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| Data Warehousing & Data Modeling - Fundamentals |
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| Software Version |
10.0 |
| Course Duration |
2 Days |
| Course Type |
Class Room and Instructor-Led On-Line (E-Learning) Hands-On Training |
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| Course Overview |
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. This course also covers the Data Warehouse and Business Intelligence. |
| Intended Audience for this course |
This course is designed for those who have technical background, knowledge with any computer language, Java, XML, .NET Developers, ERP Developers, DBAs, Application Technical Consultants, Business Analysts, Project Managers and Students who want to become IT Professionals. |
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| Course Topics |
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| Business Intelligence and Data Warehousing |
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- The road map to Business Intelligence (BI)
- Data warehouses compared with Online Transaction Processing (OLTP)
- Management information systems and decision support systems (DSS)
- Business drivers for data warehouses
- Typical uses of a data warehouse
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| 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
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| 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
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| Modeling the Data Warehouse |
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- 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
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| Building the Warehouse - Extracting Data |
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- Extracting, transforming, and loading data
- Examining data sources
- Extracting data
- Extraction techniques
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| Building the Data Warehouse - Transforming Data |
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- Transformation
- Transforming data: problems and solutions
- Resolving quality data issues
- Transformation techniques
- Transformation tools
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| 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
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| Refreshing Warehouse Data |
- Capturing and applying changed data
- Batch load requirements
- Limitations of methods in applying change
- Purging and archiving data
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| Leaving a Metadata Trail |
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- Defining warehouse metadata
- Developing a metadata strategy
- Examining types of metadata
- Metadata management tools
- Common warehouse metadata
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| Managing the Data Warehouse |
- Managing the transition to production
- Managing growth
- Managing backup and recovery
- Identifying data warehouse performance issues
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