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Hadoop has changed the economics of data and forced CIO's to rethink their data architecture. What does this mean for the relation DBMS-based data warehouse? Can Hadoop really replace finely-tuned database queries for 1000's of users in organizations? Well, that depends. As Apache Hadoop and relational database technology evolve, enterprises are taking a hybrid approach that brings together the best of both worlds into one. This session will look across multiple design patterns for Hadoop and data warehousing including the traditional, logical, and operational data warehouses. We will also cover the SQL-on-Hadoop landscape and how that enables these different design patters to optimize the data warehouse and overall enterprise data architecture.
KEYWORDS: System Architecture, Use Cases, Data Warehouse, SQL, Hadoop
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North America. Please refer to theMapR Talks Directory for specific countries.
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