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Date: January 23, 2019 Time: 10:00am PT/1:00pm ET

Recent developments in data management—self-service, big data, data lakes, NoSQL, Hadoop, and the cloud—raise questions about the role of the data warehouse in the age of analytics. Legacy data warehouses must be modernized if they are to fit gracefully into modern analytics ecosystems. Despite declarations to the contrary, the data warehouse is not dead.

Recent surveys show that more than 60% of companies are operating between two and five data warehouses, and fewer than 10% have only one data warehouse or none at all. It is clear that data warehousing is needed. People continue to need well-integrated, systematically cleansed, easy-to-access data that includes time-variant history. But data warehousing must evolve and adapt to fit with the realities of modern data management and to overcome the challenges of scalability and elasticity, data variety, data latency, and adaptability.

Join us to learn about the challenges of legacy data warehousing, the goals of modern data warehousing, and the design patterns and frameworks that help to accelerate modernization efforts. You will learn:

  • The big challenges of legacy data warehousing

  • Architectural frameworks to position data warehousing as an integral component of a modern analytics ecosystem

  • How big data and unstructured data influence the future of data warehousing and modern analytics infrastructure

  • How high-velocity data and data streams influence the future of data warehousing and modern analytics infrastructure

  • Advantages of cloud data warehousing and cloud-optimized architecture for warehouse modernization

  • Tips for getting started with data warehouse modernization


Director, Data Management Practice

David Wells


Dave Wells is an advisory consultant, educator, and industry analyst dedicated to building meaningful connections throughout the path from data to business value. He works at the intersection of information management and business management, driving business impact through analytics, business intelligence, and active data management. More than forty years of information systems experience combined with over ten years of business management give him a unique perspective about the connections among business, information, data, and technology. Knowledge sharing and skills building are Dave’s passions, carried out through consulting, speaking, teaching, and writing.

Director of Product Management

Eva Nahari


Eva is a product management director on Cloudera’s Data Warehouse team, with a focus on discovery data warehouse use cases and end-user experience. Eva brings broad and deep insight into cross-industry data strategies and customer success based on her many years of experience in modern data warehousing and as the chair of Cloudera Executive Advisory Board. Before Cloudera, she spent 15+ years in infrastructure software. Eva has an M.Sc. in computer science, with focus on AI, machine learning, and autonomous systems, she has been awarded multiple technical patents throughout her career.


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