PASS Business Analytics Conference 2014
Last year the Professional Association of SQL Server (PASS) tried something new with the Business Analytics Conference. I was lucky enough to attend and I thought it was a hit. There was a diverse set of sessions ranging from traditional Microsoft BI to where open source solutions such as R can fit in an organization. Also, the keynotes where some of the best I’ve seen in years with Ariel Netz rocking PowerBI presentations and Stephen Levitt absolutely killing it with his take on analytics. I’m expecting the PASS BA Conference of 2014 to be even better. If you haven’t registered and would like to spend some time in Northern California in May, register here.
I’m very excited about presenting at the PASS Business Analytics conference with one of my teammates from the Big Data Center of Expertise – Tammy Richter Jones. Our session will focus on The Role of PDW (AU1) & Polybase in the Modern Data Warehouse. If you are interested in PDW and are wondering what Microsoft’s story is for integrating it into the larger ecosystem of Big Data and a Modern Data Warehouse, I suggest you attend our session. This session is something we’ve been working on for a while and we know you will come away from the session not only informed about the technicalities of how SQL Server PDW works but also be better prepared to utilize all of its new features in your environment.
In this session, we’ll introduce and discuss the architecture of SQL Server 2012 Parallel Data Warehouse and the new Appliance Update 1. Specifically, we’ll dig into Transparent Data Encryption, Integrated Authentication, the new HDInsight Region, and functionality for adding capacity to an appliance. We’ll also discuss Polybase in depth. This session will not only discuss the technical details of the new features, but also the use cases for this technology, by examining how Polybase can help you:
• Streamline your ETL process by using Hadoop as the staging area of the backroom
• Export to your Hadoop environment your Enterprise Data Warehouse conformed dimensions
• Use Hadoop as a low cost, online data archive
• Enrich your relational data with ambient data resident in Hadoop