Difference between Data blending and Data Joining  


Do you want to make a report or dashboards for your business, meeting and presentation? But unable to organize the data from various source.  Because it’s critical to interact with many data sets, if the data is inaccurate, the entire goal is a failure. So we know information comes in from a variety of sources. Don’t worry in this article we will help you to short out your problem.  

We understand pulling data from multiple sources and combining it into a single dataset used to be difficult and time-consuming, but recent advances in Data blending and Data Joining concept have made it simple and intuitive. In this article we will discuss the Difference between Data blending and Data Joining. After knowing the difference you can apply this concept as per your report requirement.  

What is Data Blending? 

When you want to make a report and your sources are heterogeneous such as Excel Files, Oracle, SQL Server, DB2, Sybase, and others. And you want to use these different sources for your reporting purposes then, in this scenario you should use Data blending.  

What is Data Joining? 

When your sources are same mean combine the data between two or more tables or sheets then, in that scenario you can use Data joining. 

Note: if your grain of the table is different, then you should go for Data blending. If your grain of the table is same then, you can go for Data joining  

Difference between Data blending and Data Joining  

  • A method of integrating data that supplements a table of data from one data source with columns of data from another data source is known as data blending. 
  • Data blending is a form of left joint that is preferred or required to be used based on the circumstances. In certain cases, utilizing a join will suffice, while in others, blending will either provide better or faster results or be the only option. 
  • Joining data is a laborious process, but data blending is a feature that tableau performs automatically as you work on your sheet, making it a more intuitive tool to utilize if the requirements are met. 
  • The first and most basic need for blending data in tableau is to have a common field that connects the two data tables.
  • From a technical standpoint, blending takes individual query results from each data source and aggregates them in a tableau view, after which it connects and joins the query results on a common field that should contain information of the same data type.
  • When you use Data Joining, the aggregate happens at the database level, and only the output of the join is returned to tableau when blending, the aggregation happens in tableau.
  • If you join two data tables with duplicate values that aren’t aggregated properly while doing some preliminary work on the data, you’ll end up with an artificially inflated data set. Tableau blending solves this problem automatically by taking into account the level of granularity you’ve selected in the view your sheet and combining the data sources with aggregated fields directly. 

 Final word 

It’s clear to see why Data Blending wins on flexibility and features based on the summary of the differences between Data Blending and Data Joins in Tableau. As a result, you may now use Tableau to create a viz using data from many database sources. 

For additional information about Tableau’s features, keep an eye on our blog. Also, if you need assistance or coaching with Tableau, please visit our services page. 

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