Special Event: Cloudera Sessions (This is a full day event)

Phoenix, AZ Cloudera Sessions: Kickstart Your Data Journey

http://go.cloudera.com/Sessions_2015_Phoenix_reg

October 8th, 2015

Join us at Cloudera Sessions on Thursday, October 8th as like-minded data innovators from around Phoenix come together for a comprehensive day of exploring the different stages of the data journey.

Whether you are trying to increase operational efficiencies, discover and automate analytics, or transform your industry through unique data applications, we will walk you through our first hand experience of helping organizations build a modern architecture in order to make analytics pervasive across their organization.

9:00 AM Keynote: Pervasive Analytics
Amr Awadallah, CTO, Cloudera (http://www.cloudera.com/content/cloudera/en/about/management.html?elqaid=654&elqat=2&elqTrackId=daf4f10222064b81bd82998a3c061119)

10:30 AM Break

11:00 AM Customer Presentations

12:00 PM Lunch provided by Cloudera

1:00 PM Breakout Sessions

Hadoop and the Operational Data Store
As disparate data volumes continue to be operationalized across the enterprise, data will need to be processed, cleansed, transformed, and made available to end users at greater speeds. Traditional ODS systems run into issues when trying to process large data volumes causing operations to be backed up, data to be archived, and ETL/ ELT processes to fail. Join this breakout to learn how to battle these issues.

Data Discovery with Hadoop
Siloed data is difficult to access and causes data consumers to only have partial views of the problem at hand. By limiting access to large volumes of disparate data, analysts and business users alike don’t have the ability to include important data in their reports and models leading to suboptimal analytic outputs. Even when this data is available to countless users, traditional systems limit them to querying small volumes of data in order to return the results in a timely matter.

Operational Analytics on Hadoop
Operationalizing models and responding to large volumes of data, fast, requires bolt on systems that can struggle with processing (transforming the data), consistency (always responding to data), and scalability (processing and responding to large volumes of data). If the data volume become too large, these traditional systems fail to deliver their responses resulting in significant losses to organizations. Join this breakout to learn how to overcome the roadblocks.

3:00 PM

Happy Hour!