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23 lines
2.4 KiB
Markdown
23 lines
2.4 KiB
Markdown
In this article, we investigate some advanced data import and cleaning techniques for **Power BI Desktop**. Once you've shaped your data in **Query Editor** and brought it into **Power BI Desktop**, you can look at it in a few different ways. There are three views in Power BI Desktop: **Report** view, **Data** view, and **Relationships** view. You see each view by selecting its icon in the upper left side of the canvas. In the following image, **Report** view is selected. The yellow bar beside the icon indicates which view is active.
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To change the view, just select either of other two icons. The yellow bar beside the icon indicates which view is active.
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Power BI Desktop can combine data from multiple sources into a single report, at any time during the modelling process. To add additional sources to an existing report, select **Edit Queries** in the **Home** ribbon and then select **New Source** in **Query Editor**.
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There are many different possible data sources you can use in **Power BI Desktop**, including Folders. By connecting to a folder, you can import data from multiple files at once, such as a series of Excel files or CSV files. The files contained within your selected folder appear in **Query Editor** as binary content, and clicking the double-arrow icon at the top of the **Content** column loads their values.
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One of Power BI's most useful tools is its *Filters*. For example, selecting the drop-down arrow next to a column opens a checklist of text filters that you can use to remove values from your model.
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You can also merge and append queries, and turn multiple tables (or data from various files, in folders) into a single table that contains just the data you want. You can use the **Append Queries** tool to add the data from a new table to an existing query. Power BI Desktop attempt to match up the columns in your queries, which you can then adjust as necessary in **Query Editor**.
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Finally, the **Add Custom Column** tool gives advanced users the option of writing query expressions from scratch using the powerful M language. You can add a custom column based on M query language statements, and get your data just the way you want it.
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