Question1.8 A dashboard shows duplicated total sales after creating a many-to-many relationship between tables. The most likely cause is: Incorrect visualization type Double-counting due to relationship ambiguity Missing calculated measures Insufficient data normalization ResetMaximum marks: 2单项选择题
A
Incorrect visualization type
B
Double-counting due to relationship ambiguity
C
Missing calculated measures
D
Insufficient data normalization

Question

Question1.8 A dashboard shows duplicated total sales after creating a many-to-many relationship between tables. The most likely cause is: Incorrect visualization type Double-counting due to relationship ambiguity Missing calculated measures Insufficient data normalization ResetMaximum marks: 2单项选择题

A

Incorrect visualization type

B

Double-counting due to relationship ambiguity

C

Missing calculated measures

D

Insufficient data normalization

BlackTom AI · Accepted Answer

Many-to-many relationships can create ambiguous join paths so aggregated measures like Total Sales are counted more than once, causing the duplicated totals.

1) Relevant knowledge points and concepts
- Relationship cardinality: one-to-one, one-to-many, many-to-many. Many-to-many means rows in Table A can match multiple rows in Table B and vice versa.
- Join behavior and filter propagation: joining tables duplicates rows when there are multiple matching keys.
- Aggregation semantics: SUM over duplicated rows yields inflated totals unless handled (e.g., using bridging tables, distinct aggregations, or explicit measures).

2) Step-by-step reasoning
- Suppose Sales table has one row for each transaction with SaleID and Amount.
- Another table (e.g., Promotions or ProductTags) has multiple rows that match the same SaleID or product, creating a many-to-many link.
- When the visualization engine joins these tables without a proper bridge or disambiguating relationship, the Sale row is repeated for each matching row in the other table.
- The visualization sums Amount across the joined rows, so each original sale amount is contributed multiple times.

3) Example with intermediate steps
- Sales table: Sale1 Amount = $100.
- Tags table: TagA and TagB both relate to Sale1 (two rows).
- After join: two rows both showing $100.
- SUM(Amount) after join = $100 + $100 = $200 (double-counted).
- This demonstrates how a many-to-many join inflates totals.

4) Why the correct answer is correct
- The duplicated total directly matches the behavior of double-counting caused by relationship ambiguity in many-to-many joins. The visualization is faithfully summing the duplicated rows produced by the ambiguous relationship, so the root cause is the relationship design, not the chart itself.

5) Why other options are incorrect
- Incorrect visualization type: Chart choice changes presentation but won’t create duplicate underlying aggregated totals if relationships are correct.
- Missing calculated measures: A missing measure could be a problem, but the symptom (duplicated total) is characteristic of duplicated rows from relationships rather than simply a missing metric.
- Insufficient data normalization: Poor normalization can contribute to issues, but the immediate and most likely cause for duplicated sums after creating a many-to-many relationship is double-counting from ambiguous relationships.

6) Conclusion
The correct answer is Double-counting due to relationship ambiguity, which matches the provided answer.

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