big Costs?
Vineet Tyagi (Impetus Technologies)
The session will talk about costs involved in Big Data projects, covering the apparent and also hidden aspects of these costs. It will also discuss how to build a Big Data solution with lower cost of “per TB Data Managed and Analyzed”.
10:40am-11:20am (40m) Sponsored Session
Big Data Meets the Big Cloud: How To Monitor Thousands of Servers
Gary Dusbabek (Rackspace)
Monitoring thousands of servers generates a lot of data. Many organizations trying to harness enormous amounts of data struggle with the same types of challenges as the Rackspace cloud monitoring team. Find out how Rackspace uses NoSQL technology, distributed concepts, and open source software in novel ways to produce a multi-region cloud monitoring API.
11:30am-12:10pm (40m) Sponsored Session
Big Data and the Social Firehose
Nick Halstead (DataSift)
Nick Halstead CTO of DataSift will talk about Hadoop, HBase and dealing with storing and processing a billion tweets every 3 days. You will get insights into the architecture, pitfalls and real-world lessons on using Big Data technologies.
1:30pm-2:10pm (40m) Sponsored Session
Big Data Applications in Action
Gary Lang (MarkLogic)
Gary Lang, Senior VP Engineering, MarkLogic, will discuss the concept of Big Data Applications and walk through three in-production implementations of Big Data Applications in action.
2:20pm-3:00pm (40m) Sponsored Session
Start Innovating! Crowdsourcing and Big Data
Max Yankelvich (Crowd Computing Systems, Inc.)
There’s a big opportunity for big data: human processing. Max Yankelevich explores the latest innovations combining the scalable quality control of artificial intelligence with the scalable human judgment of crowdsourcing to solve big data problems. Learn the surprisingly easy methods to leverage the crowd to collect, control, validate and enrich data.
8:45am-8:50am (5m) Keynote
Welcome
Alistair Croll (Solve For Interesting) et al
Opening remarks by the Strata program chairs, Alistair Croll and Edd Dumbill.
8:50am-9:05am (15m) Keynote
Democratization of Data Platforms
Jonathan Gosier (metaLayer Inc.)
Big data isn't just an abstract problem for corporations, financial firms, and tech companies. To your mother, a 'big data' problem might simply be too much email, or a lost file on her computer. We need to democratize access to the tools used for understanding information by taking the hard-work out of drawing insight from excessive quantities of information.
9:05am-9:15am (10m) Keynote
5 Big Questions about Big Data
Luke Lonergan (Greenplum, a division of EMC)
How are businesses using big data to connect with their customers, deliver new products or services faster and create a competitive advantage? Learn about the changing nature of customer intimacy and how the technologies and techniques around big data analysis provide business advantage in today's social, mobile environment – and why it is imperative to adopt a big data analytics strategy.
9:15am-9:25am (10m) Keynote
The Trouble with Taste
Coco Krumme (MIT Media Lab)
Why data can tell us only so much about food, flavor, and our preferences.
9:25am-9:35am (10m) Keynote
Embrace the Chaos
Pete Warden (Jetpac)
Why unstructured data beats structured.
9:35am-9:45am (10m) Keynote
Open Data and the Internet of Things
Usman Haque (Pachube.com)
The expected massive growth of connected device, appliance and sensor markets in the coming years - often called 'The Internet of Things' - will need a more rich concept of 'open data' than is currently common.
9:45am-9:50am (5m) Keynote
Big Data’s Next Step: Applications
Gary Lang (MarkLogic)
Big Data is about extracting value from fast, huge, varied, complex data sets. But simply crunching data is only the first step. As adoption of MapReduce and data analytic technologies increases, forward thinking companies are starting to build applications on their core data assets.
9:50am-9:55am (5m) Keynote
Dr. Richard Merkin, President and CEO of Heritage Provider Network, Announces the Winner of the Second Heritage Health Progress Prize
Richard Merkin (Heritage Provider Network)
Dr. Richard Merkin, President and CEO of Heritage Provider Network, that was recently named one of Fast Company’s 10 most innovative healthcare companies for 2012, will announce the winner of the second progress prize in the $3 million dollar Heritage Health Prize competition.
9:55am-10:10am (15m) Keynote
Using Google Data for Short-term Economic Forecasting
Hal Varian (Google)
Google Insights for Search provides an index of search activity for millions of queries. These queries can sometimes help understand consumer behavior. Hal describes some of the issues that arise in trying to use this data for short-term economic forecasts and provide examples.
10:10am-10:40am (30m)
Break: Morning Break
12:10pm-1:30pm (1h 20m) Event
Thursday Lunchtime BoF Tables
Birds of a Feather (BoF) sessions are informal roundtable discussions happening during lunch on Wed 2/29 and Thu 3/1. You can join any BoF table or start your own with a topic of your choice. The BoF sign-up board will be near the Registration area.
3:00pm-4:00pm (1h)
Break: Afternoon Break Sponsored by VMware
8:00am-8:45am (45m)
Break: Coffee Break sponsored by IBM

Sponsors

  • EMC
  • Microsoft
  • HPCC Systems™ from LexisNexis® Risk Solutions
  • MarkLogic
  • Shared Learning Collaborative
  • Cloudera
  • Digital Reasoning Systems
  • Pentaho
  • Rackspace Hosting
  • Teradata Aster
  • VMware
  • IBM
  • NetApp
  • Oracle
  • 1010data
  • 10gen
  • Acxiom
  • Amazon Web Services
  • Calpont
  • Cisco
  • Couchbase
  • Cray
  • Datameer
  • DataSift
  • DataStax
  • Esri
  • Facebook
  • Feedzai
  • Hadapt
  • Hortonworks
  • Impetus
  • Jaspersoft
  • Karmasphere
  • Lucid Imagination
  • MapR Technologies
  • Pervasive
  • Platform Computing
  • Revolution Analytics
  • Scaleout Software
  • Skytree, Inc.
  • Splunk
  • Tableau Software
  • Talend

For information on exhibition and sponsorship opportunities at the conference, contact Susan Stewart at sstewart@oreilly.com.

For information on trade opportunities with O'Reilly conferences contact Kathy Yu at mediapartners
@oreilly.com

For media-related inquiries, contact Maureen Jennings at maureen@oreilly.com

View a complete list of Strata contacts