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What does Great Expectations do?

Tool: Great Expectations

The Tech: Data Quality Testing

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Their Pitch

Everything you need to trust your data.

Our Take

It's unit testing for your data - catches bad numbers before they break your reports or make your CEO ask uncomfortable questions.

Deep Dive & Reality Check

Used For

  • +**Your sales dashboard shows negative revenue and your CEO panicked** → Catches impossible values before they hit executive reports
  • +**Spending 2 hours every Monday hunting for data errors in reports** → Automated checks run overnight, flag problems before anyone sees them
  • +**Pipeline crashes when someone uploads a file with extra columns** → Handles schema changes gracefully instead of breaking everything
  • +200+ pre-built rules for common problems - no coding "expect customer_id to never be empty" from scratch
  • +Auto-suggests 10-50 data quality checks by scanning your actual data patterns

Best For

  • >Your weekly reports keep having obvious errors and your boss is asking questions
  • >Data pipelines break at 3am and you're tired of weekend emergency fixes
  • >You're manually spot-checking spreadsheets for hours because you don't trust the numbers

Not For

  • -Small teams working with simple spreadsheets - this is overkill for basic CSV validation
  • -Non-technical teams without Python skills - the free version requires actual coding
  • -Solo analysts who just need to clean data once - you'll spend more time setting it up than fixing manually

Pairs With

  • *Airflow (runs your data quality checks as part of the pipeline before loading to warehouse)
  • *Snowflake (where your clean data actually lives after passing validation)
  • *dbt (transforms data after GX confirms it's not garbage)
  • *Slack (where you get alerts when validation fails at 2am)
  • *Pandas (for the actual data processing that GX is checking)
  • *Tableau (displays the data you now trust because GX validated it)
  • *AWS S3 (stores the validation results and metadata)

The Catch

  • !The free version requires Python coding and manual setup - no pretty dashboards without paying
  • !Cloud pricing isn't public, which usually means "expensive enough that we don't want to scare you away upfront"
  • !You'll need someone to maintain the rules as your data changes, or they'll become useless noise

Bottom Line

Like spell-check for your data pipeline - catches the typos before they become disasters.