Spark for bay area big data developer
- 1. Spark Conference Global Big Data Conference is offering 3 day extensive Developer conference on Big Data. Date: March 23rd , 24th & 25th Venue : Hilton, Santa Clara
- 2. Who Should Attend Engineers Developers Networking specialists Managers Executives Students Professional Services Architects Data Analyst BI Developer/Architect QA Performance Engineers PM
- 3. Click Below Url to Register http://globalbigdataconference.com/45/santa-clara/big-data- developer-conference/attendee-registration.html
- 4. Agenda Days Big Data Track Day1 March– 23rd (7:30AM – 8:00PM) •Registration •Introduction to Big Data •Introduction to Hadoop 2.0 •HDFS Deep Dive, HDFS Lab •Use Case •MapReduce Deep Dive, MapReduce Lab •Hadoop: Amazon EC2 and CDH Setup •Use Case
- 5. Agenda Days Big Data Track Day2 March 24th (8:00AM – 8:00PM) • Introduction to NOSQL •Cassandra workshop •Use Case •Data Wrangling With R - An etude : Workshop( Krishna Sankar, Blackarrow.tv) •Breaking Into Big Data •Big Data Security : Security from Big data & Security for Big Data •Hadoop Deployment Challenge
- 6. Agenda Days Big Data Track Day3 March – 25th (8:00AM – 6:00PM) • Big Data and Cyber Security - A case study for DDoS(Dr. Satyam Priyadarshy, Halliburton) •HBase Workshop •Big Data Trends and Startups •Use Case: Convert NYSE raw data into dashboard using Hadoop eco system with no programming using SQL/Hive Query & Tableau* •Use Case: Apache Spark after Dark(Chris Fregly, Author of Effective Spark & Databricks)
- 7. Agenda Days Big Data Track II Day2 March – 24th (10:00AM – 8:00PM) •Introduction to NOSQL •MongoDB Workshop •Neo4J Workshop •Big Data Security : Security from Big data & Security for Big Data •Breaking Into Big Data •Hadoop Deployment Challenges
- 8. Agenda Days Big Data Track II (Big Data Analytics with Spark(Full day workshop)) Day3 March – 25th (9:00AM – 6:00PM) •Spark Core •Spark SQL •Spark Streaming •Machine Learning and MLlib •Scala •Advanced Spark •Big Data Trends and Startups •Scala Lab •Spark Core Lab •Spark SQL Lab •MLib Lab Spark Streaming lab