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Data Blending vs Data Joining in Tableau:


In this Blog, we are going to discuss about the purpose of Data joining and Data blending in Tableau.


Joins are used to combine tables by adding more columns of data across tables having similar structures. The joins must be created on data before the analysis process and we can't use the published data source in a join. Data blending is a method for combining data from multiple sources. Data blending is mainly used to get additional information from a secondary data source and displays it with the existing data source. It can be useful to create a relationship based on a sheet-by-sheet basis with the published data sources.



(Image by Author)


The above Image shows the process of combining the data in the tableau. The key difference between the data blending and joining is based on when the aggregation process is happening.


(Image by Author)


How to do Joining in Tableau?


Step1: Load Dataset into the Tableau. we have to crate a relationship between the tables. I have added Countrypop data file into the Tableau.

(Image by Author)


Step 2:Drag the tables population by country and population growth rate in to the pane. This will create a join between the field based on the common field.

(Image by Author)



The two tables are connected through the inner join. The join happened between the two tables with the Same Data source.


Limitation of Joins:

  • Unable to use on published Data sources

  • Data Duplication and loss of data


When and how to do data blending in Tableau?

It can be used when you want to analyze data available in different sources.


STEP 1: I have added two different dataset population by country and populationgrowthRate in tableau.

(Image by Author)


STEP 2:

To create a relationships, click Data menu - Edit Blend Relationships. When blending in Tableau, there is always a primary source and a secondary data source. It is important to understand which is the primary source, it can impact the result. In this example the primary Source us Population Growth Table and the Secondary Source is Population By Country.


(Image by Author)



STEP 3:

We need a common field called "linking field" form the primary source and secondary source .In this example the common linking field is Country. Drag country to the rows and population growth rate into text. This will create a chart on Population growth rate by country. This chart created based on the two fields from the different Data Sources.

(Image by Author)


If we have more than two Data sources, the linking fields can be activated with different worksheet ,so the blended data sources can join on different fields in different worksheets within the same Tableau workbook.


Recommendations For Tableau Data Blending:

Points to consider before doing Data Blending

  1. we have to fix which data source is the Primary source and Use small Data set as a secondary Source

  2. Ensure data connections are activate in the worksheet

  3. Joins are case sensitive in the data blend so check before joining

  4. If we are going to filtering the view, set the data source containing the filter fields as Primary

  5. Try and keep the number of blended data sources to a minimum for the troubleshooting process

  6. Use data source filters to remove redundant data from the secondary source

  7. Use a data blend to bring in single dimension values or measures.

Limitations on Data Blending:

  • · Some Calculation field aggregations are not supported by a data Blend operation

  • Asterisk will occur during the blending process

  • · Filters Issue- the data from the secondary source AND the primary source if there are connected fields.

  • · View option will give information about the primary source of data

  • · Dashboard performance -Blending of big data extracts will have a big negative performance hit and could bring down your Tableau server.

Data blending can be very useful, but can also be problematic. When used well it provides a simple way to add additional data to a dashboard. When used incorrectly it can bring down a Tableau Server.


Conclusion:

Data Joining & Blending have their own importance and should be wisely chosen based on the requirement. I hope this blog will give basic knowledge about Data joining and Blending.






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