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Downloadable csv as an Alteryx workflow input in three simple steps

This post was originally published on The Data School blog between 2018 and July 2025, before our program was renamed to MIP’s Analytics Career Accelerator. References throughout this article to “The Data School” or “DS” all refer to what is now MIP’s Analytics Career Accelerator. The program, its people, and its commitment to launching outstanding analytics careers remain the same – just under a new name.

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Most of the time an Alteryx workflow starts with an input tool set to ingest some file or stream data from a database. However, sometimes you would want to download a flat file from the Internet, probably from the URL calculated dynamically, to use it as one of the input datasets. The standard Input tool does not accept an URL as an input.

So, suppose, we need to download fresh data about COVID cases in NSW every time we run the workflow. The URL of the dataset is

https://data.nsw.gov.au/data/dataset/aefcde60-3b0c-4bc0-9af1-6fe652944ec2/resource/5d63b527-e2b8-4c42-ad6f-677f14433520/download/confirmed_cases_table1_location_agg.csv

Step 1. Enter the URL through text input (note: you can dynamically calculate/update it, if necessary, upstream).

Step2. Run the Download tool with this URL/URLs.

Now all your data is in one cell. Unlike the Input tool, the Download will not transform CSV into rows and columns automatically. Therefore…

Step3. First, use the Text-To-Columns tool with “n” as a separator and the “Split to Rows” option (I know, the tools is called “split to columns”, but…) 

You will get a table with rows separated (but all columns are still concatenated in one field). 

Step 4. Finally, use another Text-To-Columns tool to divide the columns on the “,” divider (with “Split to Columns” option). And do not forget to increase the number of the columns in the tool

Your job is effectively done here.

You can use the Dynamic rename to pull the column names from the first row, and apply the Select to remove unnecessary columns, but otherwise your data is ready for analysis.

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