Shifting Data Quality Left with Data Contracts - Case Study with Make

Make, an AI automation platform, tackled its data quality challenges by adopting Soda v4 and implementing data contracts to improve data governance across its workflows. Initially, Make faced issues with data governance, including unclear ownership, lack of visibility into downstream dependencies, and recurring data quality problems that only surfaced in reports. By embedding data contracts at both the ingestion and transformation layers of their Airflow pipelines, Make shifted data testing upstream, enabling the detection of schema breaks, null violations, duplicate keys, and business logic errors at the source. The integration of Soda's programmatic checks within Airflow allowed for automated data quality evaluations, dramatically reducing reactive interruptions and fostering a shared understanding of data ownership and dependencies among teams. This proactive approach has automated manual processes such as the monthly ARR reconciliation, enabled non-technical teams to gain visibility into data health through the Soda Cloud UI, and spurred organizational conversations about data changes' impacts. As Make continues to expand its use of data contracts, the company aims to enhance data literacy and foster a culture where teams independently manage and understand their data quality issues.