Data Warehousing Fundamentals ed 2 - Seminare

Seminarziel

In this course, students study the issues involved in planning, designing, building, populating, and maintaining a successful data warehouse. Students learn the reasons why data warehousing is a compelling decision-support solution in today s business climate.

Zielgruppe

• Database Administrators
• Implementation Team
• Project Manager
• Data Warehouse Designer
• Data Warehouse Administrator

Voraussetzungen

• Familiarity with Microsoft Windows applications
• Understanding of data warehouse architecture

Inhalt

Business Intelligence and Data Warehousing
The road map to Business Intelligence
Data warehouses compared with Online Transaction Processing
Management information systems and decision support systems
Business drivers for data warehouses
Typical uses of a data warehouse

Defining Data Warehouse Concepts and Terminology
Common data warehouse definitions
Data warehouse properties and characteristics
Warehouse development approaches
Components of data warehouse design and implementation
Components of a data warehouse
Data warehouse compared with data mart
Dependent and independent data marts

Planning and Managing the Data Warehouse Project
Managing financial issues
Obtaining business commitment
Gathering business and user requirements
Evaluating the warehouse project
Implementation processes and requirements

Modeling the Data Warehouse
Data warehouse database design phases
Defining the business model
Choosing the architecture
Creating the dimensional model
Using time in the data warehouse
Using summary data
Query rewrite
Creating the physical model

Building the Warehouse - Extracting Data
Extracting, transforming, and loading data
Examining data sources
Extracting data
Extraction techniques

Building the Data Warehouse - Transforming Data
Transformation
Transforming data: problems and solutions
Resolving quality data issues
Transformation techniques
Transformation tools

Building the Data Warehouse - Loading Warehouse Data
Loading data into the warehouse
Building the loading process
Loading the data
Post-processing of loaded data
Verifying data integrity

Refreshing Warehouse Data
Capturing and applying changed data
Batch load requirements
Limitations of methods in applying change
Purging and archiving data

Leaving a Metadata Trail
Defining warehouse metadata
Developing a metadata strategy
Examining types of metadata
Metadata management tools
Common warehouse metadata

Managing the Data Warehouse
Managing the transition to production
Managing growth
Managing backup and recovery
Identifying data warehouse performance issues

Literatur

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