What is Data Blending?
Analyzing the myriad of data that is produced in a minute, is complicated without the assistance of easy data mining tools. We use many tools like Excel to Tableau data analyzing. Data blending is joining related data from different sources in a single view.
Statistics say that organizations spend 80% of their time collecting and analyzing data. Quintillion of data is produced in an hour in a large organization! Blending is a powerful feature available in Tableau.
Data blending in Tableau brings the additional information available in the secondary data source and displays it with the primary data source. Here let us see how we can analyze data using the blending option in Tableau.
Read: Tableau vs Power BI
Several ways are available in Tableau to combine data, like Relationships, Joints and Blends.
- Relationships – It is a default method that is reliable and flexible. It combines data over all the sources, including tables. Despite all its combining effects, it cannot combine data over a calculated field and if it is shared over the internet or Tableau server.
- Joins – It combines data over tables provided if the rows are of the same structures. It has a drawback of data loss and duplication if the tables are of different levels. So, it is always recommended to check the table structure and levels before joining two data sources.
- Blend – Unlike joins or relationships, the blend does not combine the data. Instead, it aggregates the values and displays together in the same view. So, the data blending in Tableau can aggregate the data from multiple sources, of all levels and display them in one view.
The blend is highly recommended for operations done on published data or on sheet by sheet linking that is varying on every sheet. It correlates the different data sources in a shorter period, unlike the traditional data processing that involves more time and money.
Simply put, a left join is created between the primary and secondary data sources. This matches with all the rows from the primary data source that matches with the secondary data source. This is how a blend in Tableau is created. When you are much worried about the type of data and its granularity, then data blending in Tableau is recommended rather than the conventional joins.
An * (asterisk) will appear indicating the multiple dimensions in the single level. A secondary data source is re-aliased in the primary data source.
Why Should You Blend Data in Tableau?
Data blending in Tableau is widely preferred by SQL writers because of the advantages it has over the traditional joins and relationships. In joins, there are two tables, the left and the right. The left being dominant, whenever a query is run, the entire left table is returned. In the right table, a new row is created at every instance a similar data source is found. This allows too many duplications. Besides, joins have other limitations:
- Results depend upon the choice of the left table.
- Complexity increases when more numbers of tables are added in the query.
- Cross-database joins are not supported.
- The query will be stressed if data of different levels of details are present in the table.
Must Read: Tableau Data Visualization
How to Blend Data in Tableau
When using data blending to combine the data source, a query is run that returns the aggregate as combined visualizations. Simply put, you acquire the data from different data sources, combine them using join and clean them. This is the simple method of combining two data sources using the blend.
Whenever your data needs cleaning use data blend instead of joining. Too blend already connected data sources on a workbook. Drag one field from the data source, it becomes the primary source. Then drag the other field by switching to the next data source, that becomes the secondary data source.
An orange link is formed between the two data fields indicating the blend. If the link is still grey, it means the link is broken. This can be done for multiple data sources. The secondary data source is added by Data > New data source.
The primary data source will have a blue tick mark ( the one added as the first source), the secondary data sources will have orange tick marks. Primary data source restricts the value from secondary sources. Only values that are corresponding to the primary sources are allowed, which is similar to left join.
Advantages of Data Blending in Tableau
Data blending is far easier and simpler when compared to traditional relationships and joins. The primary advantages of using data blending in Tableau is:
- It helps you in informed decision making with deeper intelligence on data.
- It provides an accurate aggregate of the data from multiple sources, even for the published sources.
- It drives your business timely with its compare and contrast view of the display.
Limitations of Data Blending in Tableau
Despite being advantageous in many ways, data blending in Tableau has a few limitations too:
- Non-additive aggregates like MEDIAN, COUNT and RAWSQLAGG have data blending issues.
- Publishing the blended data source is complicated. You need to publish each data source and then blend the published data source together.
- Secondary data sources are always calculated and aggregated.
- Cube data sources must be the primary data source, always.
How to Become a Pro in Tableau
Tableau is a very helpful tool in Data Science. To start a career in Data Science, get a certified degree in Tableau. upGrad offers many courses from certification to Master of Science in Data Science, PG Diploma in Data Science is a Diploma course that is offered with the IIIT Bangalore certification. Besides, you get an alumni status in IIIT Bangalore.
Become a most wanted Tableau professional, as upGrad offers placement opportunities upon completion of course. upGrad courses are available in easy EMI pay facilities to help students. All you have to do is register yourself in the course and become a certified Data Science professional.