For medium-volume, semi-structured lists: We doubled down on Google Sheets / Microsoft Excel advanced functions. We ran workshops on REGEXEXTRACT (Google Sheets), TEXTBEFORE, TEXTAFTER, XLOOKUP, and FILTER. The ability to extract patterns using regular expressions was a game-changer for many of our lists.
For high-volume, repetitive tasks: We began exploring Python with Pandas. Our developers set up a basic script that could ingest a text file, apply a series of regex patterns to extract fields, and output a CSV.
For input standardization: We leveraged Google Forms for new customer brother cell phone list feedback collection, forcing structured input from the start.
Developing Input Templates (Days 9-10):
We created simple markdown or text templates for internal teams when submitting lists. For bug reports, for instance, we provided a template like:
Bug Title: [Short Description]
Impact: [High/Medium/Low]
Steps to Reproduce:
1. ...
2. ...
Expected Result: [What should happen]
Actual Result: [What happened]
Environment: [Browser/OS/Device]
This vastly improved the consistency of the raw input, making the transformation much easier.
Week 3: Building Transformation Routines and Training
Goal: Develop robust transformation workflows for the prioritized list types and train the relevant teams.
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