Question1.2 After performing a left join between a customer table and a transaction table, some transaction variables become missing. Which explanation is most appropriate? Binary variables cannot be merged Measures cannot be merged with dimensions Some customers have no matching transactions The dataset has been normalized ResetMaximum marks: 2单项选择题
A
Binary variables cannot be merged
B
Measures cannot be merged with dimensions
C
Some customers have no matching transactions
D
The dataset has been normalized

Question

Question1.2 After performing a left join between a customer table and a transaction table, some transaction variables become missing. Which explanation is most appropriate? Binary variables cannot be merged Measures cannot be merged with dimensions Some customers have no matching transactions The dataset has been normalized ResetMaximum marks: 2单项选择题

A

Binary variables cannot be merged

B

Measures cannot be merged with dimensions

C

Some customers have no matching transactions

D

The dataset has been normalized

BlackTom AI · Accepted Answer

A left join returns every row from the left (customer) table and attaches matching rows from the right (transaction) table; when no match exists, the right-side columns are NULL.

1. Relevant knowledge points and concepts
- SQL join types: LEFT JOIN keeps all left-table rows, filling non-matching right-table columns with NULLs.
- NULL indicates missing/unmatched data after a join; it does not mean the data vanished.
- Matching is determined by the join key (e.g., customer_id). If no transaction row shares that key, transaction columns will be NULL for that customer.

2. Step-by-step reasoning
- Suppose customers: {C1, C2}. Transactions: only for C1.
- Perform LEFT JOIN customers LEFT JOIN transactions ON customers.id = transactions.customer_id.
- For C1: matching transaction row found → transaction columns populated.
- For C2: no matching transaction row → transaction columns set to NULL (appear as missing).
- Therefore some transaction variables are missing because they were never present for those customers.

4. Why the correct answer is correct
- The observed missing transaction variables are the exact behavior of LEFT JOIN when some left-table rows have no corresponding right-table rows. Those transaction fields are NULL because those customers have no matching transactions.

5. Why other options are incorrect
- "Binary variables cannot be merged": false — binary fields can be joined like any other column.
- "Measures cannot be merged with dimensions": incorrect — joins can combine measures and dimensions; type mismatch is not the cause.
- "The dataset has been normalized": normalization organizes tables but does not by itself produce NULLs in joined columns; missing values after a LEFT JOIN specifically indicate no match.

6. Conclusion
This matches the provided answer: Some customers have no matching transactions.

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