How to Perform Data Blending in Tableau

Edited 3 weeks ago by ExtremeHow Editorial Team

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Data blending in Tableau is a key technique when it comes to working with data from multiple sources. It allows users to combine data from different sources into a single view, which can be used for comparison, analysis, and visualization. Understanding how to blend data correctly in Tableau can help gain deeper insights without needing to alter the original data sources. Below is a comprehensive guide to blending data in Tableau, with simple examples to guide you through the process.

Understanding data blending

Data blending is like creating a virtual database in Tableau. You use blending when you want to combine data from different sources to create a unified view. Each data source will retain its uniqueness, and Tableau uses the relationships established on common dimensions to merge them together. It is important to distinguish between data blending and data joining. Joining is when data from different tables is combined within one data source, while blending occurs across different data sources.

Preparing the base

Before you begin blending data, you must have at least two data sources in your Tableau workspace. These can be spreadsheets, databases, or even web data connectors. Load these data sources into Tableau using the Data pane. Generally, data blending occurs in a "primary" to "secondary" data source relationship. The primary data source is the main data set, and it typically contains the fields that drive your visualization.

Select primary and secondary data source

First, choose the primary data source. This is usually the more detailed data set or the one where most of the fields of interest exist. Once you have created a visualization using the primary source, you can add fields from your secondary data sources.

Build rapport

To blend data, Tableau needs a common connection point, usually a dimension such as "Date," "ID," or "Name," that exists in both data sets. This connection point is known as the linking field. It is critical for accurate blending. In Tableau, you set this field by dragging and dropping. When dragging a field from a secondary data source into a view that uses the primary data source, Tableau automatically tries to define a relationship by using fields with the same names.

Installation of the mixture

Here's how you can blend data in Tableau step by step:

1. Load your data:

   Start by loading two data sources into Tableau. For example, let's say you have a spreadsheet of "Sales Orders" and another spreadsheet of "Customer Data."

2. Select the primary data source:

   Start by selecting one of the data sources as the primary. Let's choose "Sales Orders" for this purpose. Create a basic visualization using fields from the sales order sheet, such as "Sales Amount," "Product," or "Date."

3. Add a secondary data source:

   Once your basic visualization is ready, you can now add data from the "Customer Data" source. Drag a field from the customer data into your visualization. If Tableau detects matching data fields, it will automatically blend them.

4. Verify linking fields:

   Notice how Tableau uses a small link icon (chain link) next to the fields it automatically links. Aligning these fields is essential for accurate blending.

5. Adjust relationships:

   If Tableau doesn't automatically choose the correct linking fields, you can set up the relationship manually. To do this, go to Data > Edit Relationships, then assign your linking fields specifically.

Optimizing mixed data

Once your data is blended, you may want to further customize the way the data is presented. Here are a few ways to get a more customized view:

• Check the aggregation level:

  Make sure the fields in both data sources are aggregated at the same level. For example, make sure both contain daily, monthly, or yearly data if necessary.

• Use a calculated field:

  Create calculated fields that incorporate primary and secondary data sources to gain new insights. For example, you can calculate a 'discounted price' using discount data from a secondary source.

Considerations for data blending

Although data blending offers significant benefits, keep the following in mind:

• Data Limitations:

  Remember that blending on linking fields is done at an aggregate level. Make sure that the linking field does not adversely restrict or aggregate the records.

• Display:

  Extensive use of blending, especially with large data sets, can impact performance. Optimize data sources to keep them as small as possible.

• Data source modification:

  If the structure of the underlying data source changes, be prepared to reevaluate established relationships and make adjustments accordingly.

Example scenario

Imagine you have a "Sales" data source with fields for "Order ID," "Sale Amount," and "Order Date." Also, you have a "Shipping" data source with fields for "Order ID," "Shipping Date," and "Shipping Cost." To analyze them together:

1. Use "Sales" as the primary data source. Create a visualization showing "Sales Amount" over time.
2. Add "Shipping Cost" from the "Shipping" data source. Tableau links these using the "Order ID".
3. Examine the graph showing sales against shipping costs on different dates.

Conclusion

Data blending in Tableau is an effective way to combine different data sources for more comprehensive analysis. It allows users to correlate different aspects of data into a single visualization while maintaining the integrity of each source. By carefully setting up primary and secondary relationships, ensuring the correct linking fields, and being aware of the limitations of blending, you can use Tableau's powerful capabilities to seamlessly blend data and extract valuable insights.

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