![]() ![]() If you look closely, you notice that all Dimension tables are related to the Fact with a Relationship, except for the Date table. The Dimensions provide context so you can, among other things, analyze: The Fact table contains numerical information about sales transactions, such as Sales Amount and Product Standard Cost. The surrounding tables are called Dimension tables, which are related to the Fact table with relationships. This model is a typical star schema that you might see from data warehouses: It resembles a star. Your data model should look like the following image, with each table in a box. Let’s inspect the data model and make some changes. The data you loaded is almost ready for reporting. To make any changes to the detected data type, on the Home tab, select Data Type, then select the appropriate data type from the list.īack on the Home tab, select Close & Apply. On the Transform tab, select Detect Data Type. To let Power BI detect data types for you, select a query, then select one or more columns. Make sure not to select the sheets (labeled _data).Ĭheck that the data types of the columns match the data types in the following table. Select all tables, and choose Transform Data. In this tutorial, we're going to transform the data before loading. ![]() The Navigator provides a preview of your data so you can verify that you have the correct range of data. In the Navigator pane, you have the option to transform or load the data. Navigate to where you saved the sample workbook, and select Open. In the Data section of the Home ribbon, select Excel. If you're planning to publish your report to the Power BI service and you aren't signed up yet, sign up for a free trial.ĭownload the AdventureWorks Sales sample Excel workbook.Before you start, you need to download Power BI Desktop.Publish your report to the Power BI service so you can share it with your colleagues.Build a report with a title, three visuals, and a slicer.Prepare your data with a few transformations. ![]()
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