I agree to the Privacy Statement and to the handling of my personal information. By submitting this form, you confirm that you agree to the storing and processing of your personal data by Salesforce as described in the Privacy Statement. By submitting this form, you acknowledge and agree that your personal data may be transferred to, stored, and processed on servers located outside of the People's Republic of China and that your personal data will be processed by Salesforce in accordance with the Privacy Statement. If your data is now fully prepped and ready for analysis, simply add an output step and run the flow to generate the new data set.īy registering, you confirm that you agree to the processing of your personal data by Salesforce as described in the Privacy Statement. Note: In the image below, it doesn’t add up correctly because there is a lot more data which doesn’t appear in the screenshot. The sum of sales is the same for each record for a given country. Every country has their record-level sales in one column and the sum of all sales for that country in a second column. If we look at the data grid in Tableau Prep, we can now see something similar to the initial table on the top of this post. If these numbers are different, it is an indication that something went wrong. You will also notice that the total number of records in the full data set equals the join result we didn’t filter anything or change the level of detail for our main data set, so this is what we want to see. Tableau Prep should detect that you want to join on Country (after all, it’s the only dimension in your second data set). If you look in the configuration, you will see something similar to the screenshot below. In this case, drag your Aggregate step down to your first step until you see the orange drop areas and release it on top of “New Join” ( NOT New Union). It is tempting to click on the little “+” next to either of the steps and add a join, but Tableau Prep has a nice little feature where you can drag and drop elements to connect them. Now we need to bring the two steps together again. įor those just starting out with LOD expressions, I recommend Andy Kriebel’s post around FIXED Level of Detail expressions in a plain English sentence. In Tableau Desktop, the calculation would be written as. The Level of Detail expression (Sales per Country) provides the total sales for a given country across every row-so we see that the US has a total sales number of 150, whether we're looking at the row for 100 or 50. Both the US and Germany have multiple rows of sales information. Using Level of Detail expressions allows you to perform analysis and create visualizations outside of the level of detail in the view-like if you want to compare per-month sales with your overall sales.Īs an example, the table below contains sales information for three countries. If you're looking at monthly sales per country, your LOD is month and country. For example, if you're looking at monthly sales, your LOD is month. The level of detail in your analysis is usually determined by the structure of the visualization. Level of Detail (LOD) expressions allow you to analyze data and answer questions involving multiple levels of granularity. Reference Materials Toggle sub-navigation.Teams and Organizations Toggle sub-navigation.Plans and Pricing Toggle sub-navigation.
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