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Show Table of Contents. Combine tables from the same database. About null values in join keys. Combine tables from different databases. About working with multi-connection data sources. About queries and cross-database joins. Review join results in the data grid. Use calculations to resolve mismatches between fields in a join. The data that you analyze in Tableau is often made up of a collection of tables that are combining joining merging by specific fields that combining joining merging, columns.

Joining is a method for combining the related data on those common fields. Combining joining merging result of combining data using combining joining merging join is a virtual table that is typically extended horizontally combining joining merging adding columns of data. For example, suppose you are analyzing data for a publisher. The publisher might have two tables.

The first table contains Combining joining merging numbers, first name, last name, and publisher type. The second table contains ID numbers, price, royalty, and title of published books. The related field between the two tables might be ID. In order to analyze these two tables together, you can join combining joining merging tables on ID to answer questions like, "How much was paid in royalties for authors from a given publisher? By combining tables using a join, you can view and use related data from different tables in your analysis.

In general, there are four types of joins that you can use to combine your data in Tableau: The combining joining merging you combining joining merging join and the different join types you can use depend on the combining joining merging or file you connect to.

You can tell which join types your data supports by checking the join dialog after you've connected to your data and have at least two tables on the canvas. When you use an inner join to combine tables, the result is a table that contains values that have matches in both tables.

When you use a left join to combine tables, the result is a table that contains all values from the left table and combining joining merging matches from the right table. When a value in the left table doesn't have a corresponding match in the right table, you see combining joining merging null value in the data grid.

When you use a right join to combine tables, the result is a table that contains all values from the right table and corresponding matches from the left table. When a value in the right table doesn't have a corresponding match in the left table, you see a null value in the data combining joining merging. When you use a full outer join to combine tables, the result is a table that contains all values from both tables.

When a combining joining merging from either table doesn't have a match with the other table, you see a null value in the data grid. If the combining joining merging you need to analyze are from the same database, or workbook for Excelor directory for text then use the following procedure to combine tables.

Combining tables that are from the same database require only a single connection in the data source. Typically, joining tables from the same database yields better performance. This is because querying data that is stored on the same database takes less time and leverages the native capabilities of the database to combining joining merging the join. Depending on the level of detail of the tables you want to combine, you might consider data blending instead.

For more information, see Blend Your Data. On the start page, under Connectclick a connector to connect to your data. This step creates the first connection in the Tableau data source. If you're signed in to Tableau Server from Tableau Desktop while you are setting up the data source, you have access to recommended tables to help make combining joining merging your data easier. Add one or more join conditions by selecting a field from one of the available tables used in the data source, a join operator, and a field from the added table.

Inspect the join condition to make sure it reflects how you want to connect the tables. For example, in a data source that has a table of order information and another for returns information, you could use an inner join to combine the two tables based on the Order ID field that exists in both tables.

You combining joining merging delete an unwanted join condition by clicking the red "x" that displays when you hover over the right side of the condition. After you've created a join, review the data grid to make sure that the join produces the results that you expect. For more information, see Review join results in the data grid.

Continue to prepare your data source for analysis. You can rename and reset fields, create calculations, clean your data with Data Interpreter, change the data types of fields, and so on.

In general, joins are performed at the database level. If the combining joining merging used to join tables contain null values, most databases return data without the rows that contain the null values. However, if you've set up your single-connection data source to use an Excel, text, or Salesforce connection, Tableau provides an additional option to allow you to join fields that combining joining merging null values with other fields that contain null values.

For example, suppose you have two tables of data that you want to join: This option is available for single-connection data sources that use text, Excel, and Salesforce connections. If you add a second connection to a data source that uses this option, the combining joining merging reverts back to the default behavior of excluding rows with null values.

Beginning with Tableau version Cross-database joins require that you first set up a multi-connection data source—that is, you create a new connection to each database before you join tables. When you connect to combining joining merging databases, a data source becomes a multi-connection data source. Multi-connection data sources can be advantageous when you need to analyze data for an organization that uses different internal systems or when you need to work with data that is managed separately by both internal and external groups.

Combining joining merging many cases, using a cross-database join is the combining joining merging method for combining your data. However, there are some cases that you might need to combine your data using data blending instead. After you've combined tables using a cross-database join, Tableau colors the tables in the canvas and the columns combining joining merging the data grid to show you which connection the data comes from.

On the Start page, under Connectclick a connector to connect to your data. In the left pane, under Connectionsclick the Add button to add a new connection to the Tableau data source. A new connection is required if you have related data stored in another database. If the connector you want is not available from the Connect list, cross-database joins combining joining merging not supported for the combination of sources that you want to join.

This includes connections to cube data e. Instead of joining tables, consider using data blending. For example, in a data source that has a table of order information and another table of returns information, combining joining merging could join the two tables based on the Order ID field that exists in both tables. Select the type of join. You can delete an unwanted join condition by combining joining merging the red "x" that displays when you hover over the combining joining merging of the condition.

After you've created a cross-database join, continue to prepare your multi-connection data source for analysis. Working with multi-connection data sources is just like working with any other data source, with a few caveats, discussed in this section.

When connecting to extract files in a multi-connection data source, make sure that the connection to the extract. This preserves any customizations that might be a part of the extract, including changes to default properties, calculated fields, groups, aliases, etc.

If you need to connect to multiple extract files in your multi-connection data source, only the customizations in the extract in the first connection are preserved. Extracts of multi-connection data sources that contain connections to file-based data. If you're publishing an extract of a multi-connection data source that contains a connection to file-based data combining joining merging as Excel, selecting the Include external files option puts a copy of the file-based data on the server as part of the data source.

In this case, a copy combining joining merging your file-based data can be downloaded and its contents accessed by other users. If there is sensitive information in the file-based data that you have intentionally excluded from your extract, do not select Include external files when you publish the data source.

For more information about publishing data sources, see Publish a Data Source. Only a subset of calculations can be used in a multi-connection data source.

You can use a specific calculation if it is both:. To pivot data, you must use text columns or Excel columns from the same connection. That is, you cannot include columns from different databases in a pivot.

To combining joining merging data, you must use text tables or Excel tables from the same connection. That is, you cannot union tables from different databases. However, you can union tables across different Excel workbooks and files in different folders.

For more information, see the Union tables using wildcard search. Collation refers to the rules of a database that determine how string values should be compared and sorted.

In most cases, the collation is handled by the database. However, combining joining merging you work with cross-database joins, you might join columns that have different collations. For example, suppose your cross-database join used a join key comprised of a case-sensitive column from SQL Server and a case-insensitive column from Oracle.

In cases like this, Tableau maps certain collations to others to minimize interpreting values incorrectly. Collation of Japanese characters, that is, Kana-sensitivity, depends on the database that you are connected to. For each connection, Tableau Desktop sends independent queries to the databases in the join. Combining joining merging results are stored in a temporary table, in the format of an extract file.

For example, suppose you create connections to two tables, dbo. Tableau queries the database in each connection independently. When you perform a cross-database join, the temporary tables are joined together by Tableau Desktop. These temporary combining joining merging are necessary for Tableau to perform cross-database joins.

After the tables have been joined, "topn" filter is applied to limit the number of values shown in the data grid to the first 1, rows. This filter is applied to help maintain responsiveness of the data grid and the overall performance of the Data Source page.

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