Practice Library
All MCQs
Browse exam-wise, subject-wise, and country-wise MCQs with explanations.
Choose an option to check your answer.
A.
A degenerate dimension
B.
A conformed dimension
C.
A junk dimension
D.
An outrigger dimension
Show Answer
Correct Answer: A. A degenerate dimension
Explanation:
A degenerate dimension is a business identifier retained directly in the fact table.
It has analytical value but no additional attributes requiring a dimension table.
Choose an option to check your answer.
A.
Sales quantity
B.
Discount amount
C.
Shipping cost
D.
Gross margin percentage
Show Answer
Correct Answer: D. Gross margin percentage
Explanation:
Percentages and ratios must usually be recalculated from their components.
Summing row-level percentages produces a misleading result.
Choose an option to check your answer.
A.
Units sold per transaction
B.
Transaction revenue
C.
Daily account balance
D.
Number of returned items
Show Answer
Correct Answer: C. Daily account balance
Explanation:
Balances can be summed across accounts but usually not across time snapshots.
They require a specific time rule such as ending balance or average balance.
Choose an option to check your answer.
A.
Account balance measured at month end
B.
Sales amount recorded for each transaction line
C.
Profit margin percentage
D.
Average selling price
Show Answer
Correct Answer: B. Sales amount recorded for each transaction line
Explanation:
Transaction sales amounts can be summed across all relevant dimensions.
Balances and ratios have restrictions that make them semi-additive or nonadditive.
Choose an option to check your answer.
A.
The grain of the fact table
B.
The index fill factor
C.
The dashboard refresh color
D.
The transaction isolation level
Show Answer
Correct Answer: A. The grain of the fact table
Explanation:
Grain declares the exact meaning and level of detail of each fact row.
Every dimension key and measure must be consistent with that declaration.
Choose an option to check your answer.
A.
Store only transaction amounts
B.
Record database lock activity
C.
Hold temporary ETL error messages
D.
Provide descriptive context used to filter, group, and label facts
Show Answer
Correct Answer: D. Provide descriptive context used to filter, group, and label facts
Explanation:
Dimensions describe the who, what, where, when, and how of facts.
Their attributes make analytical results understandable to business users.
Choose an option to check your answer.
A.
Only textual descriptions of customers
B.
Database user passwords
C.
Business measurements and foreign keys at a declared grain
D.
ETL package source code
Show Answer
Correct Answer: C. Business measurements and foreign keys at a declared grain
Explanation:
Fact tables record measurable business events or states.
Dimension keys provide the context needed to analyze those measures.
Choose an option to check your answer.
A.
Guarantee that every analytical conclusion is correct
B.
Minimize service interruption when components fail
C.
Eliminate the need for data-quality rules
D.
Make all users database administrators
Show Answer
Correct Answer: B. Minimize service interruption when components fail
Explanation:
High availability uses redundancy and failover to reduce downtime.
It addresses service continuity rather than analytical validity.
Choose an option to check your answer.
A.
Distribute processing or storage across additional servers
B.
Install more memory in the existing server
C.
Replace the existing CPU with a faster one
D.
Increase the disk capacity of the same machine
Show Answer
Correct Answer: A. Distribute processing or storage across additional servers
Explanation:
Scaling out adds nodes and distributes workload across them.
Scaling up increases resources within a single server.
Choose an option to check your answer.
A.
Store all data only in spreadsheets
B.
Use OLTP tables for both transactions and dashboards without separation
C.
Keep dimensions in memory but delete facts
D.
Store aggregates multidimensionally while retaining detail in relational storage
Show Answer
Correct Answer: D. Store aggregates multidimensionally while retaining detail in relational storage
Explanation:
HOLAP combines MOLAP speed for summaries with ROLAP scalability for detail.
Queries may use multidimensional aggregates and relational drill-through data.
Choose an option to check your answer.
A.
Every query is sent directly to an OLTP source
B.
No data is preprocessed for analysis
C.
Data and aggregations are stored in specialized multidimensional structures
D.
Measures are stored only in dashboard images
Show Answer
Correct Answer: C. Data and aggregations are stored in specialized multidimensional structures
Explanation:
MOLAP processes data into optimized multidimensional storage.
This often provides fast query performance at the cost of processing and storage overhead.
Choose an option to check your answer.
A.
Only inside client browser memory
B.
In relational database tables queried by the OLAP layer
C.
Only in flat-file backups
D.
Inside operational application forms
Show Answer
Correct Answer: B. In relational database tables queried by the OLAP layer
Explanation:
ROLAP leaves data in relational structures and generates SQL for analysis.
It can scale to large volumes but depends strongly on relational query performance.