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My boss wants me to export the raw 'Sales' table from a Power BI dataset to a single csv file. He does not want me to aggregate this table to reduce the number of rows.

I am familiar with Power BI 'Run a query against a dataset' step. However, because 'Sales' is direct query and has over 1,000,000 rows, my flow runs into an error at the 'Run a query against a dataset' step.

I am considering writing multiple 'Run a query against a dataset' steps, filtering the Sales table by month and year to keep each query from having 1,000,000 rows. For example, I would write 'Run a query against a dataset for month 1 of year 2024,' 'Run a query against a dataset for month 2 of year 2024,' etc. Is there a way that I could union these queries together? I am familiar with the DAX UNION() function, remember that I am getting an error message when I try to export the raw direct query Sales table because it is over 1,000,000 rows. That is why I would like to use Power Automate to union multiple 'Run a query against a dataset' steps together into a single csv.

I am aware that after this, I will need to apply Curbal's instructions for looping through a csv to export the more than 1,000,000 rows. My main trouble is figuring out how to union the output from the 'Run a query against a dataset' steps so it is one csv that can be looped through per Curbal's instructions.

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