Past Meetup

Big Data & Cloud Computing - Help, Educate & Demystify.

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Meet-up to help, educate and demystify "Big Data” & “Cloud Computing” technologies to businesses, professionals & individuals.

RAFFLE! RAFFLE! RAFFLE!
Winner Attends FREE!
MDM Data Governance Summit
July 17-18, 2013; San Francisco
Winner attends at absolute no cost.
For more info, click here. (http://www.information-management.com/conferences/mdmsanfrancisco/)

All BDC members get a discounted price of $495.
Please use this link (http://register.sourcemediaconferences.com/iebms/reg/reg_p4_promo.aspx?&sessionid=fb5fa6fh0fg6fg8eikei7) and mention LexisNexis during registration.
No promo code is needed.

Agenda:

6:00 pm – 6:25 pm :
Registration & Mixer 6:30 pm – 7:00 pm:
Data Science is Not Rocket Science.
- Sri Satish Amabati, Co-founder & CEO of Oxdata 7:15 pm – 8:00 pm:
How to start with Avro in a MapReduce world.
- Serge Blazhievsky, Big Data Hadoop Architect 8:00 pm – 9:00 pm:
Q&A Session, Networking, Mixer Details:

Data Science is Not Rocket Science
Get Big Data and Better Algorithms with H2O by 0xdata. H2O makes hadoop do math and scales statistics and machine learning over Big Data. H2O is extensible and users can build blocks using simple math legos at the core and keeps familiar interfaces like R, Excel & JSON. So big data enthusiasts and experts can explore, model and score data sets using a range of simple to advanced algorithms. H2O makes it easier to derive insights from your data through faster and better predictive modeling.
In this talk we look at design and implementation of multi-node highly parallel Generalized Linear Modeling & Distributed Random Forests. And use it to analyze Airline Dataset of 120M rows over 700+ categorical columns.

How to start with Avro (http://avro.apache.org/docs/current/) in Map Reduce world
The following technical topics will be cover at the level necessary for starting with Avro project.
• Avro schema definitions and data types
• Avro record creation
• How to create Avro schemas programmatically
• How to sort records by setting a property in schema
• How to read records from a file
• Hadoop Map-Reduce integration with Avro data
• Advantages of using Avro data over flat files or map files
• Specifics of the integration with Mapper and Reducer code
• Avro format for Map-Reduce result output
• Cascading Map-Reduce jobs
• Map-Reduce can be used to convert flat files into Avro data.

Speaker Bio:
SriSatish Ambati

Sri is co-founder and ceo of 0xdata (http://0xdata.com/) (@hexadata), the builders of H2O. H2O democratizes bigdata science and makes hadoop do math for better predictions. Before 0xdata, Sri spent time scaling R over bigdata with researchers at Purdue and Stanford. Prior to that Sri co-founded Platfora and was the Director of Engineering at DataStax. Before that Sri was Partner & Performance engineer at java multi-core startup, Azul Systems, tinkering with the entire ecosystem of enterprise apps at scale. Before that Sri was at sabbatical pursuing Theoretical Neuroscience at Berkeley. Prior to that Sri worked on nosql trie based index for semistructured data at in-memory index startup RightOrder.

Sri is known for his knack for envisioning killer apps in fast evolving
spaces and assembling stellar teams towards productizing that vision. A regular speaker in the BigData, NoSQL and Java circuit, Sri leaves trail @srisatish.

Serge Blazhievsky
Serge is an experienced developer and architect with a rich background in C++/Java and distributed systems. His latest venture, LiveOps, Inc. uses Hadoop infrastructure for all reporting needs. LiveOps Hadoop framework was completely designed by him and satisfies very strict performance and availability requirements. Serge's prior ventures include Attributor, Inc. where he designed Hadoop infrastructure used for Internet crawling and web-page analysis. He holds a Masters Degree in Computer Engineering from Santa Clara University, CA, located in the heart of Silicon Valley. Serge is a regular attendee and contributor to various Hadoop conferences including Hadoop User Group at Yahoo, the creator of Hadoop.