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Merge pull request MicrosoftDocs#264 from MicrosoftDocs/steindav-patch-PPandACstyle
Updates for Power Platform style
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powerquery-docs/Connectors/sap-bw/transform-filter-sap-bw-data.md

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# Transform and filter an SAP BW dataset
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With Power Query Editor, you can apply additional data transformations and filtering steps before you bring the dataset from SAP BW into the Power BI Desktop or Power Platform data model.
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With Power Query Editor, you can apply additional data transformations and filtering steps before you bring the dataset from SAP BW into the Power BI Desktop or Microsoft Power Platform data model.
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In Power Query Editor, the *Applied Steps* for the query are shown in the **Query Settings** pane on the right. To modify or review a step, select the gear icon next to a step.
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### See also
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* [Power Query M formula language reference](https://docs.microsoft.com/powerquery-m/)
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* [Implementation details](implementation-details.md)
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* [Implementation details](implementation-details.md)

powerquery-docs/dataflows/computed-entities-scenarios.md

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title: Computed entity scenarios and use cases
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description: Computed entity scenarios and use cases
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description: Computed entity scenarios and use cases.
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author: radacad
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ms.service: powerquery
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## Computed entity in other dataflows
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You can also create a computed entity in other dataflows. It can be created by getting data from a dataflow with the Power Platform dataflow connector.
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You can also create a computed entity in other dataflows. It can be created by getting data from a dataflow with the Microsoft Power Platform dataflow connector.
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:::image type="complex" source="media/getdatafromppdataflows.png" alt-text="<Get data from Power Platform dataflows>":::
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Image emphasizes the Power Platform dataflows connector from the Power Query choos data source window, with a description that states that one dataflow entity can be built on top of the data from another dataflow entity, which is already persisted in storage.

powerquery-docs/dataflows/configuring-storage-and-compute-options-for-analytical-dataflows.md

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title: Configuring storage and compute options for analytical dataflows
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description: Configuring storage and compute options for analytical dataflows
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description: Configuring storage and compute options for analytical dataflows.
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## Dataflows that use built-in storage
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By default, analytical dataflows will use the built-in Data Lake Storage; for example, when you create a dataflow in Power BI or Power Apps. Access to the output of this type of dataflow is only possible through the Power Platform dataflows connector in Power BI Desktop, or from other dataflows.
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By default, analytical dataflows will use the built-in Data Lake Storage; for example, when you create a dataflow in Power BI or Power Apps. Access to the output of this type of dataflow is only possible through the Microsoft Power Platform dataflows connector in Power BI Desktop, or from other dataflows.
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## Dataflows that use customer-provided storage
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powerquery-docs/dataflows/data-sources.md

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title: Connect to data sources for dataflows
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description: Learn how to connect to data sources for dataflows
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description: Learn how to connect to data sources for dataflows.
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author: bensack
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manager: kfile
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[!INCLUDE [CDS note](../includes/cc-data-platform-banner.md)]
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With Power Platform dataflows, you can connect to many different data sources to create new dataflows, or add new entities to an existing dataflow.
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With Microsoft Power Platform dataflows, you can connect to many different data sources to create new dataflows, or add new entities to an existing dataflow.
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This article lists many available data sources for creating or adding to dataflows, and describes how to create those dataflows by using these data sources. For an overview of how to create and use dataflows, see [Creating and using dataflows in Power BI](https://docs.microsoft.com/power-bi/service-dataflows-create-use).
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powerquery-docs/dataflows/how-to-migrate-queries-from-power-query-desktop-to-dataflows.md

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title: How to migrate queries from Power Query in the desktop (Power BI and Excel) to dataflows
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description: How to migrate queries from Power Query in the desktop (Power BI and Excel) to dataflows
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description: How to migrate queries from Power Query in the desktop (Power BI and Excel) to dataflows.
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If you already have queries in Power Query, either in Power BI Desktop or in Excel, you might want to migrate the queries into dataflows. The migration process is simple and straightforward. In this article, you'll learn the steps to do so.
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To learn how to create a dataflow in Power Platform, go to [Create and use dataflows in Power Platform](https://docs.microsoft.com/data-integration/dataflows/dataflows-integration-overview). To learn how to create a dataflow in Power BI, go to [Creating and using dataflows in Power BI](https://docs.microsoft.com/power-bi/service-dataflows-create-use).
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To learn how to create a dataflow in Microsoft Power Platform, go to [Create and use dataflows in Power Platform](https://docs.microsoft.com/data-integration/dataflows/dataflows-integration-overview). To learn how to create a dataflow in Power BI, go to [Creating and using dataflows in Power BI](https://docs.microsoft.com/power-bi/service-dataflows-create-use).
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## Migrating the queries from the desktop
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powerquery-docs/dataflows/incremental-refresh.md

