The benefits of Business Intelligence and Data Visualization are becoming increasingly evident to businesses/organizations around the world. Tableau is a Business Intelligence service that is employed by many of these organizations to implement these useful techniques on their business data, maintained in the Cloud Data Warehouse and numerous other sources. Analyzing Data from multiple sources requires manipulation and transformation capabilities such as Aggregations and Joins. These operations help bring out important insights and patterns by correlating data from multiple sources.
In this article, you will learn about different types of Joins available in Tableau, an introduction to Join Clauses, the steps to carry out Data Joining in Tableau, and the steps to carry out Aggregation and establish Relationships.
Table of Contents
What is Tableau?
Tableau is a tool that is used for applications related to Business Intelligence and Data Visualization. This can help you get important insights by analyzing the data and providing objective measurements to support and help in strategic decision-making in a business organization.
The platform supports an easy-to-learn user interface and additional functionalities to collaborate with other employees in the organization. The user can get data from multiple sources and perform analyses on the aggregated data. Tableau is helping industries to reduce the analysis time and provides functionalities while ensuring flexibility, security, and reliability.
Key Features of Tableau
- Multiple Integrations: It provides multiple integrations and connectors for increased functionality and compatibility with various data sources.
- Easy User Interface: It hosts an easy-to-use and easy-to-learn user interface to perform complex data transformations without programming know-how.
- Real-Time Dashboards: It has the ability to create and host interactive real-time dashboards highlighting KPIs and data visualizations.
- Gather Insights: It helps users to convert their queries and questions into visualizations and objective metrics.
- Multi-Platform Accessibility: It has provision to access dashboards and reports on multiple devices such as mobile, web and desktop.
- Visual Customisations: There is a huge selection of visual customizations and templates that users can utilize to highlight important data.
Data Joining in Tableau: Types of Data Joins
The following types of Join Operations are available in Tableau:
- Joining in Tableau: Inner Join
- Joining in Tableau: Left Join
- Joining in Tableau: Right Join
- Joining in Tableau: Full Outer Join
- Joining in Tableau: Union Operation
1. Joining in Tableau: Inner Join
In this type of Join, only the records which have the same values on both tables get selected.
2. Joining in Tableau: Left Join
In this type of join, all records from the left/first table are selected and the records which have the same values on the right side/second table are selected. No records will be selected from the right if there are no equal values.
3. Joining in Tableau: Right Join
In this type of join, all the records from the right side/second table are selected and the records which have the same values on the left side table are selected. No records will be selected from the first table if there are no equal values.
4. Joining in Tableau: Full Outer Join
In this type of join, records from both left and right tables are evaluated, all the records are selected and displayed, and missing attributes are allocated NULL values.
5. Joining in Tableau: Union Operation
Unlike a Join operation, a Union operation combines two tables that have the same fields or columns. The first table provides the first set of rows/records and the second table provides the second set of rows/records.
Detailed information about Union Operation in Tableau can be found here.
What is Join Clause?
A Join Clause is an expression that helps Tableau identify shared fields between tables and methods to match corresponding rows. In the case of equality, Joining in Tableau is done using the equality operator (=) to select and match rows with the same values.
To implement non equi Joining in Tableau, less than operator (<) or not equal to (<>) operators are used in Join Clauses. These join clauses are also used for performing calculations such as performing concatenation in different name fields. An example of these clauses can be seen as follows:
“[First Name] + [Last Name] = [First Name] + [Last Name]”
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Steps to Implement Data Joining in Tableau
Following are steps that you can carry out to perform a Data Joining in Tableau:
Step 1: Connection with a Database
Firstly, you will be required to connect with the database on which you desire to perform operations. There are various native connection options available in Tableau. If you wish to create a custom connector, you can do so by using JDBC[Java Database Connectivity], ODBC[Open Database Connectivity], Web Data Connector or Connector Plugin which are built using Tableau connector SDK.
