MCQ Collection
Data Warehousing and Business Intelligence MCQs
Practice Data Warehousing and Business Intelligence questions with answers and explanations.
Choose an option to check your answer.
A.
Create a new fact table for each flag
B.
Combine them into a junk dimension
C.
Store them only in report filters
D.
Remove the flags from the warehouse
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Correct Answer: B. Combine them into a junk dimension
Explanation:
A junk dimension groups miscellaneous small categorical attributes.
It avoids cluttering the fact table with many separate indicator columns.
Choose an option to check your answer.
A.
The number of columns in a dimension table
B.
The time required to design a dashboard layout
C.
The delay between a source event and its availability for analysis
D.
The distance between two data centers
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Correct Answer: C. The delay between a source event and its availability for analysis
Explanation:
Latency measures how current analytical data is relative to source events.
Refresh schedules and integration methods determine this delay.
Choose an option to check your answer.
A.
The full history of sales transactions
B.
A table of customer lifetime values
C.
A controlled list of country and currency codes
D.
A cube containing profit measures
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Correct Answer: C. A controlled list of country and currency codes
Explanation:
Reference data provides stable code sets used to classify other data.
Country, currency, and status codes are typical examples.
Choose an option to check your answer.
A.
A transaction log record
B.
A source-system input form
C.
An OLAP structure or warehouse aggregate
D.
A network routing table
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Correct Answer: C. An OLAP structure or warehouse aggregate
Explanation:
Aggregates accelerate repeated analytical queries over common groupings.
They are analytical structures rather than operational transaction records.
Choose an option to check your answer.
A.
Executive policies for approving budgets
B.
A replacement for every operational application
C.
Processes that extract, cleanse, transform, and load warehouse data
D.
Manual procedures for entering fact rows
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Correct Answer: C. Processes that extract, cleanse, transform, and load warehouse data
Explanation:
ETL implements the movement and transformation of data from sources to targets.
It operationalizes mappings and data quality rules defined during design.
Choose an option to check your answer.
A.
Render interactive charts for executives
B.
Define dashboard narratives
C.
Store warehouse data and support data acquisition from sources
D.
Manage user presentation themes
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Correct Answer: C. Store warehouse data and support data acquisition from sources
Explanation:
The bottom tier contains databases, staging areas, and integration mechanisms.
It provides the persistent analytical data foundation.
Choose an option to check your answer.
A.
All joins between facts and dimensions are eliminated
B.
Every query returns only one row
C.
Data can be managed and queried in smaller, independent segments
D.
The warehouse no longer needs backups
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Correct Answer: C. Data can be managed and queried in smaller, independent segments
Explanation:
Date partitions support targeted loads, retention, maintenance, and pruning.
They make very large tables easier to operate and scale.
Choose an option to check your answer.
A.
Fact constellation removal
B.
Vertical partitioning
C.
Role-playing dimension
D.
Bridge elimination
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Correct Answer: C. Role-playing dimension
Explanation:
One physical dimension can serve several logical roles in a business process.
Each foreign key expresses a different date context for the same fact row.
Choose an option to check your answer.
A.
The visual size of a dashboard chart
B.
The number of database users
C.
The encryption strength of a backup
D.
The level of detail represented by each fact row
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Correct Answer: D. The level of detail represented by each fact row
Explanation:
Granularity states exactly what one row in a fact table represents.
A finer grain stores more detailed events than a summarized grain.
Choose an option to check your answer.
A.
Every query returns the same number regardless of filters
B.
Revenue no longer needs a time dimension
C.
Source systems can stop recording sales
D.
Users interpret and compare the measure consistently
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Correct Answer: D. Users interpret and compare the measure consistently
Explanation:
Conformed definitions apply the same business logic wherever the measure appears.
This improves comparability and reduces disputes between reports.
Choose an option to check your answer.
A.
Warehouse tables have no dependencies
B.
Schema changes affect only chart colors
C.
Operational users automatically rewrite ETL code
D.
Historical loads, ETL mappings, semantic models, and reports can all depend on the schema
Show Answer
Correct Answer: D. Historical loads, ETL mappings, semantic models, and reports can all depend on the schema
Explanation:
A warehouse sits within a chain from sources to reports.
Changing structures can break mappings, calculations, cubes, and downstream content.
Choose an option to check your answer.
A.
Confirm that every chart uses the same font
B.
Check that users can edit fact rows directly
C.
Verify that all tables have identical row counts
D.
Reconcile warehouse measures with controlled source totals
Show Answer
Correct Answer: D. Reconcile warehouse measures with controlled source totals
Explanation:
Reconciliation compares target results with expected source-based controls.
It detects missing, duplicated, or incorrectly transformed records.