Introduction

Businesses are eager to look for new methods of transformation to combine data to get the optimum efficiency. One of these processes is Tableau Data Blending. Data blending in tableau is greatly in demand among the various enterprises and to be able to capitalize further on this, Tableau is expanding its offerings to Tableau viewer, creator, and explorer.

  1. Definition
  2. Why do you need TDB?
  3. Data Blending
  4. Data joining
  5. Working
  6. Types
  7. Limitations

1) Definition

Data blending in tableau is a crucial feature of a tableau that is used to analyze the data that is related to one single view among the multiple sources of data. Data blending makes the tableau offering customizable and scalable and this is what gets the company many positive feedbacks. Data blending has an important role to play in any data cycle of an organization and this makes it vital.

Data blending combines the data from various distinct sources and then brings in additional data from another secondary source. It then displays this data in the primary source in a single view. Data blending also combines the supplement of the data table from one of the data source with the data column from some other data source. Joins are mostly used to combine the data and at times these get backed by factors like granularity and data type when data blending gets used.

2) Why do you need TDB?

Tableau Data Blending gives the user an option to combine and join the various sources of data. The process of joining and mixing is different in tableau. Unlike in the cases of other joining, the data blending allows combining the data sources after there is aggregation on the source that is specific. Tableau Data Blending is less blending of data on the single worksheet. This is data that is got from various sources and this then gets attached to the standard dimension.

There is no requirement to create the new level joins and it is also not a way to add dimensions and rows to the data. This gets utilized when there exists data related to the various sources that you want to combine in one single view. To combine the data you will first have to add the standard dimension from the primary data source along with the view.

3) Data Blending

Here is how the data blending comes into use by the tableau developer. Suppose you have the data stored in two different databases. Also, the data granularity that is captured in each of the tables is different in the two sources of data. This makes data blending the best way to combine the data.

Data blending is used when you want to combine the data from various sources that are not supported by the cross-database joints. In this case, you will have to set up a different data source for the data that you wish to analyze. You then make use of the data blending to use a single sheet to combine the source of data.

Data blending is also used when the data is at different detail levels. At times one data set will capture the data using various detail levels. This could be that one has lesser or greater granularity. Data blending helps to combine this data.

4) Data joining

Data blending and the traditional left join stimulate each other. The difference lies when the join gets performed as per aggregation. It will need two data sources which are the secondary and the primary source. When it is a primary data source then it will perform the functions of the main table. Any other data source will be secondary. The secondary data source columns will correspond to the primary data sources and will appear in the view. This means that there will be an exact mapping of the primary and the secondary data source.

5) Working

Tableau Data Blending does not create any joins of low level and also not away to add any new rows or dimension to the data. The method is the best fit when you have related data in a distant source that needs to be analyzed together in one single view. If you wish to integrate data then you will first have to add the standard dimension from the primary source of data to the view.

Like in the case of a sales and a target business the operation that needs to be performed in the Tableau Data of the two different data sources. Here you blend the primary and the secondary data of sales. The two data sources should have one common file. When the secondary data source is switched in the window then tableau links the first name automatically. A custom relationship gets formed to create an exact mapping between the two fields.

6) Types

Tableau Data Blending is of two types

  • Automatically Defined Relationship is best when the field in which the analysis works consists of the same field name for both the data sources. If not then there are alias names that can match.
  • Manual Tableau Data Blending is a process that is used when there is a scenario that needs a complex blend that is the budget comparison data from spreadsheets with the data from the database.

7) Limitations

Here are the tableau data blending limitations which revolve around the non-additive aggregates like the median and the RAWSQLAGG.

  • Tableau Data blending compromises on the speed of query in high granularity
  • When the data that is calculated and uses blended data is sorted then it does not get listed in the sorted fields drop-down dialog box.
  • The cube data sources can only function as a primary source to blend the data in Tableau and these cannot be used as a secondary source of data.

Conclusion

Data blending is an important feature and it is used when there are related data that is present in various data sources. You want to analyze them in a single view. You make use of joins to perform the kind of data combining however there are times that as per the factors like granularity and type of data you would want to make use of data blending.

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