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Dimensional Data Modeling Course Content :
Project/Program Planning
Professional Responsibilities
Professional Boundaries
An Engineer’s View
Beware the Objection Removers
What Does the Central Team Do?
Avoid DW/BI Isolation
Implementation Analysis Paralysis
Kimball Methodology
Kimball Lifecycle in a Nutshell
Think Critically When Applying Best Practices
Eight Guidelines for Low Risk Enterprise Data Warehousing
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3. Fact Table Core Concepts
Dimension Table Core
Concepts
More Dimension Patterns
and Case Studies
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Contents
4. • Professional Responsibilities
• Professional Boundaries
• An Engineer’s View
• Beware the Objection Removers
• What Does the Central Team Do?
• Avoid DW/BI Isolation
• Implementation Analysis Paralysis
• Kimball Methodology
• Kimball Lifecycle in a Nutshell
• Think Critically When Applying Best Practices
• Eight Guidelines for Low Risk Enterprise Data Warehousing
Project/Program Planning
5. • Gathering Requirements
• Business Requirements
• Requirements Gathering Dos and Don’ts
• Surprising Value of Data Profiling
• Organizing around Business Processes
• Focus on Business Processes, Not Business  Departments!
• Identifying Business Processes
• Business Process Decoder Ring
• Relationship between Strategic Business Initiatives and Business Processes
Wrapping Up the
Requirements Definition
6. • Making the Case for Dimensional Modeling
• Is ER Modeling Hazardous to DSS?
• A Dimensional Modeling Manifesto
• There Are No Guarantees
• Enterprise Data Warehouse Bus Architecture
• Divide and Conquer
• The Matrix
• The Matrix: Revisited
• Drill Down into a Detailed Bus Matrix
• Integration Instead of Centralization
• Integration for Real People
• Data Stewardship : The First Step to Quality And Âconsistency
• To Be or Not To Be Centralized
• Contrast with the Corporate Information Factory
• Differences of Opinion
• Don’t Support Business Intelligence with a Normalized EDW
Data Architecture
7. • Basics of Dimensional Modeling
• Fact Tables and Dimension Tables
• Drilling Down, Up, and Across
• Myths about Dimensional Modeling
• Dangerous Preconceptions
• Fables and Facts
Dimensional Modeling
Fundamentals
8. • Granularity
• Declaring the Grain
• Keep to the Grain in Dimensional Modeling
• Types of Fact Tables
• Fundamental Grains
• Factless Fact Tables
• Factless Fact Tables? Sound Like Jumbo Shrimp?
• What Didn’t Happen
• Parent-Child Fact Tables
• Patterns to Avoid When Modeling Header/Line
• Item Transactions
• Fact Table Keys and Degenerates
• Fact Table Surrogate Keys
• Reader Suggestions on Fact Table Surrogate Keys
• Miscellaneous Fact Table Design Patterns
• Put Your Fact Tables on a Diet
• Keeping Text Out of the Fact Table
• Dealing with Nulls in a Dimensional Model
Fact Table Core Concepts
9. • Dimension Table Keys
• Surrogate Keys
• Keep Your Keys Simple
• Date and Time Dimension Considerations
• It’s Time for Time
• Surrogate Keys for the Time Dimension
• Latest Thinking on Time Dimension Tables
• Smart Date Keys to Partition Fact Tables
• Handling All the Dates
• Miscellaneous Dimension Patterns
• Data Warehouse Role Models
• Mystery Dimensions
• De-Clutter with Junk Dimensions
• Showing the Correlation Between Dimensions
• Causal (Not Casual) Dimensions
• Are Not Always as easy as
Dimension Table Core Concepts
10. • Resist Abstract Generic Dimensions
• Hot-Swappable Dimensions
• Accurate Counting with a Dimensional Supplement
• Slowly Changing Dimensions
• Perfectly Partitioning History with Type SCD
• Many Alternate Realities
• Monster Dimensions
• When a Slowly Changing Dimension Speeds Up
• When Do Dimensions Become Dangerous?
• Slowly Changing Dimensions Are Not Always as easy as
Dimension Table Core Concepts