Microsoft PL-300 Bundle

A specified placeholder can preserve row meaning for optional text values. This solves “and approved business rules require a placeholder label”; the stated issue is “but some analysts replace all zeros as missing”.

Quarantine or reject rows lacking mandatory relationship keys. The deciding difference is “and cannot be safely joined to a customer” versus “but some analysts replace all zeros as missing”.

Replacing unknown revenue with zero can distort aggregate metrics. Its application is “must remain distinguishable from true zero sales”, not the need “but some analysts replace all zeros as missing”.

Changing type before cleaning malformed source values creates conversion errors. It serves “values such as 'unknown', producing Power Query errors”, not “ZIP codes as whole numbers, stripping leading zeros”.

Arithmetic requires values stored as numbers, not formatted strings. The present requirement is “ZIP codes as whole numbers, stripping leading zeros”; “dollar sign and commas as text, blocking SUM” is a distinct situation.

Treating a UTC instant as an unzoned local datetime can shift reporting periods. That matters for “as UTC but executives expect regional local time” rather than the condition “ZIP codes as whole numbers, stripping leading zeros”.

Changing type before cleaning malformed source values creates conversion errors. The boundary it addresses is “values such as 'unknown', producing Power Query errors”, while this case concerns “text, but the workbook uses an English-US locale”.

Postal codes are identifiers, not quantities; leading zeros are meaningful. This solves “ZIP codes as whole numbers, stripping leading zeros”; the stated issue is “text, but the workbook uses an English-US locale”.

Arithmetic requires values stored as numbers, not formatted strings. The deciding difference is “dollar sign and commas as text, blocking SUM” versus “text, but the workbook uses an English-US locale”.

Changing type before cleaning malformed source values creates conversion errors. The deciding difference is “values such as 'unknown', producing Power Query errors” versus “dollar sign and commas as text, blocking SUM”.

Postal codes are identifiers, not quantities; leading zeros are meaningful. Its application is “ZIP codes as whole numbers, stripping leading zeros”, not the need “dollar sign and commas as text, blocking SUM”.

Locale-aware parsing avoids silently swapping day and month. That is a different operating condition from “dollar sign and commas as text, blocking SUM”: “text, but the workbook uses an English-US locale”.

Locale-aware parsing avoids silently swapping day and month. It serves “text, but the workbook uses an English-US locale”, not “values such as 'unknown', producing Power Query errors”.

Postal codes are identifiers, not quantities; leading zeros are meaningful. That matters for “ZIP codes as whole numbers, stripping leading zeros” rather than the condition “values such as 'unknown', producing Power Query errors”.

Arithmetic requires values stored as numbers, not formatted strings. The boundary it addresses is “dollar sign and commas as text, blocking SUM”, while this case concerns “values such as 'unknown', producing Power Query errors”.

Changing type before cleaning malformed source values creates conversion errors. The boundary it addresses is “values such as 'unknown', producing Power Query errors”, while this case concerns “as UTC but executives expect regional local time”.

Locale-aware parsing avoids silently swapping day and month. The deciding difference is “text, but the workbook uses an English-US locale” versus “as UTC but executives expect regional local time”.

Arithmetic requires values stored as numbers, not formatted strings. Its application is “dollar sign and commas as text, blocking SUM”, not the need “as UTC but executives expect regional local time”.

Repeated invoice numbers do not imply duplicate transaction lines. That is a different operating condition from “rows and must be one row per key”: “and a developer deletes duplicates on invoice number”.

Removing exact duplicate records repairs a confirmed replication problem. It serves “append, and the owner confirms they are erroneous”, not “rows and must be one row per key”.

Profile the lookup's key cardinality and repair or remodel its duplicates. The present requirement is “rows and must be one row per key”; “loading because a supposed customer lookup repeats keys” is a distinct situation.

Test CustomerID uniqueness before defining the one-side relationship. The present requirement is “and a developer deletes duplicates on invoice number”; “rows and must be one row per key” is a distinct situation.

Removing exact duplicate records repairs a confirmed replication problem. The boundary it addresses is “append, and the owner confirms they are erroneous”, while this case concerns “and a developer deletes duplicates on invoice number”.

Profile the lookup's key cardinality and repair or remodel its duplicates. This solves “loading because a supposed customer lookup repeats keys”; the stated issue is “and a developer deletes duplicates on invoice number”.

Repeated invoice numbers do not imply duplicate transaction lines. The deciding difference is “and a developer deletes duplicates on invoice number” versus “append, and the owner confirms they are erroneous”.

Profile the lookup's key cardinality and repair or remodel its duplicates. Its application is “loading because a supposed customer lookup repeats keys”, not the need “append, and the owner confirms they are erroneous”.

Latest-version selection needs a stable tie-break rather than arbitrary duplicate removal. That is a different operating condition from “append, and the owner confirms they are erroneous”: “versions for each customer with a LastUpdated timestamp”.

Repeated invoice numbers do not imply duplicate transaction lines. That is a different operating condition from “versions for each customer with a LastUpdated timestamp”: “and a developer deletes duplicates on invoice number”.

Profile the lookup's key cardinality and repair or remodel its duplicates. It serves “loading because a supposed customer lookup repeats keys”, not “versions for each customer with a LastUpdated timestamp”.

Removing exact duplicate records repairs a confirmed replication problem. That matters for “append, and the owner confirms they are erroneous” rather than the condition “versions for each customer with a LastUpdated timestamp”.

Repeated invoice numbers do not imply duplicate transaction lines. The boundary it addresses is “and a developer deletes duplicates on invoice number”, while this case concerns “loading because a supposed customer lookup repeats keys”.

Test CustomerID uniqueness before defining the one-side relationship. This solves “rows and must be one row per key”; the stated issue is “loading because a supposed customer lookup repeats keys”.

Latest-version selection needs a stable tie-break rather than arbitrary duplicate removal. The deciding difference is “versions for each customer with a LastUpdated timestamp” versus “loading because a supposed customer lookup repeats keys”.