On-Demand Recording
How McDonald's Deploys 1000s of Data Quality Checks Fast
How to Deploy Thousands of Checks in Under a Year, Without Developer Cycles
Share:
Access Free Recording
Fill out the form to get access.
After watching this recording, you'll understand...
- Why McDonald’s phased out their legacy Data Quality tools
- The benefits of using pushdown data quality checks, AI-powered anomaly detection, and incident alerts
- Best practices for scaling data quality checks in your own organization
Their Story
Why fixing data quality (fast) was critical for McDonald's
As one of the world’s largest fast-food chains, McDonald’s manages massive amounts of data for customers, sales, inventory, marketing, and more. And at that scale, ensuring the accuracy, reliability, and quality of all that data comes with a new set of complex challenges. Developing manual data quality checks with legacy tools was too time-consuming and resource-intensive, requiring developer support and data domain expertise. Ultimately, they struggled to scale their checks across their enterprise data pipelines.
Watch our on-demand recording, where you’ll hear from Matt Sandler, Senior Director of Data and Analytics at McDonald’s, teach you how they use the Lightup Deep Data Quality platform to deploy pushdown data quality checks in minutes, not months — without developer support.
Access Free Recording
Fill out the form to get access.
Find hidden bad data, across the modern data stack.
Get full visibility into enterprise data with Lightup’s modern Data Quality Monitoring solution.
