Understanding Data Blending

Data blending is when you blend data from multiple data sources on a single worksheet. The data is joined on common dimensions. Data Blending does not create row level joins and is not a way to add new dimensions or rows to your data. Refer to Joining Tables to learn how to create those types of joins. Instead, data blending should be used when you have related data in multiple data sources that you want to analyze together in a single view. For example, you may have Sales data collected in an Oracle database and Sales Goal data in an Excel spreadsheet. To compare actual sales to target sales, you can blend the data based on common dimensions to get access to the Sales Goal measure.
To integrate data, you must first add one of the common dimensions from the primary data source to the view. For example, when blending Actual and Target sales data, the two data sources may have a Date field in common. The Date field must be used on the sheet. Then when you switch to the secondary data source in the Data window, Tableau automatically links fields that have the same name. If they don’t have the same name, you can define a custom relationship that creates the correct mapping between fields.
For each data source that is used on the sheet, a query is sent to the database and the results are processed. Then all the results are left joined on the common dimensions. The join is done on the member aliases of the common dimensions so if the underlying values aren’t an exact match, you can fix it up in Tableau.
In general, a good test to see whether data can be integrated smoothly is to drag the dimensions from the primary data source into a text table on one sheet. Then on another sheet, drag the same fields from the secondary data source into a text table. If the two tables match up then the data is most likely going to blend correctly.

1 comment:

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