The data that you simply analyze in Tableau is usually made from a set of tables that are related by specific fields (that is, columns). Joining may be a method for combining data on supported those common fields. The results of combining data employing a join may be a virtual table that’s typically extended horizontally by adding columns of knowledge .
In general, there are four sorts of joins that you simply can use in Tableau: inner, left, right, and full outer. The tables you’ll join and therefore the different join types you’ll use depend upon the database or file you hook up with . you’ll tell which join types your data supports by checking the join dialog after you’ve connected to your data and have a minimum of two tables on the canvas.

If you are not sure what join type you would like to use to mix data from multiple tables, you ought to use relationships.
Combine tables from an equivalent database
If the tables you would like to research are from an equivalent database, or workbook (for Excel), or directory (for text) then use the subsequent procedure to mix tables. Combining tables that are from an equivalent database require only one connection within the data source. Typically, joining tables from an equivalent database yields better performance. this is often because querying data that’s stored on an equivalent database takes less time and leverages the native capabilities of the database to perform the join.
About null values in join keys
In general, joins are performed at the database level. If the fields wont to join tables contain null values, most databases return data without the rows that contain the null values. However, if you’ve found out your single-connection data source to use an Excel, text, or Salesforce connection, Tableau provides a further choice to allow you to hitch fields that contain null values with other fields that contain null values.

To join on null values

After you’ve found out your data source, on the info source page, select Data > Join null values to null values.
Combine tables from different databases
Beginning with Tableau version 10.0, if the tables you would like to research are stored in several databases, or workbooks (for Excel), or directories (for text), use the subsequent procedure to mix tables employing a cross-database join.

Cross-database joins require that you simply first found out a multi-connection data source—that is, you create a replacement connection to every database before you join tables. once you hook up with multiple databases, a knowledge source becomes a multi-connection data source. Multi-connection data sources are often advantageous once you got to analyze data for a corporation that uses different internal systems or once you got to work with data that’s managed separately by both internal and external groups.
Improve performance for cross-database joins
Beginning with Tableau Desktop and Tableau Server version 2019.3, you’ll improve performance when joining data from one file connection and one database connection by allowing Tableau to perform the join using the database that you simply are connected to rather than Hyper. When this feature is enabled, Tableau chooses the fastest option (Hyper or the connected database). If Tableau uses the connected database, the info from the file connection is moved into temporary tables within the database and therefore the join is performed there.
In Tableau Desktop: you’ll use a selected calculation if it’s both:

Supported by all the connections within the multi-connection data source

Supported by Tableau extracts.

In web authoring (Tableau Online and Tableau Server): you’ll use a selected calculation if it’s supported by all the connections within the multi-connection data source.

Stored procedures
Stored procedures aren’t available for multi-connection data sources.

Pivot data from within a connection
To pivot data, you want to use text columns or Excel columns from an equivalent connection. That is, you can’t include columns from different databases during a pivot.

Make extract files the primary connection (Tableau Desktop only)
When connecting to extract files during a multi-connection data source, confirm that the connection to the extract (.tde or .hyper) file is that the first connection. This preserves any customizations which may be a neighborhood of the extract, including changes to default properties, calculated fields, groups, aliases, etc.
Extracts of multi-connection data sources that contain connections to file-based data (Tableau Desktop only)
If you’re publishing an extract of a multi-connection data source that contains a connection to file-based data like Excel, selecting the Include external files option puts a replica of the file-based data on the server as a part of the info source. during this case, a replica of your file-based data are often downloaded and its contents accessed by other users. If there’s sensitive information within the file-based data that you simply have intentionally excluded from your extract, don’t select Include external files once you publish the info source.
About queries and cross-database joins
For each connection, Tableau sends independent queries to the databases within the join. The results are stored during a temporary table, within the format of an extract file.

For example, suppose you create connections to 2 tables, dbo.listings and reviews$. These tables are stored in two different databases, SQL Server and Excel. Tableau queries the database in each connection independently. The database performs the query and applies customizations like filters and calculations, and Tableau stores the results for every connection during a temporary table. during this example, FQ_Temp_1 is that the temporary table for the connection to SQL Server and FQ_Temp_2 is that the temporary table for the connection to Excel.