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## Considerations and limitations
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Incremental refresh in Power Platform dataflows is only supported in dataflows with an Azure Data Lake Storage account, not in dataflows with Dataverse as the destination.
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Incremental refresh in Microsoft Power Platform dataflows is only supported in dataflows with an Azure Data Lake Storage account, not in dataflows with Dataverse as the destination.
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### See also
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powerquery-docs/dataflows/power-platform-dataflows-and-adf-wrangling-data-flows.md

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title: How Power Platform dataflows and Azure Data Factory wrangling dataflows relate to each other
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description: How Power Platform dataflows and Azure Data Factory wrangling dataflows relate to each other
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description: How Microsoft Power Platform dataflows and Azure Data Factory wrangling dataflows relate to each other.
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# How Power Platform dataflows and Azure Data Factory wrangling dataflows relate to each other
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# How Microsoft Power Platform dataflows and Azure Data Factory wrangling dataflows relate to each other
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[!INCLUDE [CDS note](../includes/cc-data-platform-banner.md)]
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Power Platform dataflows and Azure Data Factory dataflows are often considered to be doing the same thing: extracting data from source systems, transforming the data, and loading the transformed data into a destination. However, there are differences in these two types of dataflows, and you can have a solution implemented that works with a combination of these technologies. This article describes this relationship in more detail.
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Microsoft Power Platform dataflows and Azure Data Factory dataflows are often considered to be doing the same thing: extracting data from source systems, transforming the data, and loading the transformed data into a destination. However, there are differences in these two types of dataflows, and you can have a solution implemented that works with a combination of these technologies. This article describes this relationship in more detail.
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## Power Platform dataflows
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powerquery-docs/dataflows/relationships-in-standard-dataflows.md

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## What is the relationship and why do you need that?
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If you're coming from a database development background, you're familiar with the concept of a relationship between tables. However, many users of Power Platform services aren't coming from that background. You might wonder what the relationship is, or why you should create a relationship between tables.
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If you're coming from a database development background, you're familiar with the concept of a relationship between tables. However, many users of Microsoft Power Platform services aren't coming from that background. You might wonder what the relationship is, or why you should create a relationship between tables.
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The tables and their relationship are fundamental concepts of designing a database. To learn everything about relationships is beyond the scope of this article. However, we'll discuss it in a general way here.
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powerquery-docs/dataflows/troubleshooting-dataflow-issue-get-data-from-dataflow.md

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title: Troubleshooting dataflow issue - get data from dataflow
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description: Troubleshooting dataflow issue - get data from dataflow.
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More information: [Refreshing a dataflow in Power BI](https://docs.microsoft.com/power-bi/transform-model/dataflows/dataflows-configure-consume#refreshing-a-dataflow) and [Set the refresh frequency in Power Apps](https://docs.microsoft.com/powerapps/maker/common-data-service/create-and-use-dataflows#set-the-refresh-frequency)
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## My Power Platform dataflow isn't listed
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## My Microsoft Power Platform dataflow isn't listed
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Sometimes, you have a Power Platform dataflow you created and also refreshed, but you still can't access it through the **Get data** command. This might be because the account that's trying to access the dataflow doesn't have access. However, if the account does have access to the dataflow, another reason might be the type of dataflow you're accessing.
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Sometimes, you have a Microsoft Power Platform dataflow you created and also refreshed, but you still can't access it through the **Get data** command. This might be because the account that's trying to access the dataflow doesn't have access. However, if the account does have access to the dataflow, another reason might be the type of dataflow you're accessing.
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You might receive the error message "We reached the end of the buffer" or "DataFormat.Error: We reached the end of the buffer".
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powerquery-docs/dataflows/understanding-differences-between-analytical-standard-dataflows.md

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title: Understanding the differences between standard and analytical dataflows
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description: Understanding the differences between standard and analytical dataflows.
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## Analytical dataflows
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An analytical dataflow loads data to storage types optimized for analytics&mdash;Azure Data Lake Storage. Power Platform environments and Power BI workspaces provide customers with a managed analytical storage location that's bundled with those product licenses. In addition, customers can link their organization’s Azure Data Lake storage account as a destination for dataflows.
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An analytical dataflow loads data to storage types optimized for analytics&mdash;Azure Data Lake Storage. Microsoft Power Platform environments and Power BI workspaces provide customers with a managed analytical storage location that's bundled with those product licenses. In addition, customers can link their organization’s Azure Data Lake storage account as a destination for dataflows.
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Analytical dataflows are capable additional analytical features. For example, integration with Power BI’s AI features or use of computed entities which will be discussed later.
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