Relationship in Tableau

 Relationships are a dynamic, flexible way to combine data from multiple tables for analysis. We recommend using relationships as your first approach to combining your data because it makes data preparation and analysis easier and more intuitive. 

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Requirements for using relationships

When relating tables, the fields that define the relationships 
1 must have the same data type.
2-Changing the data type in the Data Source page does not change this requirement.
3- Tableau will still use the data type in the underlying database for queries.
4-You can't define relationships based on geographic fields.
5-Circular relationships aren't supported in the data model.
6-You can't define relationships between published data sources.
7-- Relationships do not allow us to decide on the join type.
8-In the earlier versions of Tableau, in the absence of a relationships, this task would have required data blending with multiple sources and would therefore be slow. Using relationships, we can do this in one datasource. Also, data blending is limited to a worksheet, but relationships are available for the entire workbook. Relationships will increase the performance of your dashboard

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Here are some advantages to using relationships to combine tables:

1-Make your data source easier to define, change, and reuse.

2-Make it easier to analyze data across multiple tables at the correct level of detail (LOD).

3-Do not require the use of LOD expressions or LOD calculations for analysis at different levels of detail.

4-Only query data from tables with fields used in the current viz.

5-Are displayed as flexible noodles between logical tables

6-Require you to select matching fields between two logical tables

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1-Do not require you to select join types

2-Make all row and column data from related tables potentially available in the data source

3-Maintain each table's level of detail in the data source and during the analysis

4-Create independent domains at multiple levels of detail. 

5-Tables aren't merged together in the data source.

6-During analysis, create the appropriate joins automatically, based on the fields in use.

7-Do not duplicate aggregate values (when Performance Options are set to Many-to-Many)

8-Keep unmatched measure values (when Performance Options are set to Some Records Match)

9-Relationships are a dynamic, flexible way to combine data from multiple tables for analysis. We recommend using relationships as your first approach to combining your data because it makes data preparation and analysis easier and more intuitive. 

10--Do not duplicate aggregate values (when Performance Options are set to Many-to-Many)

11-Keep unmatched measure values (when Performance Options are set to Some Records Match)

12-Make your data source easier to define, change, and reuse.

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