What is Great Expectations?

Great Expectations (GX) is an open-source data quality framework. You declare Expectations (rules about a batch of data), validate batches against them, and get human-readable reports called Data Docs.

Mental model

batch of data (table / file / query)
        |
        v
  Expectation Suite  (rules)
        |
        v
  Validation Result  (pass/fail + metrics)
        |
        v
  Data Docs / alerts / CI gate

Example expectations (conceptual)

• expect_column_values_to_not_be_null on order_id
• expect_column_values_to_be_unique on order_id
• expect_column_values_to_be_between on amount (min=0)
• expect_column_values_to_be_in_set on status
• expect_table_row_count_to_be_between for volume sanity

Where it sits

• After load, before publishing curated tables
• In CI against sample fixtures
• As a scheduled checkpoint on warehouse tables

vs dbt tests

dbt tests live next to SQL models and are warehouse-native. GX is richer for profiling, docs, and multi-source batches (files, Spark, DBs). Many stacks use both.

Interview tip: "GX = declarative expectations + validation + docs." Name 2-3 expectation types and say it gates bad data before consumers see it.