Comparing Relationships vs Joins in Tableau: Which One to Use When?
Data visualization has been revolutionized with Tableau, allowing users to connect to different data sources and create stunning visualizations. One common problem that data analysts often encounter is deciding between relationships and joins in Tableau. This article aims to provide clarity on the differences between the two and when to use them for optimal results.
What are Relationships and Joins in Tableau?
Tableau allows users to link tables in two ways: relationships and joins. Relationships enable the creation of a hierarchy between tables based on shared fields, whereas joins combine fields from different tables based on a common field value.
In relationships, one table is designated as the primary table, and the other tables are designated as secondary tables. The primary table contains all the fields necessary to answer the question, while the secondary tables only add context.
Joins, on the other hand, combine fields from multiple tables into a single view. Users can choose between four join types: inner join, left join, right join, and full outer join. Inner join excludes data that doesn’t match in both tables, while left join includes all data from the primary table and only matching data from the secondary table.
When to Use Relationships in Tableau?
Relationships are often used when working with multiple data sources, as they allow multiple tables to be linked. In addition, relationships provide better performance for large datasets and reduce clutter on the Tableau interface by displaying only the necessary fields.
Relationships are also useful when analyzing data at different levels of detail. For example, a sales analysis may require a single table to display sales information, and another table to display the salespeople who made the sales.
When to Use Joins in Tableau?
Joins are most commonly used when working with a single data source or when creating customized views. Joins allow users to combine fields from different tables to answer specific questions, providing better context and clarity.
When using joins, it is essential to ensure that the joining field is present in both tables and is of the same data type. Additionally, Tableau recommends using aggregations when using joins to avoid duplicating data and sacrificing performance.
Conclusion
In summary, relationships and joins in Tableau are used to link multiple tables and provide insights into data. Relationships are useful when dealing with multiple data sources and analyzing data at different levels of detail, while joins provide context and clarity when working with a single data source or when creating customized views.
When deciding between relationships and joins in Tableau, it is essential to consider the data sources, the level of detail required, and the performance needed. By understanding the differences between relationships and joins, data analysts can choose the appropriate method to produce the most optimal results.
