Tableau Data Blending

What is Tableau Data Blending?

When it comes to advanced data analysis, there are multiple data sources from which data analysts need to define relations and infer data from multiple sources. Using features from different data sources to create effective graphs or tables is called Data Blending. Tableau Data blending performance is seamless and makes it easy for beginners to blend data without a fuss by simply dragging and dropping features from different data sources.

Here is an example depicting Tableau Data Blending using the Sample-Superstore dataset.

Here, the Sample-Superstore dataset has 2 sheets, Orders and People. The Region and People were taken from the “People” dataset and the “Order ID” was taken from the “Orders” dataset.

How to Blend Data in Tableau?

Follow these simple steps to perform data blending. Generally, it is required that there is at least one common feature or, you must define the common features manually, similar to defining a relational schema.

Step 1: Once you open The Tableau Public application, select “File” in the toolbar and select “New”.

It will open a new workbook, where you can add sheets and dashboards in tableau by selecting it at the bottom of the application.

Step 2: Add the main data source. Here, the “Orders” worksheet from the Sample-Superstore dataset is chosen.

Step 3: Go to a new sheet and start creating your visualizations.

Step 4: In the toolbar, click on “File” and then “New Data Source.”

Click on “Microsoft Excel” to add new files.

Step 5: Select the dataset in your local storage. Here, the Sample-Superstore dataset is chosen again.

It opens a new data bar in Tableau.

Step 6: Select “Returns” and go back to the Worksheet.

Now, you can see both the data sources on the top-left-hand side of the application.

Step 7: In the Orders dataset, select “Category” and “Sub-Category.”

Step 8: From the “Returns” dataset, drag and drop the “Returns” feature onto the table as shown.

The orange tick icon on the “Returns” dataset shows that the dataset has successfully blended with “Orders” and any feature taken from the “Returns” dataset is indicated with an orange tick.

With that, you have successfully blended data from two different sources.

These are the number of returns of every sub-category depending on the Category.

Examples

Go through the various ways to utilize tableau data blending aggregation as shown below.

Example #1

Suppose you want to find the Percentage of Sales by comparing it with the Sales target and the actual sales, you can do so by introducing a Tableau Data Blending Calculated Field to the worksheet and using it with two features from different datasets. Follow these simple steps below to learn how to implement this.

Step 1: In a “New” Workbook, connect to the Sample-Superstore Dataset by dragging and dropping the Excel file in question.

Step 2: Check if the data source is connected. The Orders Worksheet from the Sample-Superstore dataset is connected.

Step 3: Switch to the worksheet to add new datasets.

Step 4: Click on “File” in the toolbar and then “New Data Source”.

Click on “Microsoft Excel” to add new files.

Step 5: Select the dataset in your local storage. Here, the Sales Target dataset is chosen.

Step 6: Select “Order Date” from the Sample-Superstore Dataset and click on the ‘+’ icon on the YEAR to expand it to QUARTER as shown.

Then remove the YEAR(Order Date) leaving only the QUARTER(Order Date).

Step 7: Next, select “Segment” and place it in the rows.

Step 8: Add the “Sales” feature to the rows. Then right-click on it and select “Discrete”.

Step 9: Create a Calculated field to implement the Tableau Data Blending Calculated Field.

Step 10: To find the Percentage, you need to divide the total sales and the total sales target.

As seen above, you can drag and drop the features into your calculated field.

Step 11: Drag and drop the calculated field into the “Text” section in the “Marks” tab.

You can see that the data is blended successfully.

With that, a table blending the sales and sales target datasets is done successfully.

Example #2

You can implement data blending to compare and contrast data, such as sales and sales targets and so on. The example demonstrates how you can use tableau data blending asterisk with different graphs and different features.

Step 1: Open a New Workbook in Tableau and connect to the Sample-Superstore dataset.

Step 2: Select “Orders” in the Sample-Superstore dataset.

Step 3: Go to a new worksheet to start with your work.

Step 4: Add another data source by clicking on “File” in the toolbar and selecting “New Data Source”.

Select the data type that you want to connect with. Here, “Microsoft Excel” is shown.

Step 5: Select the dataset in your local storage. Here, the Sales Target dataset is chosen.

Step 6: Take “Segment” from either of the datasets (Segment is the common feature between both.)

Step 7: Place “Sales” from the Sample-Superstore dataset into the rows.

Step 8: Place “Sales Target” in the “Rows” component.

This is the current graph.

Step 9: Click on “Show Me” to select from the various options available.

Select “side-by-side bars” to compare both the sales and sales targets.

With that, a bar graph using tableau data blending aggregation has been implemented successfully.

Example #3

Here, you can learn how to compare and contrast different features and show them in Tableau Map format to help viewers understand more about the sales and number of returns made in proportion to them. You can blend data from different worksheets in the Sample-Superstore dataset. Here, the “Orders” worksheet and the “Returns” worksheet are utilized. Follow these simple steps to implement it yourself along the way.

Step 1: In a new workbook, connect it to the Sample-Superstore dataset.

Step 2: Select the worksheet from which you want Tableau to extract it. Here, “Orders” are chosen.

Step 3: Tableau creates a new worksheet “Sheet1” by default. Go to it to continue further.

Step 4: To add another worksheet, you need to add a new data source. To do so, select “File” from Tableau’s toolbar and select “New Data Source”.

This opens a new popup where Tableau asks you to select the file type you want to import from your local storage to perform data analysis. Select “Microsoft Excel”.

Step 5: In the popup, go to the file directory where you have the dataset stored and select “Sample-Superstore”.

The data overview is shown again.

Step 6: In the overview, select “Returns”.

You can see both of them in the worksheet.

Step 7: Select “Latitude” and “Longitude” and place them.

Step 8: Place “State” in the “Text” tab in the “Marks” tab.

Step 9: Place the “Country” feature from the “Sample-Superstore” dataset into the “Detail” component from the “Marks” tab.

Step 10: Place the “Returns” feature from the Returns dataset in the “Size” component in the “Marks” tab.

Step 11: Increase or decrease the size of the bubbles based on your convenience.

Step 12: Copy and paste Longitude in the Columns and right-click on them to create a dual-axis.

Step 13: In the other axis, select “Sales” from the Sample-Superstore dataset and place it in the “Color” section in the “Marks” tab.

Change the measure from “SUM” to “COUNT”.

This is the graph, currently.

Step 14: Right-click on “Longitude” and select “Dual-axis”.

This is the final graph comparing both the number of sales and returns.

Important Things To Note

• Before blending data, thoroughly understand the structure and relationships within each dataset.
• Cleanse and prepare your data beforehand to ensure consistency and accuracy. This includes removing duplicates, handling missing values, and standardizing data formats.
• If there are direct relationships between fields in different datasets, define these relationships explicitly in Tableau.
• Blend data from compatible sources with similar granularities and dimensions.
• Always validate the results of your data blending analysis to ensure accuracy.
• Data blending can impact performance, especially with large datasets. Consider the Tableau data blending performance implications of blending data and optimize accordingly.

Frequently Asked Questions (FAQs)

Recommended Articles

This has been a guide to Tableau Data Blending. Here we learn how to blend data aggregation in Tableau with examples & points to remember. You can learn more from the following articles –

• Tableau Bins
• Tableau Map
• Tableau Histogram