BigDataCamp @Strata - Feb 27, 2012BigDataCampMonday, February 27, 2012 from 5:30 PM to 10:00 PM (PST) |
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Event Details
BigDataCamp takes place the night before the O'Reilly's Strata Conference . We invite all attendees and anyone else interested in Big Data to join us for a lively discussion, finger food, and a frosty beverage or two.
BigDataCamp is an unconference for users of Hadoop and related Big Data technologies to exchange ideas in a loosely distributed format. Led by CloudCamp's Dave Nielsen, attendees are encouraged to share thoughts in open discussions with community-proposed topics, including Lightning Talks & Unconference Sessions.
Data engineers, enterprise architects, developers, analysts, data mining and business intelligence professionals are encouraged to attend and mix with other members of the community.
Location:
5001 Great America Parkway
Grand Ballroom AB
Santa Clara, CA 95054
Schedule: Feb 27, 2012
5:30pm - Registration, Finger Food & Networking
6:00pm - Welcome, Thank-you & Introductions - Dave Nielsen
7:15pm - Organize Unconference
7:30pm - Breakout Sessions - Round 1
8:15pm - Breakout Sessions - Round 2
9:00pm - Breakout Sessions - Round 3
9:45pm - Wrap Up (1 minute summary of each session)
10:00pm - Drinks? Marriott Hotel Bar?
Organizer & Facilitator:
Dave Nielsen of Platform D
Volunteers:
- To volunteer, email dave@platformd.com
Follow us at http://twitter.com/bigdatacamp
Register for O'Reilly's Strata Conference using discount code BDC20 and get 20% off
Thank you to our supporters:
Tag Cloud based on Topics Proposed During Registration:
access alternatives analysis analytics architecture aws based batch best business case cloud computing data distributed exists file financial flume full future getting going graphs hadoop hdfs important language learning management map-reduce mining models nlp nosql practices predictive processing real-time report social solutions storage structured system text used visualization wants web
Topics of interest from attendees:
| "anything petabyte scale, computer vision, video processing.” |
| "how Big Data can help solve analytics problems” |
| "how to make optimal use of the map/reduce pattern for efficient data queries on big data" |
| "leverage the rich libraries in R” |
| "new approaches to managing and searching over large data.” |
| "NoSQL solutions (MongoDB, Hadoop, Graph databases)” |
| "time-series Big Data ” |
| "tool and languages that best support implementation of the map/reduce pattern” |
| “Analytics (reporting and analysis)" |
| “Analytics" |
| “Analytics” |
| “analytics” |
| “Analytics” |
| “Analyzing big data with R and hadoop” |
| “Architecture of distributed data processing systems, new trends and tools in NoSQL.” |
| “AWS deployment” |
| “Behavioral data ecommerce” |
| “Best ways to leverage big data to benefit global conditions (i.e. health, environment, energy, etc.).” |
| “BI database, BI tool” |
| “Big Data analytics” |
| “Big Data Analytics” |
| “Big data related analysis tool and software. ” |
| “business insight” |
| “business strategy and networking” |
| “Cassandra” |
| “Challenges faced by people in implementing Big Data strategy - political , business, technical, lack of skills etc.” |
| “click stream” |
| “Cloud based computing” |
| “Cloud BI, PaaS” |
| “Commercial applications of big data. Social gaming analytics.” |
| “consumption data and which database is best suited for it.” |
| “Cross-category commerce personalization and relevance.” |
| “Currently fraud detection. But it's all the same problem.” |
| “Data about the physical world; especially, over long periods of time. E.g,, world commercial air traffic flight information, wide-area meteorological data, and the prices for petroleum-based fuels over decades. ” |
| “data analysis” |
| “data analytics” |
| “data analytics” |
| “data imports into hadoop. ” |
| “Data mining, Hadoop, Map Reduce” |
| “Data mining, impact metrics, bibliometrics, research, recommendation, R” |
| “Data mining.” |
| “Data mining” |
| “Data mining” |
| “Data mining” |
| “Data scalability question and which NoSQL solution is good for which use case.” |
| “Databases and storage” |
