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Oracle Database: Administer a Data Warehouse

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Lerninhalte:

  • Partitionierung
  • Parallele Abfrage zu Reduzierung der Antwortzeit
  • Daten extrahieren, transformieren und laden
  • Materialized Views für bessere Data Warehouse Performance anlegen und aktualisieren
  • Query Rewrite verwenden
  • Benutzen des SQL Access Advisor und von PL/SQL Prozeduren für schnelles Aktualisieren von Materialized Views und Query Rewrite


Teilnehmerkreis:

  • Technischer Data Warehouse Berater
  • Data Warehouse Entwickler
  • Data Warehouse Administrator


Erforderliche Vorkenntnisse:

  • Lesen und Verstehen von Ausführungsplänen
  • Gutes Grundlagenwissen über SQL und über Data Warehouse Design bzw. Implementierung

 

Kursziele:

  • Use parallel operations to reduce response time for data-intensive operations
  • Extract, Transform and Load data in the data warehouse
  • Create, use and refresh materialized views to improve the data warehouse performance
  • Use Query rewrite to quickly answer business queries using materialized views
  • Use SQL Access Advisor and PL/SQL procedures to tune materialized views for fast refresh and query rewrite
  • Use the features of compression and resumable sessions
  • Review the basic Oracle data warehousing concepts


Kursthemen:

Introduction
Development Tools
Oracle SQL Developer
Enterprise Manager
Sample Schemas used

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

Data Warehouse Tuning Considerations
Optimizing Star Queries
Introducing Bitmap Join Indexes
Understanding Star Query Optimization and Bitmap Joined Index Optimization

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

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

Parallel Operations in Data Warehouses
Parallel Query
Parallel DDL
Parallel DML
Tuning Parameters for Parallel Execution
Balancing the Workload

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

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

ETL: Transformation
Data transformation
Transformation Mechanisms
Transformation Using SQL
Table Functions
DML error logging

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

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

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

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

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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