Big Data for the Enterprise- Part 1

Large companies see an opportunity to replace expensive legacy data warehouse applications with Big Data technologies. But how realistic is the notion of switching from tried and true data warehouse implementations to something that's still maturing, and what are the pitfalls? What will a business user need to learn in order to adapt to the new platform?

Mark Kidwell of DesignMind (http://www.designmind.com/) will share experiences of companies like Intel and Intuit, who have seized on the Big Data opportunity, and what they encountered along the way.

Nate Philip of Qubole (http://www.qubole.com/) will take us inside the world of analytics at Pinterest, where a third of employees use Big Data.

You’ll learn:

· How SQL-on-Hadoop lets users bring their standard client tools to Big Data

· What the challenges are when migrating from traditional relational databases

· How achieving self-service is a more realistic goal than ever

· How to overcome the integration obstacles for analysts and IT users of Big Data

· How Pinterest users interact with their data, which tools they use, and how they got to this level

Mark Kidwell is VP, Big Data at DesignMind. He specializes in Hadoop and related technologies, Data Warehousing, and Technical and Project Leadership. Before joining DesignMind, Mark spent two years at Western Union Digital Ventures where he transformed Western Union data processing capabilities with the introduction of a new Cloudera Hadoop-based Big Data processing platform for risk and customer analytics uses cases.

Nate Philip joined Qubole in January 2015 to lead Product Marketing. Prior to Qubole, he helped drive the acceleration and adoption of a wide variety of data-generating technologies from sensor networks to mobile devices. In an advocacy role at the Software & Information Industry Association, he worked to enhance and drive the Federal Cloud Computing Initiative.

About the Hosts:

DesignMind is a San Francisco-based technology consulting firm specializing in data architecture and analysis. Our expertise is in business intelligence, big data, data science, collaboration platforms, and mobile applications. We leverage state-of-the-art technologies, including Hadoop, Qubole, MapR, SQL Server, SharePoint, and .NET, to develop database, data warehousing solutions, and custom applications that are both powerful and cost-effective.

Qubole simplifies the provisioning, management and scaling of big data analytics workloads leveraging data stored on Amazon Web Services, Google Compute, or Microsoft Azure infrastructure. With Qubole connected to your choice of cloud provider, once IT sets policies, any number of data analysts can be set free to collaboratively “click to query” with the power of Hive, Spark, Presto and many others in a growing list of data processing engines. Our platform, Qubole Data Service (QDS), delivers these best-in-class Apache tools integrated into an enterprise-feature rich platform optimized to run in the cloud at petabyte+ scale.