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A well designed data model is the cornerstone to building business intelligence and data warehouse applications that provide significant business value.
Effective data modeling results in transforming data into an enterprise information asset that is consistent, comprehensive and current. Data is transformed from operational or source systems into a data warehouse and often data marts or OLAP cubes for analysis. This course provides the fundamental techniques to designing the data warehouse, data marts or cubes that enable business intelligence reporting and analytics.
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This online training course discusses the two logical data modeling approaches of Entity-Relationship (ER) and dimensional modeling. ER modeling is used to establish the baseline data model while dimensional modeling is the cornerstone to Business Intelligence (BI) and Data Warehousing (DW) applications. These modeling techniques have expanded and matured as best practices have emerged from years of experience in data modeling in enterprises of all sizes and industries. These techniques improve the business value of the data, enhance project productivity and reduce the time to develop applications
This course includes a mix of concepts, applications and practical examples.
You will learn:
- the basics of Entity-Relationship (ER) and dimensional modeling
- the benefits and applicability of Dimensional Data Modeling
- how to create Dimensional Data Models for BI and DW applications
- how to learn more about Data Modeling
This course is geared towards:
- Beginning Data Modelers
- Business Analysts and Architects
- Database Administrators and Analysts
- Information Technology Managers, Project Managers
- Application Development Project Team Members
- People involved in design and maintenance of Data Warehousing and Business Intelligence applications
- People involved in data quality or data governance processes
DM-04 Data Warehousing and Business Intelligence Data Modeling
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DM-04-00 About the Course (6 min)
DM-04-01 Introduction to Data Modeling (75 min)
- Data Modeling Overview
- Entity-Relationship Modeling Overview
- Normalization
DM-04-02 Dimensional Modeling Basics (88 min)
- What is Dimensional Modeling?
- Facts
- Dimensions
- Schemas
- Entity-Relationship vs. Dimenstional Modeling
- Purpose of Dimensional Modeling
- Fact Tables
- Dimensional Modeling Vocabulary
DM-04-03 Advanced Dimensional Modeling (84 min)
- Hierarchies
- Slowly Changing Dimensions
- Rapidly Changing Dimensions
- Casual Dimensions
- Multi-Valued Dimensions
- Snowflaking
- Junk Dimensions
- Value Brand Reporting
- Heterogeneous Products
- Hot Swappable Dimensions
- Too Few or Too Many Dimensions
- Benefits of Dimensional Modeling
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Click –here- to download a more detailed outline of this course.
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This exam tests knowledge and understanding of the data modeling techniques used in design of Data Warehousing and Business Intelligence applications.
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You will be tested in these areas:
- The basics of Entity-Relationship (ER) and dimensional modeling
- Purpose and benefits of dimensional modeling
- Basic concepts and terminology of dimensional modeling
- Understanding facts and dimensions
- Understanding dimensional schemas
- Understanding hierarchies
- Various advanced topics in dimensional modeling, including slowly-changing and rapidly-changing dimensions, casual dimensions, multi-valued dimensions, junk dimensions, etc.
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Additional Information
Number of Questions: 25
Time Limit: 50 Minutes
Passing Score: 70%
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Once you pass the exam, you will receive a Certificate of Education documenting that you have demonstrated mastery of the topic. Further, the exam counts towards Certified Information Management Professional (CIMP) designation in the Metadata Management track.
We recommend that you take detailed notes and review the course material multiple times before taking this exam. Click here to learn more about CIMP exams.
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Course Review 
Course Review 