Most databases have multiple tables of data that are related in some way. Additionally, with Tableau 10 and later, you are able to join together tables of data across various data connections for many different data sources. As we'll see, Tableau makes it very easy to join together tables of data relatively easy.

Consider, for example, tables such as these:

The primary table is the Hospital Visit table, which has a record for every visit of a patient to the hospital and includes details such as admission type (examples include inpatient, outpatient, and ER). It also contains key fields that link a visit to a Primary Physician, Patient, and Discharge Details.

When you connect to the database in Tableau, you'll see the tables listed on the left and will have the option to drag and drop them into the data source designer.

If key fields and relationships have been defined in the database, Tableau will automatically create the joins as you add additional tables. Otherwise, it will attempt to match field names. In any case, you may adjust the joins as needed. The preceding tables will look similar to the following diagram when dropped into the designer:

You may adjust the join by clicking the small diagram between the tables. The diagram indicates what kind of join is used. For example, the join between Hospital Visit and Patient is an Inner Join because it is assumed that every visit will have a patient and every patient will have a visit. However, the join between Hospital Visit and Discharge Details is a left join because some records in Hospital Visit may be for patients still in the hospital (so they haven't been discharged).

Clicking on the diagram will allow you to select a different type of join and define which fields are part of the join.

You may specify the following types of joins:

• Inner: Only records that match the join condition from both the table on the left and the table on the right will be kept. In the following example, only the three matching rows are kept in the results:

• Left: All records from the table on the left will be kept. Matching records from the table on the right will have values in the resulting table, while unmatched records will contain NULL values for all fields from the table on the right. In the following example, the five rows from the left table are kept with NULL results for right values that were not matched:

• Right: All records from the table on the right will kept. Matching records from the table on the left will result in values, while unmatched records will contain NULL values for all fields from the table on the left. Not every data source supports a right join. If it is not supported, the option will be disabled. In the following example, the five rows from the right table are kept with NULL results for left values that were not matched:

• Full Outer: All records from tables on both sides will be kept. Matching records will have values from the left and the right. Unmatched records will have NULL values where either the left or the right matching record was not found. Not every data source supports a full outer join. If it is not supported, the option will be disabled. In the following example, all rows are kept from both sides with NULL values where matches were not found: