Posts

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An even faster way to generate realistic sample data for Salesforce

A couple of weeks ago, I shared my workflow for generating volunteer data using Snowfakery to build the structure, CumulusCI to extract it to SQL, and ChatGPT to make it realistic. That approach worked, but I’ve since made some significant improvements:

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How I built semi-realistic sample volunteer data for Nonprofit Cloud

NEW AND IMPROVED! I’ve made significant updates to this process. The page you’re viewing is the original post, which I’m leaving up for anyone who comes here first, but please refer to this one instead! Realistic volunteer data makes learning Nonprofit Cloud so much easier, but generating that data from scratch can be painfully time-consuming. I ended up using a process that uses Snowfakery, SQL, and ChatGPT together to make the process faster, easier, much more fun, and done in an afternoon.

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Start with NPC from scratch (orgs)

Forgive me for the terrible pun. I can’t resist. One of the challenges of learning (or teaching!) the new Salesforce Nonprofit Cloud is that the best way to understand it is to get your hands on it. Trial orgs are helpful, but they’re fixed snapshots - and once you’ve made a mess of one, you can’t easily rewind and start fresh.