Live Webinar May 31st 2016 2:00 PM – 3:00 PM EDT
Duration: 1 Hour Credits: 1 PDU Category C Free
Presented by : O’Reilly

Your web, mobile, and IoT applications generate an endless stream of information.

This Information can improve the operational efficiency and insight of your business – but only if you have the right technology to quickly capture and analyze the data.

To benefit from Spark, you need to get data into Spark as fast as possible for analysis and then make the results available to applications and analysts just as fast.

Pairing Spark with a NoSQL database like Couchbase helps your enterprise get smarter, faster.

In this webinar you’ll learn:

• How you can leverage Spark and NoSQL for use cases like improving recommendations based on customer profiles and shopping carts and generating real-time alerts based on sensor data
• Three different ways for moving data between a NoSQL database and Spark – Core Spark with RDDs, Spark SQL with DataFrames, and Spark Streaming with DStreams
• How to create a feedback loop between your NoSQL database and Spark so your applications can use iterative analysis to provide the best user experience possible

Presenters:

Will Gardella (LinkedIn profile) is Director of Product Management at Couchbase where he focuses on analytics, Spark, Kafka, and search. Will is now responsible for interoperability at Couchbase, but previously he was a product manager in the big data platform team at HP, a senior director of product management at SAP HANA, and the senior director of SAP Research’s global Big Data program centered on big data and machine learning.

Michael Nitschinger, (LinkedIn profile, @daschl) is a JVM engineer at Couchbase. Michael is the architect and maintainer of the Couchbase Java SDK, one of the first completely reactive database drivers on the JVM. Michael also authored and maintains the Couchbase Spark Connector. Michael is active in the open source community, a core member of the Netty project, and also contributes to various other projects like RxJava.

PDU Category C (PMBOK 5) documentation details:
Process Groups: Planning Executing
Knowledge Areas: 5 – Scope 8 – Quality

• 5.3 Define Scope
• 6.2 Define Activities
• 8.1 Plan Quality Management
• 9.3 Develop Project Team

As a Category C, ‘Self Directed Learning’, activity remember to document your learning experience and its relationship to project management for your ‘PDU Audit Trail Folder.’

Click to register for:
How To Leverage Spark & NoSQL
For Data Driven Applications