Best Practices for Standardizing Client Data

Question

Hi Alteryx Community,

I’m kicking off a new use tax project and would love to get your thoughts on how best to structure it in Alteryx.

Project Context:

For each new client, our team receives data files with varying formats. The first step in our workflow is to transform client data into a standardized column template (see attached Excel file for the headers we plan to use). This template will then feed into downstream use tax analysis.

Initial Approach:

My current thought is: Each time we onboard a new client, the team will analyze the client’s raw data file. They’ll then map each column from the client file to the corresponding standardized template column in our Excel file. Once mapped, we’ll run an Alteryx workflow to restructure the data into the standardized template format.

Open Questions:

Is there a more scalable or automated way to do the column mapping step across different clients? Has anyone built something similar (e.g., using Alteryx macros or a mapping table approach)? Are there recommended best practices for maintaining flexibility while still enforcing a standardized structure?

Would really appreciate any ideas, lessons learned, or examples from your own projects. Thanks in advance!

Standard Headers List.xlsx

fnfunkin · Answer

I’ve worked on similar projects in Alteryx, and using a mapping table can really streamline the column standardization process across multiple clients. You can create a master Excel sheet with client-specific column names mapped to your standard headers and feed that into a dynamic macro, which automatically restructures incoming files. It takes a bit of setup upfront, but it saves a ton of repetitive manual work later.

dreldrel · Answer

I quite often use a reference table to help me achieve a similar task. There other way you can ask your users to map the fields on the analytics app, so you wont need a reference table in this case

apathetichell · Answer

Hey --- this is a fairly normal process in data modelling/data engineering. My go-to  on this is a spreadsheet which contains mapping information --- (file type/client/column name) and which maps via dynamic rename/join/whatever to create the naming context which I need downstream for processing. My downstream processing (ie your core worfklow) becomes a batch macro --- and in my outerworkflow/macros which sit above that --- I'd do my column name mapping. This may include minor prep (case/trimming white space) but ideally it should have master list of client/filetype schema -> workflow required schema. This isn't really an Alteryx problem per se --- more of a general data model issue --- and it's something which Alteryx is not worse at than most systems (I'd posit it's actualy something Alteryx is quite good at).