Oracle DWH 10g Data Warehousing Fundamentals

Day 1

• Lesson 1 : Data Warehousing and Business Intelligence
• Lesson 2 : Defining Data Warehouse Concepts and Terminology
• Lesson 3 : Business, Logical, and Dimensional Modeling
• Lesson 4 : Physical Modeling: Sizing, Storage, Performance,
  and Security Considerations 5

Day 2

• Lesson 5 : The ETL Process: Extracting Data
• Lesson 6 : The ETL Process: Transforming Data
• Lesson 7 : The ETL Process: Loading Data
• Lesson 8 : Refreshing Warehouse Data

Day 3

• Lesson 9 : Summary Management
• Lesson 10 :Leaving a Metadata Trail
• Lesson 11 :OLAP and Data Mining
• Lesson 12 :Data Warehouse Implementation Considerations
• Lesson 13 :Workshop

Lesson 1 : Data Warehousing and Business Intelligence

• Describe the role of data warehousing and business intelligence (BI) in today’s marketplace
• Define the terminology and explain the basic concepts of data warehousing
• Define the decision support purpose and end goal of a data warehouse
• Develop familiarity with the various technologies required to implement a data warehouse
• Identify the technology and tools from Oracle to implement a successful data warehouse
• Identify data warehouse modeling concepts
• Describe methods and tools for extracting, transforming, and loading data
• Identify the tools for accessing and analyzing warehouse data
• Identify the features of Oracle Database 10g that aid in implementing the data warehouse
• Describe the OLAP and data mining techniques and tools
• Explain the implementation and organizational issues surrounding a data warehouse project

Lesson 2 : Defining Data Warehouse Concepts and Terminology

• Identify a common, broadly accepted definition of a data warehouse
• Describe the differences of dependent and independent data marts
• Identify some of the main warehouse development approaches
• Define some of the operational properties and common terminology of a data warehouse

Lesson 3 : Business, Logical, and Dimensional Modeling

• Discuss data warehouse environment data structures
• Discuss data warehouse database design phases:
• Defining the business model
• Defining the logical model
• Defining the dimensional model

Lesson 4 : Physical Modeling: Sizing, Storage, Performance, and Security Considerations

• Describe how to translate the dimensional model to physical model
• Explain data warehouse sizing techniques and test load sampling
• Describe data warehouse partitioning methods
• Describe indexing types and strategies
• Explain parallelism in data warehouse operations
• Explain the importance of security in data warehouses
• Identify the tools and technologies provided by Oracle

Lesson 5 : The ETL Process: Extracting Data

• Outline the extraction, transformation, and loading (ETL) processes for building a data warehouse
• Identify the ETL tasks, importance, and cost
• Explain how to examine data sources
• Identify extraction techniques and methods
• Identify analysis issues and design options for extraction processes
• List the selection criteria for the ETL tools
• Identify Oracle’s solution for the ETL process

Lesson 6 : The ETL Process: Transforming Data

• Define transformation
• Identify possible staging models
• Identify data anomalies and eliminate them
• Explain the importance of quality data
• Describe techniques for transforming data
• Design transformation process
• List Oracle’s enhanced features and tools that can be used to transform data

Lesson 7 : The ETL Process: Loading Data

• Explain key concepts in loading warehouse data
• Outline how to build the loading process for the initial load
• Identify loading techniques
• Describe the loading techniques provided by Oracle
• Identify the tasks that take place after data is loaded
• Explain the issues involved in designing the transportation, loading, and scheduling processes

Lesson 8 : Refreshing Warehouse Data

• Describe methods for capturing changed data
• Explain techniques for applying the changes
• Describe refresh mechanisms supported in Oracle Database 10g
• Describe techniques for purging and archiving data and outline the techniques supported by Oracle
• Outline final tasks, such as publishing the data and automating processes

Lesson 9 : Summary Management

• Discuss summary management and Oracle implementation of summaries
• Describe materialized views
• Identify the types, build modes, and refresh methods for materialized views
• Explain the query rewrite mechanism in Oracle
• Describe the significance of Oracle dimensions

Lesson 10 : Leaving a Metadata Trail

• Define warehouse metadata, its types, and its role in a warehouse environment
• Examine each type of warehouse metadata
• Develop a metadata strategy
• Outline the Common Warehouse Metamodel (CWM)
• Describe Oracle Warehouse Builder’s compliance with Object Management Group’s
  Common Warehouse Metamodel (OMG-CWM)

Lesson 11 : OLAP and Data Mining

• Define online analytical processing and the Oracle Database 10g OLAP option
• Compare ROLAP and MOLAP
• List the benefits of OLAP and RDBMS integration
• List the benefits of using OLAP for end users and IT
• Describe the data mining concepts
• Describe the tools and technology offered by Oracle for OLAP and data mining

Lesson 12 : Data Warehouse Implementation Considerations

• Describe the project management plan
• Specify the requirements for the implementation
• Describe the metadata repository, technical architecture, and other considerations
• Describe post implementation change management considerations