#Tableau prep join for free#
#Tableau prep join how to#

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#Tableau prep join for free#

It is available for free to most people with Tableau Desktop licenses. It has just been two years since Tableau Prep joined the Tableau product family. EMEA RISING STAR TABLEAU PARTNER OF THE YEAR 2018.Tableau workshops on your data – Proof of Concept.In this case, remove the second connection and then select Data > Convert to custom SQL. The Convert to custom SQL option is available only when the data source contains only one connection. Tableau Desktop only: For most connections, you can use the Convert to custom SQL option to change the data type of one of the fields in the join key, using a function like CAST (). For more information, see Troubleshoot Joins.įor text or Excel-based data, modify the data type of one of the text or Excel fields in the join key using the data type menu in the data grid. To create a join calculation, click the join icon between the tables that have a broken join, click the field whose format needs to be modified, and then select Create Join Calculation. A join calculation supports a subset of calculations that lets you modify the format of the join key in one or more tables that you want to combine. You can change the format of a field (including its data type) in the join dialog to make the join keys match by creating a join calculation. To fix a broken join, use one of the following suggestions: If the data types of the join keys don't match, the join breaks, which is indicated by a red exclamation point and the error text 'type mismatch between join fields'.

#Tableau prep join how to#

For more information about how to connect to a custom SQL query from Tableau, see Connect to a Custom SQL Query.īroken table joins and cross-database joinsīefore you join tables (from the same data source or using a cross-database join), make sure that the data types of the join keys match. This option requires some knowledge about writing SQL queries and assistance from a database expert if possible. You can pre-aggregate the tables before joining them with a GROUP BY clause. Use custom SQL: Tableau supports using custom SQL for connecting to multiple tables in a data source.

For more information, see Removing Duplicate Data with LOD Calculations (Link opens in a new window) in the Tableau Knowledge Base. You could also use a Level of Detail Expression to delete the duplicate data. In this case, in the view replace Salary with a calculated field that uses the following formula: SUM ()/ COUNT (). For more information, see Relate Your Data.Ĭhange the aggregation: Depending on your analysis, you can use the MIN or AVG aggregation to remove over-counting.įor example, if you change the aggregation of Salary from SUM to MIN or from SUM to AVG.Ĭreate a calculated field that removes the duplicate values: You can create a calculation that divides the sum of the field being duplicated by the number of instances of the field that is causing the duplication.įor example, the Salary values are being duplicated by the number of instances of Employee ID for Wilson, Henry. Relate the data: Instead of creating a join, which might duplicate your data, you can use relationships. To help resolve this issue, you can do one of the following: For more information on cardinality between tables, see Optimize Relationship Queries Using Performance Options. This is an example of one-to-many cardinality (one employee ID in Table 1 has multiple results in Table 2). If you join these tables on Employee ID, an employee's salary is counted more than once because the employee is associated with multiple departments. The second table contains organizational information, such as department names. This can cause values to be over-counted.įor example, suppose you have two tables. The first table contains employee information, such as employee ID and salary. When multiple tables are treated as one table, after the tables are joined, all tables are queried. In some cases, Tableau treats the multiple tables as one table. When you connect to and join multiple tables together, you set up a denormalized version of the data.

For information about how Tableau handles combining data from different levels of detail (such as many-to-many relationships), see Cardinality and Referential Integrity.

For more information about relationships, see Relate Your Data. Note: If your join is mis-counting data, it could be a sign you should be using a relationships instead.