I. Overview:

Enroll for the 3-day Oracle Database 19c: Data Warehousing Techniques course from Koenig Solutions accredited by Oracle. This course teaches you the various Data Warehousing concepts and techniques related to data extraction, transformation, and loading phases.

Through a blend of hands-on labs and interactive lectures you will learn about the different changed data capture methods for data refresh, and how to define summary management and implement materialized views. You will also learn about the role of warehouse metadata along with the various data warehouse implementation considerations.

II. Duration:

03 days (24 hours)

III. Objectives:

• Describe methods and tools for extracting, transforming, and loading data.
• Describe the benefits of partitioning in a data warehouse.
• Use parallel operations to reduce response time for data-intensive operations.
• Create, use, and refresh materialized views to improve data warehouse performance.
• Explain the implementation and organizational issues surrounding a data warehouse project.

IV. Intended Audience:

• Data warehouse developers
• Data warehouse engineers
• Data warehouse analysts
• Data warehouses builders and administrators
• Data warehouse implementation team members
• Data warehouse developers

V. Prerequisites

• Basic knowledge of data warehouse concepts and related terminology.
• Relational database concepts and Oracle server concepts including application and server tuning, and the operating system environment under which you are running the Oracle Database Server.
• Good working knowledge of the SQL language.

VI. Course outlines:

Module 1: Course Overview

Module 2: Data Extraction Techniques

• Data Extraction Techniques
• Data Extraction Process

Module 3: Introduction to Data Transformation

Module 4: Data Transformation Techniques

Module 5: Data Loading Techniques

• Data Loading Techniques
• Loading Techniques Supported by Oracle

Module 6: Database Sizing, Storage, and Security Considerations

• Database Sizing, Storage, and Security Considerations
• Data Partitioning

Module 7: Data Refresh Techniques

• Data Refresh Techniques
• Applying the Changes to the Data Warehouse

Module 8: Summary Management

• Summary Management
• Refresh Modes

Module 9: Metadata Management

• Metadata Management
• Metadata Strategy and Considerations

Module 10: Data Warehouse Implementation Considerations