ETL Actions translated to MySQL Transforms

If it doesn't already exist (haven't found anything to indicate it does), consideration for Domo Support or even the Dojo Community to put together a detailed, comprehensive resource guide that offers simple/basic examples as well as more complex ones of what a MySQL transform would look like based on a specific ETL action, i.e. "Group By", or aggregate rows, written in MySQL utilizing a sample dataset throughout the entire dataflow process.


The simplicity of Magic ETL is great for a lot of things, but there are a lot of things that seem to be more difficult than they should be or simply not available to do in this environment, and a recent issue with time conversion PRIOR to changing a Date/Time field to Date only is proving to be a very involved, cumbersome process in the ETL environment.


EXAMPLE: Domo Support got back to us with a reason of why the dates were converting incorrectly, i.e. depending on UTC time of source data, it would count something either +1/-1 day from what it actually was. We were told to add Convert_tz ()to the dataflow to correct this before the Date() conversion, but can't find a way to do this in ETL.


After researching for some time, we found a Dojo thread ( which all totaled is 30+ steps to complete, and the solution from Domo Support's response was simply as adding a single transform!


I can only speak for myself, but my guess is that there others who are newer to Domo and Data Analysis/Databases/MySQL would probably want to learn how to write queries/transforms and create dataflows in MySQL as opposed to ETL, but so much of the Domo documentation has very basic examples and nothing to help understand the actions in ETL as they would be in MySQL.

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  • DaniBoy



    Thanks @John-Peddle!


    I will bring this to the Domo Education team to see what we can do to streamline this.

    Great feedback!



    CC @JeriLarsen

    Dani aka "Mr.Dojo"

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  • @John-Peddle - That's an great point raised. Individuals new to DOMO will face difficulty in understanding the entire DataFlow and also their is an every chance that Data might not be running as per the designed mode. Adding the available options in ETL will increase the DataFlow which can be avoided by giving a simpler options to get the desired output. 

    Also on Education or Guide for ETL & SQL can be increased by adding up of relevant examples raised in the Idea Exchange where the DOMO technical team has reviewed an implemented the same for the users. Providing an practical solution is tough but giving a thread access to actual query in the guide will give more scope of learning to the new users. 


    Thank You DOMO team for all the support, Cheers to all you Smiley Happy

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