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Table of contents
1.
Introduction
2.
Tableau Relationship
3.
Tableau Joins
4.
Pros of Relationships in Tableau
5.
Pros of Joins in Tableau
6.
Cons of Relationships in Tableau
7.
Cons of Joins in Tableau
8.
Comparison Table (Relationships vs Joins)
9.
Frequently Asked Questions
9.1.
What is the main difference between Relationships and Joins in Tableau?
9.2.
When can I use Relationships instead of Joins?
9.3.
Which method is more suitable for granular analysis?
9.4.
Which one provides better performance: Relationships or Joins?
9.5.
How are null values handled in Relationships and Joins?
10.
Conclusion
Last Updated: Mar 27, 2024

Relationships vs Joins

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Anubhav Sinha
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Introduction

Hey learners! As we all know that the database is used to store data in the form of tables. And in MNCs, have you ever considered how these tables and data are handled? If you are saying no, then you are at the right place. Let's dive deep into this topic.

Relationships vs joins image

In this blog post, we will explore the distinction between Relationships and Joins in Tableau and discuss their advantages and limitations.

Tableau Relationship

By the word "Relation", it is evident that it's related to the connection. The main purpose of Relationships is to establish connections between tables based on common columns or fields. It is an easy and flexible way to combine data from multiple tables for analysis. It is used in working with structured and denormalized data sources.

The Relationship generates the appropriate join conditions based on the field Relationships. A Relationship is represented by a diamond shape in an ER diagram. Below are the four types of relationships.

  • One-to-One Relationship: In this Relationship, a single record in Table A is related to the single record in Table B. Also, a single record in Table B is related to the single record in Table A.
one-to-one example

In the above figure, the Id of Table A is related to the id of Table B. So, it is a one-to-one relationship.

  • One-to-Many or Many-to-one Relationship: Each record of Table A is related to one or more than one record of Table B.
one-to-many example

In the above figure, one person can have many accounts so it is a one-to-many relationship. On the other hand, many accounts are held by one person, so it is a many-to-one relationship.

  • Many-to-Many Relationship: Each record of Table A can be related to one or many records of Table B, and vice-versa.
many-to-many example image

In the above example, each customer can buy more than one product, and many customers can buy one. Therefore, it is a many-to-many relationship.

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Tableau Joins

Joins are a way to combine data from multiple tables based on specific join conditions. Joins combine two tables into a single table. Joins are mainly used when you need more control over the join criteria. The common field is the primary key in one table, acting as a foreign key in another. There are various types of Joins and some are below.

  • Inner Join: It combines records from two tables whenever there are matching values in a field common to both tables.
inner join image
  • Left Join: It returns all the records from the left table and matching records from the right table.
left join image
  • Right Join: It retrieves all rows from the table on the right side of the join and matches rows from the table on the left side.
right join image
  • Natural Join: It joins two or more tables based on common rows of a column.
Natural Join image

Pros of Relationships in Tableau

Below are some pros of Relationships in Tableau.

  • It makes your source easier to change, define, and reuse.
     
  • It reduces the complexity of the underlying data structure and simplifies the data modelling.
     
  • It facilitates data blending, where you can combine data from multiple tables.
     
  • You can easily access and explore the related data without complex joint calculations.
     
  • You can easily blend data from multiple sources, such as databases, spreadsheets, or cloud services with the help of Relationships.

Pros of Joins in Tableau

Let’s discuss the pros of Joins in Tableau.

  • It allows you to combine data from various tables or sources into one dataset. 
     
  • It provides flexibility in exploring and examining the data.
     
  • Joins can help to improve overall performance, mainly when dealing with large datasets.
     
  • It allows us to perform granular analysis by bringing together data.
     
  • You can ensure data accuracy and consistency by joining the tables.

Cons of Relationships in Tableau

Below are some cons when working with Relationships in Tableau.

  • It works best with structured data sources. But while dealing with unstructured data sources, such as JSON or XML files, establishing Relationships may be more complex.
     
  • There are complexities while dealing with large or complex datasets.
     
  • Managing and understanding the Relationships between multiple tables can be challenging.
     
  • If primary and foreign keys are missing, then Relationships may not be possible. Relationships in Tableau rely on the presence of primary and foreign keys in the data.
     
  • When using Relationships, creating and maintaining data extracts like TDE or Hyper files can become more complex.

Cons of Joins in Tableau

Here are some cons when working with Joins in Tableau.

  • Joins increase complexity while dealing with multiple tables or complex datasets.
     
  • Joining multiple tables or large tables can impact query performance in Tableau.
     
  • Data redundancy occurs during combining tables with similar information.
     
  • Joining tables can introduce null values in the resulting dataset.
     
  • We can not use Joins on published data sources.

Comparison Table (Relationships vs Joins)

Below is the difference table between Relationships and Joins.

S.No

Relationships

Joins

1

Relationships are called the logical layer.

Joins are called the physical layer.

2

It happens at the worksheet level.

It happens at the workbook level.

3

Relationships are based on logical associations between tables using standard fields.

Joins combine tables based on specific join conditions, mostly using primary and foreign keys.

4

Relationships provide a simplified approach to data blending.

Joins offer more flexibility in data blending.

5

Relationships do not merge two tables into a single table.

Joins combine two tables into a single table.

 

Frequently Asked Questions

What is the main difference between Relationships and Joins in Tableau?

Relationships provide automatic data blending between tables. But Joins explicitly combine tables based on specific join conditions.

When can I use Relationships instead of Joins?

You can use it while working with structured data sources that already have established relationships.

Which method is more suitable for granular analysis?

Joins are more suitable for granular analysis.

Which one provides better performance: Relationships or Joins?

In the performance, Relationships in Tableau perform better than Joins.

How are null values handled in Relationships and Joins?

Relationships automatically handle null values by maintaining referential integrity. Joins can introduce null values when combining tables, especially with left, right, or full outer Joins.

Conclusion

In this blog, we discussed the difference between Relationships and Joins. This blog helped you to enhance your Relationships and Joins learning. Check the below articles to know more.

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