All Number functions, except for MAX and MIN, are non-additive aggregates.” “Instead, the values have to be calculated individually.
“Non-additive aggregates are aggregate functions that produce results that cannot be aggregated along a dimension,” says Tableau. Tableau Data Blending Limitations: A Closer Lookĭata blending limitations often occur when working with “non-additive aggregates” like MEDIAN, RAWSQLAGG, and COUNTD. Use data blending when you have duplicate rows after combining data.Data blending is typically used when your data needs to be cleansed and your tables do not match up correctly after merging.For example, in a table with cities, you might have State, City, and ID, and in a table with sales, you might have many more fields. Data blending is granular independent: Since you get data from different sources, this data can have different levels of detail.See this article to familiarize yourself further with the joins in Tableau. Data blending works only as a left join operation and does not work with any other join types.Investigate your data sources for common data types: both data sources must have a field for linking tables (city or state ID in our example).Data blending is best used when you need to analyze data from different data sources: For example, you need to view sales by location – it can be the name of a state or city, and sales data stored in different tables, and to visualize data by city, then you need data blending.Each data source is queried independently and the results are aggregated to the appropriate level then visualized together.” Instead, data blending is a better method. If we were to join this data, some quota information would be duplicated for each transaction because joins are row-level. For example, you have transactional data in one source and quota data in another. “This is ideal when the data is at different levels of granularity. “Unlike joins, data blending keeps the data sources separate and simply displays their information together,” Tableau explains.
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