Data Modeling and Schema Design Flashcards
6 cards from real Data Engineering practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 Data Modeling and Schema Design flashcards as text
Which normal form requires that every non-key attribute is fully functionally dependent on the entire primary key, not just part of it?
Answer: Second Normal Form (2NF)
2NF eliminates partial dependencies, requiring every non-key attribute to depend on the whole composite primary key.
A fact table with very few numeric measures that primarily stores the occurrence of an event is called a:
Answer: Factless fact table
A factless fact table records events or coverage relationships without any numeric measures, only keys to dimension tables.
What is the purpose of a 'junk dimension' in dimensional modeling?
Answer: To combine multiple low-cardinality flags and indicators into a single dimension
A junk dimension consolidates miscellaneous low-cardinality flags and indicator fields into one dimension to reduce fact table width.
In the Kimball methodology, what is the 'Bus Matrix' used for?
Answer: Mapping which business processes share which conformed dimensions
The Enterprise Bus Matrix maps each business process (fact table) against the dimensions it shares, ensuring conformed dimensions across the data warehouse.
Which schema type is most appropriate when querying across multiple star schemas that share common dimensions?
Answer: Galaxy schema (fact constellation)
A galaxy schema (fact constellation) consists of multiple fact tables sharing conformed dimension tables, enabling cross-subject-area queries.
What is 'grain' in the context of a fact table?
Answer: The level of detail represented by each row in the fact table
Grain defines exactly what one row in a fact table represents, and declaring the grain is the most critical step in dimensional design.