Oracle Database 11g: Administer a Data Warehouse Training

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Oracle Database 11g: Administer a Data Warehouse training explains how to extract, transform and load data into an Oracle database warehouse. The training explains the basic concepts of administering the database, increasing the manageability, and improving the performance of the data warehouse. The expert professional will explain and provide you hands-on session on the optimized way of using the SQL Access Advisor for managing the entire workload.

By the end of the Oracle Database 11g: Administer a Data Warehouse training, you will be proficient in the following skills:

  • Learn data warehouse architectures, design, objects, and schemas
  • Implement partitioning and parallel operations to reduce response time for data-intensive operations
  • Extract, Transform, and Load data in the data warehouse
  • Work with Dimensions, hierarchies,and privileges
  • Create, use, and refresh materialized views to improve the data warehouse performance
  • Use SQL Access Advisor and PL/SQL procedures to tune materialized views for fast refresh and query rewrite that ultimately results in increasing the response time for answering business queries
Target audience
  • Application Developers
  • Data Warehouse Developer
  • Data Warehouse Administrator
  • Database Administrators
  • Support Engineer
  • Technical Consultant
Prerequisites

The candidates with working knowledge of SQL and experience in Data Warehouse design, implementation, and maintenance can get the best out of thistraining.

Oracle Database 11g: Administer a Data Warehouse training explains how to extract, transform and load data into an Oracle database warehouse. The training explains the basic concepts of administering the database, increasing the manageability, and improving the performance of the data warehouse. The expert professional will explain and provide you hands-on session on the optimized way of using the SQL Access Advisor for managing the entire workload.

By the end of the Oracle Database 11g: Administer a Data Warehouse training, you will be proficient in the following skills:

  • Learn data warehouse architectures, design, objects, and schemas
  • Implement partitioning and parallel operations to reduce response time for data-intensive operations
  • Extract, Transform, and Load data in the data warehouse
  • Work with Dimensions, hierarchies,and privileges
  • Create, use, and refresh materialized views to improve the data warehouse performance
  • Use SQL Access Advisor and PL/SQL procedures to tune materialized views for fast refresh and query rewrite that ultimately results in increasing the response time for answering business queries
Target audience
  • Application Developers
  • Data Warehouse Developer
  • Data Warehouse Administrator
  • Database Administrators
  • Support Engineer
  • Technical Consultant
Prerequisites

The candidates with working knowledge of SQL and experience in Data Warehouse design, implementation, and maintenance can get the best out of thistraining.

Oracle Database 11g: Administer a Data Warehouse Training Course Content

1. Introduction

  • Development Tools
  • Oracle SQL Developer
  • Enterprise Manager
  • Sample Schemas used

2. Data Warehouse Design: Overview

  • Characteristics of a Data Warehouse
  • Comparing OLTP and Data Warehouses
  • Data Warehouse Architectures
  • Data Warehouse Design
  • Data Warehouse objects
  • Data Warehouse Schemas

3. Data Warehouse Tuning Considerations

  • Optimizing Star Queries
  • Introducing Bitmap Join Indexes
  • Understanding Star Query Optimization and Bitmap Joined Index Optimization

4. Partitioning Basics

  • Partitioned Tables and Indexes
  • Partitioning Methods
  • Partitioning Types
  • Partition Pruning and Star queries

5. Parallelism Concepts

  • Operations That Can Be Parallelized
  • How Parallel Execution Works
  • Degree of Parallelism
  • Parallel execution plan
  • Automatice Parallelism

6. Parallel Operations in Data Warehouses

  • Parallel Query
  • Parallel DDL
  • Parallel DML
  • Tuning Parameters for Parallel Execution
  • Balancing the Workload

7. ETL: Extraction and Transportation

  • Extraction Methods
  • Capturing Data With Change Data Capture
  • Sources and Modes of Change Data Capture
  • Publish and Subscribe Model: The Publisher and the Subscriber
  • Synchronous and Asynchronous CDC
  • Asynchronous AutoLog Mode and Asynchronous HotLog Mode
  • Transportation in a Data Warehouse
  • Transportable Tablespaces

8. ETL: Loading

  • Loading Mechanisms
  • Applications of External Tables
  • Defining external tables with SQL*Loader
  • Populating external tables with Data Pump
  • Other Loading Methods

9. ETL: Transformation

  • Data transformation
  • Transformation Mechanisms
  • Transformation Using SQL
  • Table Functions
  • DML error logging

10. Materialized Views

  • The Need for Summary Management
  • Types of Materialized Views
  • Using Materialized Views for Summary Management
  • Materialized View Dictionary views

11. Refreshing Materialized Views

  • Refresh Options
  • Refresh Modes
  • Conditions That Effect Possibility of Fast Refresh
  • Materialized View Logs
  • Partition Change Tracking (PCT) Refresh
  • Refresh Performance Improvements

12. Working With Dimensions

  • What Are Dimensions
  • Creating Dimensions and Hierarchies
  • Dimensions and Privileges
  • Dimension Restrictions
  • Verifying Relationships in a Dimension
  • Dimension Invalidation

13. Query Rewrite

  • Query Rewrite: Overview
  • What Can be Rewritten
  • Conditions Required for Oracle to Rewrite a Query
  • Query Rewrite guidelines
  • Setting Initialization Parameters for Query Rewrite
  • Query Rewrite Methods
  • Partition Change Tracking (PCT) and Query Rewrite
  • Query Rewrite Enhancement to Support Queries Containing Inline Views

14. Using the SQL Access Advisor, Compression, and Resumable Sessions

  • SQL Access Advisor: Usage Model
  • Setting Initial Options
  • Specifying the Workload Source
  • Recommendation Options
  • Schedule and Review
  • PL/SQL Procedure Flow
  • Tuning Materialized Views for Fast Refresh and Query Rewrite
  • Table Compression and Resumable Sessions

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