AWS Big Data Blog

AWS Big Data Analytics Sessions at re:Invent 2015

by Roy Ben-Alta | on | | Comments

Roy Ben-Alta is a Business Development Manager – Big Data & Analytics

If you will be attending re:Invent 2015 in Las Vegas next week, you know that you’ll have many opportunities to learn more about Big Data & Analytics on AWS at the conference–and this year we have over 20 sessions! The following breakout sessions compose this year’s Big Data & Analytics track.

Didn’t register before the conference sold out? All sessions will be recorded and made available on YouTube after the conference. Also, all slide decks from the sessions will be made available on SlideShare.net after the conference.

Click any of the following links to learn more about a breakout session.

Deep Dive Customers Use cases

BDT303 – Running Spark and Presto on the Netflix Big Data Platform
BDT306 – The Life of a Click: How Hearst Publishing Manages Clickstream Analytics with AWS
BDT307 – Zero Infrastructure, RealTime Data Collection, and Analytics
BDT312 – Application Monitoring in a Post-Server World: Why Data Context Is Critical
BDT314 – Running a Big Data and Analytics Application on Amazon EMR and Amazon Redshift with a Focus on Security
BDT318 – Netflix Keystone: How Netflix Handles Data Streams Up to 8 Million Events Per Second 
BDT404 – Building and Managing LargeScale ETL Data Flows with AWS Data Pipeline and Dataduct
DAT308 – How Yahoo! Analyzes Billions of Events a Day on Amazon Redshift
DAT311 – Large-Scale Genomic Analysis with Amazon Redshift
BDT323 – Amazon EBS and Cassandra: 1 Million Writes Per Second on 60 Nodes
BDT322 – How Redfin and Twitter Leverage Amazon S3 to Build Their Big Data Platforms
MBL314 – Building World-Class, Cloud-Connected Products: How Sonos Leverages Amazon Kinesis

Services Sessions (Amazon EMR, Amazon Kinesis, Amazon Redshift, AWS Data Pipeline and Amazon DynamoDB)

BDT208 – A Technical Introduction to Amazon Elastic MapReduce
BDT305 – Amazon EMR Deep Dive and Best Practices
BDT313 – Amazon DynamoDB for Big Data
BDT401 – Amazon Redshift Deep Dive: Tuning and Best Practices
BDT316 – Offloading ETL to Amazon Elastic MapReduce
BDT403 – Best Practices for Building Realtime Streaming Applications with Amazon Kinesis
BDT206 – How to Accelerate Your Projects with AWS Marketplace 
DAT201 – Introduction to Amazon Redshift

Architecture and Best Practice

BDT317 – Building a Data Lake on AWS 
BDT310 – Big Data Architectural Patterns and Best Practices on AWS
BDT402 – Delivering Business Agility Using AWS
BDT309 – Data Science & Best Practices for Apache Spark on Amazon EMR
DAT204 – NoSQL? No Worries: Building Scalable Applications on AWS NoSQL Services
SM303 – Migrating Your Enterprise Data Warehouse to Amazon Redshift

Machine Learning

BDT311 – Deep Learning: Going Beyond Machine Learning
BDT302 – RealWorld Smart Applications With Amazon Machine Learning
BDT207 – RealTime Analytics In Service of SelfHealing Ecosystems

Workshops

BDT205 – Your First Big Data Application on AWS
WRK301 – Implementing Twitter Analytics using Spark Streaming, Scala, and AWS EMR
WRK303 – Realworld Data Warehousing with Redshift, Kinesis and AWS Marketplace
WRK304 – Recommendation Engine using Amazon Machine learning in Realtime

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