Innovative Tableau

Chapter 50. How to Deduplicate Joined Rows

There are always problem-solving brainstorms at our Tableau training events, and sometimes the solutions are so relevant for all Tableau users that I want to share them on a larger scale. In one such case, an attendee was trying to solve the business problem of currency conversion. This person worked for a global company and needed to join a dataset containing monthly exchange rates to their primary data source.

Joins in Tableau are a powerful way to add new dimensions and measures to your analysis, but without a good understanding of how they affect your dataset, you will often end up with inflated numbers. This chapter shares the challenge with joining multiple data sources and several solutions to ensure that you are getting accurate answers—even when joining on multiple dimensions (e.g., country and month).

The Challenge of Working with Joined Data Sources in Tableau

My favorite way to use joins in Tableau is to add fields to my analysis when my primary table and the table containing the new fields have at least one dimension in common. For example, suppose that I want to add a column from the Returns table to the Orders table of the Sample – Superstore dataset. The join would look like this in Tableau Desktop:

Because both tables contain the Order ID dimension, left joining the Returns table to the Orders table will add the new Returned ...