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Dimensional Modeling 3
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Dimensional Modeling 3
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Lecture 3_ Kimball Lifecycle and Dimensional Modelling_DWM.pptx_removed.pdf Flashcards
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Question
What is the main focus of the star schema design in dimensional modeling?
Answer
The star schema design centers around the SalesFact table which is connected to several dimension tables including the CustomerDimension.
Question
What are the dimension tables in the star schema?
Answer
The dimension tables in the star schema include CustomerDimension, ProductDimension, DateDimension, and StoreDimension.
Question
What is the key characteristic of the snowflake schema?
Answer
The snowflake schema is a more normalized version of the star schema where dimension tables are structured in multiple related tables forming a structure that resembles a snowflake.
Question
What is one advantage of using the snowflake schema?
Answer
The snowflake schema reduces data redundancy.
Question
What is one disadvantage of using the snowflake schema?
Answer
The snowflake schema can complicate querying because it involves more joins.
Question
What is the new dimension table added in the snowflake schema?
Answer
The new dimension table is LocationDimension, which contains City, State, and Country from CustomerDimension.
Question
What does CustomerDimension now contain in the snowflake schema?
Answer
CustomerDimension now contains CustomerID (PK), CustomerName, Email, PhoneNumber, DateOfBirth, Gender, JoinDate, and LocationID (FK to LocationDimension).
Question
What is a common hierarchy that can be defined within the DateDimension?
Answer
A common hierarchy within the DateDimension allows for analysis at different time levels such as Year, Quarter, Month, and Day.
Question
What is the primary fact table in both star and snowflake schemas?
Answer
The primary fact table in both star and snowflake schemas is SalesFact.
