The Misata blog
Practical writing on synthetic data, test data, and getting the numbers right in a data pipeline before real data exists.
· 3 min read
How to test a data pipeline before you have data
Known-answer testing: declare the metric your pipeline should produce, generate synthetic data that hits it exactly, then assert your transform returns that number. A test that can actually be wrong.
· 2 min read
Generate relational test data with foreign keys in Python
Faker fills one field at a time and leaves the foreign keys to you. Here is how to generate whole relational datasets in Python where every FK resolves and the totals reconcile, with a proof attached.
· 3 min read
The best MCP server for synthetic data generation
AI agents can design a schema but cannot guarantee the math. Misata's MCP server lets an agent generate relational datasets locally, with no API key, and returns a foreign-key integrity proof it can actually verify.