Non-additive aggregates from the secondary data source WorkaroundĪgain, try creating an extract of your data source. In order to use non-additive aggregates in the primary data source, the data source must originate from a relational database that allows temporary tables to be used. Non-additive aggregates from the primary data source Try using an extract of your multi-connection data source and this could solve the problem. WorkaroundĮxtracts-or saved subsets of data-support temporary tables. Temporary tables aren’t supported by multi-connection data sources that utilize live connections. There are non-additive aggregates from a multi-connection data source with a live connection As such, you cannot use blending with non-additive aggregates when using a published data source as your primary data source. If you are using Tableau 8.3 or earlier, Tableau Server won’t support temporary tables. If you are using Tableau 9.0 and later, you can try using MEDIAN and COUNTD with blending in a published primary data source. ![]() This can restrict what you do with non-additive aggregates. However, not all versions of Tableau Server support them. A published data source is the primary data sourceĬertain tables in SQL Server are temporary. ![]() Then, try using the LOD expression from the secondary data source. Remove all dimensions from the secondary data source and confirm that the linking field in the primary data source is in the view. According to Tableau, this error can also appear when using a LOD expression in a view with data blending. LOD expressions are used when running complex queries with multiple dimensions at the data source level. A Level of Detail (LOD) expression is being taken from the secondary data source “Cannot blend the secondary data source because one or more fields use an unsupported aggregation.” Causes and Workarounds for a Blending Limitation Errors 1. When this happens, you will see the following error message appear over the invalid fields: Under certain circumstances, these limitations can cause certain fields in the view to become invalid, according to Tableau. 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. This is a bit different from data joining, which involves combining related data from common fields. When blending data, you merge data from a secondary data source and display it alongside data from a primary data source in a view (i.e., a visualization). Occasionally when working in Tableau, you will have to perform a function called data blending, which involves combining data from different sources.
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