![]() Imagine you want to enrich the Account table with data from the ServiceCalls.įirst you would need to aggregate the data from the ServiceCalls to calculate the number of support calls that were done for each account in the last year. You also have ServiceCalls raw data from the Service Center, with data from the support calls that were performed from the different account in each day of the year. What kind of transformations can be performed with computed tables? Any transformation that you usually specify by using the transformation user interface in Power BI, or the M editor, are all supported when performing in-storage computation.Ĭonsider the following example: you have an Account table that contains the raw data for all the customers from your Dynamics 365 subscription. Instead the query is performed on the data that resides in the dataflow storage. That means that the query won't run against the external data source from which the data was imported, like the data pulled from the SQL database. The icon changes, and shows the computed icon, as shown in the following image.Īny transformation you perform on this newly created table is run on the data that already resides in Power BI dataflow storage. Right-click on the table to display this context menu.īy selecting Enable load, you create a new table for which its source is the referenced table. In the context menu, choose Reference.įor the table to be eligible as a computed table, the Enable load selection must be checked, as shown in the following image. In the dataflow authoring tool in the Power BI service, select Edit tables, then right-click on the table you want to use as the basis for your computed table and on which you want to perform calculations. How to create computed tablesĪfter you have a dataflow with a list of tables, you can perform calculations on those tables. Or if you want to edit or transform the table, you can create a reference or duplicate of the table. You can create a new query from a merge operation. There are two ways to convert a linked table into a computed table. The result is a new table, which is part of the dataflow. Create a dataflow by using a computed tableĬreating a dataflow by using a computed table allows you to reference a linked table and perform operations on top of it in a write-only fashion. Linked tables are available only with Power BI Premium. ![]() If you need to perform a merge between two tables. Doing so allows every subsequent consumer to use that table, reducing the load to the underlying data source. If you want to avoid creating multiple refreshes to a data source, it's better to use linked tables to store the data and act as a cache. If you want to reuse a table across multiple dataflows, such as a date table or a static lookup table, you should create a table once and then reference it across the other dataflows. The following list describes some of the reasons you might choose this approach: Create a dataflow by using linked tablesĬreating a dataflow by using linked tables enables you to reference an existing table, defined in another dataflow, in a read-only fashion. The reconnection keeps the data in your dataflow refreshed at the frequency that you select later in the setup process.Īfter you select the data for use in the table, you can use dataflow editor to shape or transform that data into the format necessary for use in your dataflow. When you choose data and a source, Power BI reconnects to the data source. Once connected, you can select which data to use for your table. When you select a data source, you're prompted to provide the connection settings, including the account to use when connecting to the data source, as shown in the following image. Using the Define new tables option lets you define a new table and connect to a new data source. Create a dataflow by using define new tables ![]() Dataflows can be created by users in a Premium workspace, users with a Pro license, and users with a Premium Per User (PPU) license. ![]()
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