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So, how does one create synthetic relational data? Do you just crank out a list of synthetic customers, assign IDs, create between 0 and 3 synthetic orders per

So, how does one create synthetic relational data? Do you just crank out a list of synthetic customers, assign IDs, create between 0 and 3 synthetic orders per person, and between 0 and 3 order line entries per order?

blopker 2y ago
This is somewhat framework dependent, but factory_boy supports connecting factories together via SubFactory. There's a real-world example I'm building [0]. See where "author = SubFactory(UserFactory)". I'd imagine there are similar ways to do this for Rails and others too. [0]: https://github.com/totem-technologies/totem-server/blob/main/totem/circles/tests/factories.py https://github.com/totem-technologies/totem-server/blob/main...
edrenova 2y ago
we're actually working on this right, can see the PR here -> https://github.com/nucleuscloud/neosync/pull/1832/files https://github.com/nucleuscloud/neosync/pull/1832/files it's a combination of creating a random number of records for foreign keys i.e 1 customer - create between 2 and 5 transctions. Working on giving you control over that, and handling referential integrity with table constraints (foreign keys, unique constraints, etc.) ML based approaches typically are not very good at this and struggle with handling things like referential integrity. So a more "procedural" or imperative way is slightly better. The ideal is a combination of both.
beeboobaa3 2y ago
Pretty much, yeah. Use normal distribution so you can get some outliers.