OLAP fundamentals: does OLAP operate with measures and dimensions (but not “associations,” which belong to association-rule mining)?
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AInvalid statement — OLAP relies on measures and dimensions; “associations” are from data mining
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BValid statement — OLAP always uses association rules
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CValid only for market basket analysis
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DTrue exclusively in MOLAP, not ROLAP
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ETrue only when using star schemas
Answer
Correct Answer: Invalid statement — OLAP relies on measures and dimensions; “associations” are from data mining
Explanation
Introduction / Context:OLAP cubes organize numeric measures (such as sales_amount) by descriptive dimensions (such as time, product, region). “Associations” is a term used in association-rule mining (for example, market basket analysis), which is a data mining technique, not an OLAP construct.
Given Data / Assumptions:
- OLAP supports slicing, dicing, roll-up, and drill-down.
- Dimensional models include hierarchies (day → month → quarter → year).
- Association rules discover item co-occurrence patterns (e.g., {bread} ⇒ {butter}).
Concept / Approach:The statement claiming OLAP “uses measures, dimensions and associations” blends OLAP with data mining. Correct OLAP terminology is measures and dimensions; “associations” are not an OLAP element.
Step-by-Step Solution:Recall OLAP building blocks: facts/measures + dimension tables.Contrast with association-rule mining objectives and outputs.Conclude the statement is invalid because it mixes distinct concepts.
Verification / Alternative check:Check OLAP tool documentation: cube definitions specify measures and dimensions; association rules live under data mining modules.
Why Other Options Are Wrong:Referring to MOLAP/ROLAP or star schemas does not make associations an OLAP primitive; market basket analysis is outside OLAP core.
Common Pitfalls:Confusing “relationships between dimensions” with association rules; they are different.
Final Answer:Invalid statement — OLAP relies on measures and dimensions; “associations” are from data mining