Is your Big Data journey stalling? Take the Leap with Capgemini and Cloudera.
Learn how to industrialize your transition to the modern data landscape.
In the world of big data, large organizations are struggling to get value from their legacy BI systems. Transitioning to a big data architecture is a huge step, and the complexity of moving existing analytical services onto modern platforms like Cloudera can seem overwhelming.
Capgemini’s Leap Data Transformation Framework helps clients by industrializing the entire process of bringing existing BI assets and capabilities to next-generation big data management platforms.
Date: September 7, 2016
Time: 9:00am PT / 11:00am ET
Know our Experts
Big Data Practice Leader, Insights & Data, NA, Capgemini
Goutham leads the Big Data Integration practice in North America, and has over 15 years of demonstrated success at Capgemini in assisting large companies drive organizational change by leveraging information. He is known for his ability to seamlessly enhance and integrate business process enhancements with data management, predictive analytics, CRM, big data, and other technologies.
Senior Solution Architect, Insights & Data, UK, Capgemini
With more than 15 years of architectural, project, and technical leadership experience in complex big data and business information systems, Andrea provides technical leadership for complex big data solutions with large multinational organizations. He works closely with clients, colleagues, and partners to deliver innovative, reliable, and performant big data solutions.
Product Marketing Manager, Cloudera
Alex focuses on Cloudera’s core platform technologies and enterprise features. Prior to Cloudera, she managed technical marketing and PR for Basho Technologies, and managed consumer and enterprise marketing for Truaxis, a MasterCard company. She holds a BS in Marketing and BA in Psychology from Carnegie Mellon University.
In this session, you will learn:
- The key drivers for industrializing your transformation to big data at all stages of the lifecycle – estimation, design, implementation, and testing
- How one of our largest clients reduced the transition to modern data architecture by over 30%
- How an end-to-end, fact-based transformation framework can deliver IT rationalization on top of big data architectures