DA0-002 Data Analysis Practice Question
Which TWO of the following are dimensional modeling techniques commonly used in data warehouses?
⚠ Common exam trap
Candidates often confuse general data modeling concepts (like ERDs) or data visualization tools (like scatter plots and histograms) with specific dimensional modeling techniques used in data warehouses.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Snowflake schema
Snowflake schema (B) is a dimensional modeling technique in which dimension tables are normalized into multiple related tables, reducing redundancy while preserving the fact-dimension structure of a data warehouse. Star schema (C) is the classic dimensional modeling technique where a central fact table joins directly to denormalized dimension tables, optimizing query performance for analytical workloads. Both are standard approaches described by Kimball for organizing data marts and warehouses around facts and dimensions. Entity-relationship diagram (A) is a conceptual/logical modeling notation for OLTP-style normalized databases, not a dimensional technique. Scatter plot (D) and histogram (E) are data visualization or statistical analysis tools, not data warehouse modeling techniques.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Entity-relationship diagram
Why it's wrong here
Entity-relationship diagrams model operational OLTP schemas normalised to third normal form; dimensional modelling instead uses star or snowflake schemas with fact and dimension tables. It is tempting because ER diagrams are the standard design artefact for relational databases, and they would be correct when designing a transactional system rather than a warehouse.
- ✓
Snowflake schema
Why this is correct
Snowflake schema normalises dimension tables into multiple related tables, reducing redundancy and storage at the cost of more joins. It is a recognised dimensional modelling technique, alongside star schema, used to structure data warehouse dimensions.
- ✓
Star schema
Why this is correct
Star schema keeps each dimension as a single denormalised table joined directly to the central fact table, giving simple, fast queries. It is the classic dimensional modelling technique for data warehouses, contrasted with snowflake schema's normalised dimensions.
- ✗
Scatter plot
Why it's wrong here
Scatter plots are exploratory visualisation charts for spotting correlation between two numeric measures, not a dimensional modelling technique. They tempt because analysts use them during profiling, but the stem asks for warehouse schema constructs such as star schemas, snowflaking, or slowly changing dimensions.
- ✗
Histogram
Why it's wrong here
Histograms display frequency distributions of a single numeric column during exploratory data analysis, not a dimensional modelling technique. They tempt because they are common in data profiling, yet the stem requires schema design constructs like star schemas, snowflaking, or conformed dimensions.
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