This process is understandably more work, as two different aggregations have to occur, and much more data ends up being processed at once because the VLOOKUP occurred before the aggregation. take the max of Sales by Country and the sum of Sales Quota by Country. Use the above table to aggregate Sales and Sales Quota by Country. Join Sales and Sales Quota tables on common fields (Country)Ģ.

The steps in an ordinary join would follow the process below: 1. In order to get the desired comparison, we would have to aggregate the data by summing the Sales column by Country, and grabbing the max (or min) Sales Quota by Country. Had we performed a VLOOKUP on the Sales data before aggregating by Country, we would likely have multiple Sales records for each Country (one row for each Sales Agent) with the Sales Quota next to each record that repeats itself for the same countries. This process of joining data sources post-aggregation is referred to as data blending in Tableau. Therefore, the “join” to the second data source was done post-aggregation. This concept is referred to as a post-aggregate join, as the VLOOKUP to the sales quota spreadsheet did not occur until after the sales data was already aggregated by country. Perform a vlookup from Sales to Sales Quota on Country Sales Quota by Country, you would likely first aggregate the Sales Quota data to be summed by Country, then perform a VLOOKUP to the Sales Quota table on each Country in the Sales table to grab the total Sales Quota for that Country, and place the result next to the Sales column for the corresponding Country. If you wanted to do a side by side comparison of Sales vs. Notice how these two tables are at different granularities, as the Sales table lacks a Sales Agent dimension. Suppose you have data in two different Excel spreadsheets: the first sheet contains a table of data on sales broken out by country, the second sheet contains a table of sales quotas for sales agents, split out by the sales agent name and his or her assigned country. To answer this question, consider the following example, which is the equivalent of a data blend in Tableau but is executed within the familiar environment of Excel. You may ask, “How is blending different from a regular join?”

Since data blending is a fairly advanced concept, this article explains the concept of data blending at a basic level using Excel as an example. Even to an experienced SQL query writer, the mechanics of blending data, rather than joining it, can be difficult to understand upon initial exposure.

Tableau prep join