The best primary key for the LendingClub rejected loan dataset would likely be the Loan Application Number. This is because:

1. Uniqueness: Each loan application should have a unique number, which is crucial for a primary key.
2. Stability: The loan application number should not change over time.
3. Not Null: Every loan application should have an application number, so there will be no null values.
4. Minimal: It is a single attribute, making it a minimal key.

The other options are not as suitable:

a. Loan Number: This may not exist for rejected loans as no loan was issued.
c. Zip Code: This would not be unique as multiple applicants could apply from the same zip code.
d. Customer Number: This could potentially work if each customer only applies once, but if a customer applies more than once, the customer number would not be unique.

Question

The best primary key for the LendingClub rejected loan dataset would likely be the Loan Application Number. This is because:

1. Uniqueness: Each loan application should have a unique number, which is crucial for a primary key.
2. Stability: The loan application number should not change over time.
3. Not Null: Every loan application should have an application number, so there will be no null values.
4. Minimal: It is a single attribute, making it a minimal key.

The other options are not as suitable:

a. Loan Number: This may not exist for rejected loans as no loan was issued.
c. Zip Code: This would not be unique as multiple applicants could apply from the same zip code.
d. Customer Number: This could potentially work if each customer only applies once, but if a customer applies more than once, the customer number would not be unique.

Knowee AI · Accepted Answer

The best primary key for the LendingClub rejected loan dataset would likely be the Loan Application Number. This is because:

1. Uniqueness: Each loan application should have a unique number, which is crucial for a primary key.
2. Stability: The loan application number should not change over time.
3. Not Null: Every loan application should have an application number, so there will be no null values.
4. Minimal: It is a single attribute, making it a minimal key.

The other options are not as suitable:

a. Loan Number: This may not exist for rejected loans as no loan was issued.
c. Zip Code: This would not be unique as multiple applicants could apply from the same zip code.
d. Customer Number: This could potentially work if each customer only applies once, but if a customer applies more than once, the customer number would not be unique.

What would be the best primary key for the LendingClub rejected loan dataset?Question 1Answera.Loan numberb.Loan application numberc.Zip coded.Customer number

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What would be the best primary key for the LendingClub rejected loan dataset?

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