Data joining is a common need in any data analysis. We may need to join data from many sources or join data from different tables in a single source. It is provides to join the table by using the data pane available by under. Data menu in the Edit Data Source.
Creating a Join
Let’s consider the data source sample superstore. To create a join between Orders and Returns table. We have gone to the Data menu and then choose the option Edit Data Source. Next we drag the two tables, orders and Returns to the data pane.
The below diagram displays the creation of inner join between orders
Editing Join Type
The type of join which Table creates automatic could change manual. We click on the middle of two circles showing join. A popup window appears below which displays the four types of joins available.
In the below diagram we see the inner and left outer join as the available joins.
Editing Join Fields
We should change the fields forming by clicking on the Data Source option for join condition. Available in the join popup window. While selecting the field we can also search for the field we are looking for using a search text box.
Data Blending is a powerful feature in Tableau. It is use when there is relate data in more data sources to analyze together in a single view. As an example which you want, The Present sales data is in a relational database. Then to compare actual sales to target sales. We can blend the data based on common dimensions to get access to the Sales Target measure. The two sources involved in data blending are referring as Primary data sources.
Preparing Data for Blending
Tableau has two inbuilt data sources named Sample superstore. mdb which we will use to illustrate data blending. Let’s first load the sample coffee chain to tableau and look at its metadata. Go to the menu Data. Browse for the sample coffee chain new Data Source file which is a MS access database file. The below diagram displays the different tables and joins available in the file.
Adding Secondary Data Source
Next we add the secondary data source named by again following the steps Data. New Data Source and choosing this data source. Both the data sources now appear on the Data window as shown below.
Blending the Data
Now we can integrate the data from both above common dimension for based on sources. Note that a small chain image appears next to the dimension named State. This indicates the common dimension between the two data sources.
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We select the bullet chart option from Show me to get the bullet chart below. It showed how the profit ratio varies for each state in both the superstore and coffee chain shops.