Detailed Documentation regarding Plugins and Connectors can be found here.
In case of performing Join operations between Tables of different Databases, you will be required to perform a Cross Database Join.
Step 2: Addition of First Table
From the left navigation pane, you will be required to drag the first required table onto the Canvas.
Subsequently, click on “Open” from the menu, or double click on the first table to open up the Joining in Tableau canvas.
Step 3: Addition of Second Table
From the left navigation pane, you will be required to double click on the second table you desire to join and drag it on the Join canvas.
In the case of Cross-Database Joining in Tableau, you will be required to add the second table after establishing a Connection from the second Database. This can be done by clicking on the “Add” option in the Data Pane.
Step 4: Configuration of Data Joining in Tableau
Open up the Join configuration pane by clicking on the Join icon. Proceed by selecting the
desired field from the first table, then select the Join operator and lastly select the desired field from the second table to execute the Join operation.
If you are performing Cross-Database Join in Tableau you can toggle between the two Data sources easily using the Data Pane.
What is Data Aggregation in Tableau?
Data Aggregation of the data is the process to control the granularity of data. Differentiation on whether the data is being aggregated or grouped can be made on the basis of the data type such as string, number, date etc. Aggregation is usually done before operating with Joins or Relationships to align the data in the desired manner.
Procedure to Implement Aggregation of Data
Step 1: You are required to click the plus icon on the Flow Pane and then click on “Aggregate”.
Step 2: Flow Pane will display aggregation steps and Profile Pane will show updates in the group profile.
Step 3: Subsequently you can drag and drop the fields of the tables between the two panes.
Step 4: You may also click “Add all” or “Remove all” to bulk apply and remove fields.
Step 5: Any cleaning operations carried out on the fields can be tracked in the Change Pane.
What is Data Relationships in Tableau?
Relationships are a better method to operate on tables as they preserve the level of detail while combining the information. They enable Context-based Joins to be executed on a sheet-by-sheet basis thus making each data source more flexible. Relationships are not depicted using Venn Diagrams but are instead illustrated using Data Models.
Relationships can be considered as contracts between two tables, as there is no predefined Join type and the user is only required to select the matching fields to define a Relationship. These relationships are flexible and can be many-to-many and support Full Outer Joins.
Procedure to Implement Relationships
Following are the steps that you can carry out to implement Relationships between tables:
Step 1: Connecting the Data Source
Firstly you will be required to connect the database on which you desire to perform operations.
There are numerous native connection options available in Tableau. If you wish to create a custom connector, you can do so by using JDBC[Java Database Connectivity], ODBC[Open Database Connectivity], Web Data Connector or Connector Plugin which are built using Tableau connector SDK.
Detailed Documentation regarding Plugins and Connectors can be found here.
Step 2: Adding Table to Canvas
Start by adding the desired first table from the left Data Pane to the Canvas. Subsequently drop the second table to the Canvas. [Drop the table if you see the noodle icon while adding second table]
Step 3: Defining the Relationship
The Edit Relationship window will open up once the second table is added to the canvas. You will be required to select the relevant fields and define the relationship between the tables. If the user does not define any constraints, by default Many-to-Many relationship is established and referential integrity is set to “Some Records Match”.
Step 4: Adding more Tables to the Relationship
More tables can be added using the same steps and by defining the relationships after the table is added to the canvas.
Step 5: Viewing a Relationship
Users can drag over the Relationship line between the tables on the canvas to check out the matching fields that define that relationship. You may also hover over logical tables to check out their components and descriptions.
Conclusion
In this article, you learned about different types of Joins available in Tableau, introduction to Join Clauses, the steps to carry out Joins between Tables, and the steps to carry out Aggregation and establish Relationships.
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Abhishek is a data analysis enthusiast with a passion for data, software architecture, and writing technical content. He has experience writing articles on diverse topics such as data integration and infrastructure.