Oracle Database 11g Data Warehousing Fundamentals Cources

Oracle Database 11g: Data Warehousing Training

This Database 11G Data Warehousing training teaches data warehousing concepts and technologies, while examining Oracle’s approach to data warehouse implementation. Review partitioning, parallel operations, materialized views and more.

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Course Curriculum

Oracle Database 11g: Data Warehousing

SELF PACED

This Database 11G Data Warehousing training teaches data warehousing concepts and technologies, while examining Oracle’s approach to data warehouse implementation. Review partitioning, parallel operations, materialized views and more.

  • WEEK 5-6
  • 10 Modules
  • 6 Hours
Course Content


Topics:
  • The sh and dm Sample Schemas and Appendices Used in the Course.
  • Class Account Information.
  • Course Schedule.
  • Course Objectives.
  • SQL Environments and Data Warehousing Tools Used in this Course.
  • Oracle 11g Data Warehousing and SQL Documentation and Oracle By Examples.
  • Course Pre-requisites and Suggested Pre-requisites.
  • Continuing Your Education: Recommended Follow-Up Classes.


Topics:
  • Data Warehouse Definition and Properties.
  • Extraction, Transformation and Loading (ETL).
  • Warehouse Development Approaches.
  • The Dimensional Model and Oracle OLAP.
  • Data Warehouses, Business Intelligence, Data Marts and OLTP.
  • Oracle Data Mining.
  • Typical Data Warehouse Components.


Topics:
  • Data Warehouse Definition and Properties.
  • Data Warehouses Versus Data Marts.
  • Strategy Phase Deliverables.
  • Typical Data Warehouse Components.
  • Warehouse Development Approaches.
  • Introducing the Case Study: Roy Independent School District (RISD).
  • Data Warehousing Process Components.
  • Data Warehouse Versus OLTP.


Topics:
  • Defining the Business Model.
  • Fact and Dimension Tables Characteristics.
  • Translating Business Dimensions into Dimension Tables.
  • Translating Dimensional Model to Physical Model.
  • Defining the Physical Model: Star, Snowflake and Third Normal Form.
  • Defining the Logical Model.
  • Defining the Dimensional Model.
  • Data Warehouse Modeling Issues.


Topics:
  • Indexing.
  • Oracle’s Strategy for Data Warehouse Security.
  • Security in Data Warehouses.
  • Optimizing Star Queries: Tuning Star Queries.
  • Database Sizing and Estimating and Validating the Database Size.
  • Oracle Database Architectural Advantages.
  • Parallelism.
  • Data Partitioning.


Topics:
  • Extraction Techniques and Maintaining Extraction Metadata.
  • Possible ETL Failures and Maintaining ETL Quality.
  • Extraction, Transformation and Loading (ETL) Process.
  • Extracting Data and Examining Data Sources.
  • Mapping Data.
  • Logical and Physical Extraction Methods.
  • Oracle’s ETL Tools: Oracle Warehouse Builder, SQL*Loader and Data Pump.
  • ETL: Tasks, Importance and Cost.


Topics:
  • Remote and Onsite Staging Models.
  • Transformation.
  • Maintaining Transformation Metadata.
  • Quality Data: Importance and Benefits.
  • Data Anomalies.
  • Transformation Routines.
  • Transformation Techniques and Tools.
  • Transforming Data: Problems and Solutions.


Topics:
  • Data Granularity.
  • Loading Data into the Warehouse.
  • Transportation Using Flat Files, Distributed Systems and Transportable Tablespaces.
  • Loading Techniques Provided by Oracle.
  • Indexing and Sorting Data and Verifying Data Integrity.
  • Data Refresh Models: Extract Processing Environment.
  • Building the Loading Process.
  • Post Processing of Loaded Data.


Topics:
  • Time- and Date-Stamping, Database Triggers and Database Logs.
  • Developing a Refresh Strategy for Capturing Changed Data.
  • Planning and Scheduling the Load Window.
  • Final Tasks.
  • Capturing Changed Data for Refresh.
  • User Requirements and Assistance.
  • Load Window Requirements
  • Applying the Changes to Data.


Topics:
  • Using Summaries to Improve Performance.
  • Working With Dimensions and Hierarchies.
  • Types of Materialized Views.
  • Build Modes and Refresh Modes.
  • Using Materialized Views for Summary Management.
  • Query Rewrite: Overview.
  • Cost-Based Query Rewrite Process.


Topics:
  • Integrating Multiple Sets of Metadata.
  • Managing Changes to Metadata.
  • Defining Warehouse Metadata.
  • Defining Warehouse Metadata.
  • Identifying Target Metadata Users and Choosing Metadata Tools and Techniques.
  • Metadata Users and Types.
  • Extraction, Transformation and Loading Metadata.
  • Examining Metadata: ETL Metadata.
  • Defining Metadata Goals and Intended Usage.


Topics:
  • Project Management.
  • Data Warehouse Architecture.
  • Some Useful Resources and White Papers.
  • ETL, Reporting and Security Considerations.
  • Logical, Dimensional and Physical Data Models.
  • Testing the Implementation and Post Implementation Change Management.
  • Metadata Management.
  • Requirements Specification or Definition.

Program Syllabus

Curriculum

You can also view the program syllabus by downloading this program Curriculum.

Course Description

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Instructor-led Sessions

30 Hours of Online Live Instructor-Led Classes.
Weekend Class : 10 sessions of 3 hours each.

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Real-life Case Studies

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