Pretty much the same SQL (except using People_Multiple instead of People),īut because of the record duplication, our resulting Sales aggregates are doubled. Only part of the problem-aggregations are also impacted by this data duplication.įor example, let’s create that bar chart showing Sales by Customer again. If you’re dealing with millions of records, thisĭuplication could prove to be a huge constraint. The result set is 19,988 records, as opposed to the 9,994 But, because there are two people for each region, each record in Orders When we use this in our data model, it executes a similar SQL statement as shownĪbove. Yourself, the connection information is available on the SQL for Tableau UsersĪs you can see, this table has two people for each region. Finally, these tests will be performed using my publicly-available Learn, feel free to check out my series on SQL for Tableau Users. If you do not have a SQL background and want to While I’ll be simplifying this SQL a bit for readability, I am assuming some Model is doing, we’re going to be looking at the SQL generated by Tableau. ![]() Second, in order to understand exactly what the data Interested in digging a bit deeper, you can also read The Tableau Data Model and Relationships, Part 1: Introducing New Data Modeling in Tableau. Of “relationships” and generally how they differ from joins. It will give you an overview of the new concept Video on How Relationships Differ from Joins. ![]() First, if you’re not yetįamiliar with the new data model, I’d suggest that you start by watching the short
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