Business Intelligence and Data Visualization are proving to be beneficial to businesses and organizations all around the world. Many of these firms utilize Tableau, a Company Intelligence tool, to deploy these valuable strategies based on business data stored in the Cloud Data Warehouse and other locations. The ability to manipulate and alter data from various sources, such as Aggregations and Joins, is required when analyzing data from multiple sources. By correlating data from different sources, these activities aid in the discovery of crucial insights and patterns.
In this article, you’ll learn about the types of joins available in Tableau, an introduction to Join Clauses, and how to Implement Data Joining in Tableau.
Types of Data Joining in Tableau
1. Inner Join
Only the records that have identical values in both tables are selected in this sort of join.
2. Left Join
This sort of join selects all entries from the left/first table, as well as records from the right side/second table that have the same values. If there are no equal values, no records will be selected from the right.
3. Right Join
This join picks all entries from the right side/second table, as well as any records from the left side table with the same values. If there are no equal values in the first table, no records will be picked.
4. Full Outer Join
This type of join evaluates records from both the left and right tables, selects and displays all of the entries, and assigns NULL values to missing attributes.
5. Union Operation
Unlike a Join operation, a Union action unites two tables that have the same fields or columns. The first table contains the first set of rows/records, whereas the second table has the second set.
What is Join Clause?
A Join Clause is an expression that allows Tableau to match corresponding rows by identifying shared fields between tables and methods. In the event of equality, Tableau selects and matches rows with the same values using the equality operator (=).
In Tableau, the less than () or not equal to (>) operators are used in Join Clauses to implement non-equi Joining. These join clauses can also be used to do calculations, such as concatenation across many name fields. The following is an example of one of these clauses:
“[First Name] + [Last Name] = [First Name] + [Last Name]”
How to Implement Data Joining in Tableau?
Step 1: Connection with a Database
To begin, you must first connect to the database on which you wish to perform operations. Tableau provides a number of built-in connectivity options. The Tableau connector SDK can be used to create a custom connector to construct ODBC[Open Database Connectivity], Web Data Connector, JDBC[Java Database Connectivity], or Connector Plugin.
Here you may find detailed documentation about Plugins and Connectors.
When executing join operations between tables from separate databases, you’ll need to use a Cross Database Join.
Step 2: Addition of First Table
You’ll need to drag the first required table onto the Canvas from the left navigation pane. Go to the menu and select Open,” or double-click on the first table to open the Joining in Tableau canvas.
Step 3: Addition of Second Table
You’ll need to double-click the second table you want to join in the left navigation pane and drag it onto the Join canvas. Once you’ve made a connection to the second database, you’ll need to add the second table to Tableau for Cross-Database Joining. The “Add” option in the Data Pane can be used to complete this.
Step 4: Configuration of Data Joining in Tableau
By clicking the Join symbol, you may access the Join setup pane. To finish the Join, choose the required field from the first table and click OK, Then choose the Join operator, and lastly the field you want from the second table. When using Tableau to do a cross-database join, you may easily switch between the two data sources by using the Data Pane.
You learned about the types of joins available in Tableau, an introduction to Join Clauses, and how to perform joins between tables in this article.
Integrating and interpreting data from a large number of different sources might be difficult; this is where Hevo comes in. Hevo Data, a No-code Data Pipeline, allows you to move data from any source in an automatic and secure manner without having to rewrite the code. With Hevo’s excellent interaction with 100+ sources and BI tools, you can not only export and load data but also convert and enhance it in seconds, making it analysis-ready.
Follow Techdee for more!