factcat

Product analytics on the event model already in your warehouse. Your grain, your periods, your definitions.

Every other product analytics tool hard-codes entity = user, period = a calendar bucket, and retained = did any event. Real definitions violate all three:

from factcat import RetentionSpec, retention_sql

spec = RetentionSpec(
    table="analytics.fct_subscription_payments",
    entity="subscription_id",   # not the user
    entity_time="sub_start",
    event_time="paid_at",
    period_days=35,             # a billing cycle plus dunning, not a calendar bucket
    n_periods=12,
    retained="status = 'collected' AND within_period_offset <= 5",
)

print(retention_sql(spec, dialect="snowflake"))

retained is arbitrary SQL over any column in your table, plus the derived columns offset_days, period_index and within_period_offset.

Generates SQL and queries in place. No SDK, no ingestion, no copy of your data. Supports DuckDB, Postgres, BigQuery, Snowflake, Databricks, Spark, Trino, Presto, ClickHouse and Redshift.

Full documentation: https://github.com/gordonkjlee/factcat

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