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Oracle Database: Implement Partitioning

Este curso tem como objetivo compreender e aprender a usar as diferentes formas de particionamento de tabelas e índices da BD.

Duração

2 dias / 12 horas

Modalidade

Presencial e Live Training

Sobre a formação

Este curso tem como objetivo compreender e aprender a usar as diferentes formas de particionamento de tabelas e índices da BD.

A quem se destina

  • Application Developers
  • Architect
  • Database Administrators
  • System Administrator
  • System Analysts
  • System Integrator
  • Technical Administrator

Programa do curso

This Oracle Database: Implement Partitioning training teaches you how to manage partitioning using Oracle Database. Expert Oracle University instructors will demonstrate the benefits of partitioning for different types of workloads and learn the syntax for partitioning maintenance operations. In this course, you will be introduced to Oracle Database Cloud Service.

Learn To:

  • Apply partitioning strategies to enhance application performance.
  • Use partitioning techniques to reduce impact of table and index maintenance.
  • Use partitioning to decrease the time to refresh materialized views.
  • Partition lob segments, nested tables and object tables.
  • Understand the Oracle Partitioning methods for tables, index and materialized views available in Oracle Database.
  • Gain an understanding of the Oracle Database Cloud Service.

Benefits to You

Taking this course will introduce you to several new partitioning enhancements, including partition maintenance operations on multiple partitions, heat maps, partial indexes for partitioned tables, interval-reference partitioning and online move partition capabilities. When the new enhancements are added to all the existing methods of partitioning, this large range of choices and capabilities requires that database administrators and data architects understand each partitioning method and it's appropriate uses. Proper use of partitioning can greatly benefit many types of applications including data warehouses, information life cycle management and very large databases.

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