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Creating and using DataFlows in Power BI

Creation of Dataflows in power BI

Dataflows in power bi are reusing power query logic among different pbix files.Dataflow is a collection of entities that are created and managed in power bi service. You can add and edit entities in your dataflow and manage data refresh schedules directly from workspace.

Why we need in power bi:

  Power bi introduces data flow to help organizations unify data from disparate sources and prepare it for modelling.

  Dataflows are used to ingest, transform and integrate by defining data source connections, ETL logic and refresh schedules.  Data is stored as entities in common data model in azure data lake storage GEN2 and these were created and managed in workspaces by using power bi service.

Steps to create dataflows in Power BI

1. At first we need to create one workspace for the dataflow in power bi.

2. After creation of workspace, we will create a data flow in power bi service.

3. We can select any one option to build data flow.Here I selected option called add new entities.

4. We can select any file as data source to add entity in already existing dataflow or for creation of new entity in data flow.

5. Here I selected data source as Blank Query.We need to create a script for the formation of dataset.

6. After creation of query, it will transform to edit queries to change or rename the data and then click on save the data flow.

7. Once created a data flow, we need to connect from power bi. By clicking on get data source -> power bi dataflows.In that we need to select blank query for the creation of data flow in power bi.

8. After creation of data set from data flow to the existing pbix. File.
This is one of the process for the creation of data flow in power bi.

Usage of dataflow in power bi.

1. Dataflow is a power query process that runs in the cloud independently from any power bi reports.2. Re-usable tables or queries across multiple power bi files, are one of the best candidates for dataflow.3. Dataflow can run ETL process on a different schedule for every query (table).

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