DEEQU YOUR DATA

Unit-Test Quality for AWS Spark Pipelines

Trusted by engineers at Amazon, Airbnb, and Bukalapak

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AWS Partner 10K+ GitHub Stars Used in Production at Scale

Deequ → Spark Dashboard

70% of data pipelines fail due to quality issues.

Nulls, duplicates, schema drift — they kill ML models and dashboards.

Write data checks like unit tests:

Completeness > 99%
No duplicate IDs
Price between 0 and 10,000

Run on 1B+ rows in minutes with Spark.

See Full Tutorial


from pydeequ.checks import *
check = Check(spark, CheckLevel.Error, "Review Check")
result = check \
    .isComplete("review_id") \
    .isUnique("review_id") \
    .run()

Real-World Proof

Case Study: Bukalapak

Reduced bad data incidents by 70%
Automated quality gates in CI/CD
Saved 200+ engineer hours/month

Trusted at Scale

Amazon

Airbnb

XenonStack

[Your Client]

Services (Start Small)

Deequ Pipeline Audit

2-day review + custom check library

$2,500

PyDeequ + Glue Setup

Serverless DQ in 1 week

$7,500

Team Training

Hands-on Deequ & Spark DQ

$3,000/day

Get Started in 48 Hours

Free Resources (Lead Magnet)

PyDeequ in 10 Minutes (Video)

50 Deequ Constraints Cheat Sheet (PDF)

Glue Data Quality vs Deequ (Comparison)