| “Effects of no ACID on sites.” |
| “Financial Services Regulations and Big Data Analytics.” |
| “Focus on equity and commodities investment data management, how to irganize it and how to take advantage of cloud based resources to mine it. ” |
| “graph, clustering, batching, aggregation engine.” |
| “Hadoop / Hive” |
| “Hadoop and R” |
| “Hadoop compression” |
| “Hadoop deployments and reporting tools” |
| “Hadoop stack application and implementation.” |
| “Hadoop, AI/ML, Big data for both consumers and enterprises” |
| “Hadoop, Big Data Management” |
| “Hadoop, HBase, Hive” |
| “Hadoop, HBase” |
| “hadoop, mongodb, neo4j” |
| “Hadoop, NoSQL” |
| “Hadoop,tools” |
| “Hadoop” |
| “Hadoop” |
| “hadoop” |
| “hadoop” |
| “hadoop” |
| “Hadoop” |
| “Hadoop” |
| “Hadoop” |
| “Hardware systems and interfaces. Connectivity to the outside world...” |
| “HBase, Map-Reduce v2, Namenode federation” |
| “HBase/Cassandra/MondoDB” |
| “hive, cassandra, hbase” |
| “How Big Data in high tech companies?” |
| “How role does Big Data play as part of an overall Information Management strategy?” |
| “how to effectively get relevant data.” |
| “How to scale NLP work without more processors. ” |
| “how to select the right parallel algorithm for your problem requirements and computing architecture” |
| “Interested in assembling a toolkit of Big Data analyltics tools.” |
| “interpret photo images” |
| “Machine Learning for traffic pattern ” |
| “Machine learning” |
| “Machine Learning” |
| “Mahout” |
| “MapReduce and Asynchronous ” |
| “New Technology & Algorithms, Performance Techniques, NoSQL, Data Mining.” |
| “Nosql data-analytics structured+unstructured” |
| “NoSQL dbs, flash disks, R3 database systems” |
| “nosql, hadoop” |
| “NoSql” |
| “NoSQL” |
| “Open Source” |
| “Opportunities” |
| “parallel processing” |
| “Personalization and recommendation engines” |
| “platforms, best practices, startups” |
| “Popularity of Hadoop platform and examples of the types of analytics and performance” |
| “Privacy, Text Analytics, Security” |
| “R programming” |
| “R with Hadoop” |
| “Real Time and Streaming Analytics” |
| “Real world implementations exploring data modeling on eventual consistenct architectures.” |
| “real-time analytics” |
| “Real-time analytics” |
| “real-time, low-latency capture and analytics” |
| “Recent research done regarding Apache Hadoop” |
| “Recommender Systems, Sentiment Analysis using Big Data technology” |
| “Retail analytics” |
| “Retail Applications” |
| “Scalable infrastructure, hosted infrastructure services.” |
| “Scale out for structured data analytics” |
| “Social gaming, mobile analytics” |
| “social graph” |
| “Talks by big data companies or networking opportunities with such companies” |
| “the big picture of big data...the infrastructure, personnel, and ability to put big data into action to solve critical business issues, improve customer relations and *gasp* change the world!” |
| “Tools Implementing Big Data Analytic and BI implementation” |
| “trends, architecture, new area of applications...” |
| “use cases, sucess / failure factors for big data projects, organizational changes necessary for the fruitful work with big data.” |
| “Using multiple NOSQL tools in one solution (i.e., the right tool for the right (part of the) job).” |
| “Venture opportunity” |
| “visualization of large data sets, sparse matrix processing” |
| “We are using MongoDB, and could use insight into managing db consistency. ” |
| “web development/databases/php/mysql” |
| “What are the common practices people using today for big data? Any specific technology as the status quo, any upcoming ones?” |
| “Why is Big Data soo important. ” |
| big data and searching.” |
| data visualization |
| opportunities |
| performance monitoring” |
| security |
When & Where
Santa Clara Convention Center
5001 Great America Parkway
Grand Ballroom AB
Santa Clara,
CA 95054
Monday, February 27, 2012 from 5:30 PM to 10:00 PM (PST)
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BigDataCamp
BigDataCamp is an unconference for users of Hadoop and related technologies to exchange ideas in a loosely distributed format.
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