Beat methods to validate/test the output data with original data

I have built dataflows from customer input data in Asure data factory. We designed the Workflows which are built on Alteryx(another Etl tool) in Azure data factory .

Now testing the sample data is ok on both sides.

But how to validate the entire output of Alteryx and Azure to be matched/Validated. Is there any tool.

My output file format is CSV.

Is there any automation proceaa to validate all the rows of Alteryx outout and Azure Output so that i can be sure that i have built the right Dataflow logics.

You should be able to do verify the whole dataset through validate activity if thats what you want (that the dataset meets a certain criteria etc.):

https://learn.microsoft.com/en-us/azure/data-factory/control-flow-validation-activity

Dataset validation directly on Alteryx output is not supported, in which case you need to store the dataset somewhere that you just transformed in Alteryx like a blob store, then you can validate there. Validation activity usually supports file storage systems like datalake, (S)FTP, or a relational database.

You can also do this through dataflows but you need to store it somewhere, as ADF cannot store any files or data by itself. Once you have both datasets stored, you can for example do this through dataflows by self-joining the datasets, and creating hash values and comparing those values, there is a video like this:

https://www.youtube.com/watch?v=GACpvMjOJgE

And here is another post similar to yours:

https://learn.microsoft.com/en-us/answers/questions/856074/how-can-i-compare-source-data-(sql-server)-with-de

Later if you wanna do this going forward, you can use CDC.