Microsoft PL-300 Bundle

A gateway is not automatically necessary for supported reachable cloud data sources. This solves “with cloud credentials and no private network restriction”; the stated issue is “data source name differs from the published model”.

The gateway securely relays cloud requests to private network data sources. Its application is “Server is inaccessible from Power BI's cloud service”, not the need “data source name differs from the published model”.

Standard mode supports shared data sources and centralized gateway management. That is a different operating condition from “data source name differs from the published model”: “centralized, shared connectivity for multiple scheduled-refresh semantic models”.

File sharing does not transfer personal data-source credentials to another account. It serves “source refuses to authenticate under the colleague's identity”, not “leaks its rows into an unrelated public query”.

Public identifies data that can be combined without private-source confidentiality assumptions. The present requirement is “leaks its rows into an unrelated public query”; “site is freely available without a confidentiality requirement” is a distinct situation.

Correct source classification and query architecture are safer than globally ignoring privacy errors. That matters for “joining sources with incompatible levels” rather than the condition “leaks its rows into an unrelated public query”.

Correct source classification and query architecture are safer than globally ignoring privacy errors. That matters for “joining sources with incompatible levels” rather than the condition “can be combined under the same organizational boundary”.

Power Query privacy levels help govern how source data can be combined. The boundary it addresses is “leaks its rows into an unrelated public query”, while this case concerns “can be combined under the same organizational boundary”.

Public identifies data that can be combined without private-source confidentiality assumptions. The deciding difference is “site is freely available without a confidentiality requirement” versus “can be combined under the same organizational boundary”.

Power Query privacy levels help govern how source data can be combined. The deciding difference is “leaks its rows into an unrelated public query” versus “site is freely available without a confidentiality requirement”.

File sharing does not transfer personal data-source credentials to another account. That is a different operating condition from “site is freely available without a confidentiality requirement”: “source refuses to authenticate under the colleague's identity”.

Correct source classification and query architecture are safer than globally ignoring privacy errors. It serves “joining sources with incompatible levels”, not “site is freely available without a confidentiality requirement”.

Power Query privacy levels help govern how source data can be combined. It serves “leaks its rows into an unrelated public query”, not “joining sources with incompatible levels”.

File sharing does not transfer personal data-source credentials to another account. That matters for “source refuses to authenticate under the colleague's identity” rather than the condition “joining sources with incompatible levels”.

Public identifies data that can be combined without private-source confidentiality assumptions. The boundary it addresses is “site is freely available without a confidentiality requirement”, while this case concerns “joining sources with incompatible levels”.

Correct source classification and query architecture are safer than globally ignoring privacy errors. The boundary it addresses is “joining sources with incompatible levels”, while this case concerns “source refuses to authenticate under the colleague's identity”.

Organizational privacy permits bounded combination within an enterprise trust boundary. This solves “can be combined under the same organizational boundary”; the stated issue is “source refuses to authenticate under the colleague's identity”.

Public identifies data that can be combined without private-source confidentiality assumptions. Its application is “site is freely available without a confidentiality requirement”, not the need “source refuses to authenticate under the colleague's identity”.

A reusable date parameter avoids hard-coded cutoffs scattered across M steps. Its application is “a rolling date cutoff used by several queries”, not the need “development and production without rewriting every Source step”.

Those names drive partition-aware time window filtering for incremental refresh. It serves “incremental-refresh configuration uses two specially named datetime boundaries”, not “development and production without rewriting every Source step”.

Slicers change visual filter context, while Power Query parameters generally shape loaded data. The present requirement is “development and production without rewriting every Source step”; “report consumption time, not a refresh-time source parameter” is a distinct situation.

Relative-path parameters support portability without changing connector origins repeatedly. The present requirement is “a rolling date cutoff used by several queries”; “file path while keeping a stable base location” is a distinct situation.

A parameter centralizes configuration that can change by environment. That matters for “development and production without rewriting every Source step” rather than the condition “a rolling date cutoff used by several queries”.

Those names drive partition-aware time window filtering for incremental refresh. The boundary it addresses is “incremental-refresh configuration uses two specially named datetime boundaries”, while this case concerns “a rolling date cutoff used by several queries”.

A parameter centralizes configuration that can change by environment. This solves “development and production without rewriting every Source step”; the stated issue is “incremental-refresh configuration uses two specially named datetime boundaries”.

A reusable date parameter avoids hard-coded cutoffs scattered across M steps. The deciding difference is “a rolling date cutoff used by several queries” versus “incremental-refresh configuration uses two specially named datetime boundaries”.

Slicers change visual filter context, while Power Query parameters generally shape loaded data. Its application is “report consumption time, not a refresh-time source parameter”, not the need “incremental-refresh configuration uses two specially named datetime boundaries”.

A parameter centralizes configuration that can change by environment. That is a different operating condition from “file path while keeping a stable base location”: “development and production without rewriting every Source step”.

A reusable date parameter avoids hard-coded cutoffs scattered across M steps. It serves “a rolling date cutoff used by several queries”, not “file path while keeping a stable base location”.

Those names drive partition-aware time window filtering for incremental refresh. The present requirement is “file path while keeping a stable base location”; “incremental-refresh configuration uses two specially named datetime boundaries” is a distinct situation.

A parameter centralizes configuration that can change by environment. That matters for “development and production without rewriting every Source step” rather than the condition “report consumption time, not a refresh-time source parameter”.

Those names drive partition-aware time window filtering for incremental refresh. The boundary it addresses is “incremental-refresh configuration uses two specially named datetime boundaries”, while this case concerns “report consumption time, not a refresh-time source parameter”.

A reusable date parameter avoids hard-coded cutoffs scattered across M steps. This solves “a rolling date cutoff used by several queries”; the stated issue is “report consumption time, not a refresh-time source parameter”.