Partitioning Data Warehouses on Oracle Database with Tim Gorman

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Partitioning Data Warehouses on Oracle Database with Tim Gorman

Oracle University
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Description

This 2-day seminar is based on 14 years of extensive experience implementing very large multi-terabyte databases to support data warehouses on the Oracle RDBMS. One of the most important technical decisions is how to implement partitioning within the Oracle RDBMS to optimize query performance for response time even as data volumes increase, and also to optimize data loading to maximize availability during load windows, eliminating downtime and minimizing impact on the system. Partitioning is also implemented to optimize storage by enabling compression and taking advantage of tiered storage. Partitioning is the key to unlock the full power of numerous advanced Oracle features for data warehou…

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This 2-day seminar is based on 14 years of extensive experience implementing very large multi-terabyte databases to support data warehouses on the Oracle RDBMS. One of the most important technical decisions is how to implement partitioning within the Oracle RDBMS to optimize query performance for response time even as data volumes increase, and also to optimize data loading to maximize availability during load windows, eliminating downtime and minimizing impact on the system. Partitioning is also implemented to optimize storage by enabling compression and taking advantage of tiered storage. Partitioning is the key to unlock the full power of numerous advanced Oracle features for data warehousing in a way that is not explicitly documented by Oracle. This interlocked dependency between features is described by Mr Gorman as the "virtuous cycle". Not starting with partitioning on a data warehouse project can lead to a deadly embrace of unfortunate circumstances that can doom the project to almost inevitable failure, which Mr Gorman characterizes as the "death spiral". In fact, one of the most important query optimizations for data warehouses in Oracle known as "star transformations" is effectively not available without using properly using database partitioning.
Audience
  • Data Warehouse Administrator
  • Data Warehouse Analyst
  • Data Warehouse Developer

Course Topics Data warehousing "utopia" Logical data model design Physical Database design Data load Optimization Query Optimization
Course Objectives
  • Optimization of data loading
  • Optimization of queries
  • Optimization of storage

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