TL;DR
- Monday.com deployed a fully GDPR-compliant European data warehouse in under two weeks using Snowflake, Satori, and Terraform, demonstrating that speed and compliance can coexist with proper tooling and architecture.
- Modern data security requires three pillars: visibility into sensitive data locations and access patterns, fine-grained access control based on role and purpose, and comprehensive audit trails for compliance evidence.
- Infrastructure-as-code using Terraform enabled monday.com to create a unified model merging Snowflake and Satori objects, making permission management scalable and changes simple to implement across thousands of users.
- Organizations pursuing AI initiatives must first establish strong data governance foundations—quality, secure data with proper access control and visibility accelerates AI readiness rather than slowing it down.
This live edition of the STRIVE podcast, recorded at Commvault SHIFT 2025 in New York City, presents a compelling case study of how monday.com successfully deployed a fully GDPR-compliant data warehouse in Europe in under two weeks. The conversation features Asif Dromi from monday.com and Ben Herzberg, former Chief Scientist at Satori and now part of Commvault's Solutions Marketing Group, discussing the practical challenges and solutions involved in operationalizing data security at enterprise scale. Monday.com, described as a data-driven company from day one where data is not optional but essential, faced a significant challenge when they needed to support a new type of data subject to GDPR compliance requirements. The complexity stemmed from the need to ensure data residency in Europe while simultaneously enabling thousands of employees across multiple departments—analysts, developers, and leadership—to access only the data relevant to their specific roles. The solution involved building a separate European data warehouse using Snowflake, with Satori providing centralized permission management and access control. What made the implementation particularly elegant was the use of Terraform to create infrastructure-as-code, allowing the team to merge Snowflake and Satori objects into a unified model that could be managed, scaled, and modified efficiently. Ben Herzberg emphasizes that modern data security requires three fundamental capabilities: visibility into where sensitive data resides and who accesses it, fine-grained control over data access based on role and purpose, and comprehensive audit trails for compliance evidence. The discussion highlights that operationalizing data security—making it repeatable and scalable rather than treating it as a one-time setup—is essential for organizations pursuing AI initiatives, as quality, governed data forms the foundation for successful AI projects.
Chapters
0:00 - Introduction and Guest Introductions
1:05 - Monday.com's GDPR Compliance Challenge
4:13 - Common Data Security Challenges at Scale
6:12 - Building the European Data Warehouse Solution
8:44 - Operationalizing Data Security with Terraform
10:26 - AI Readiness and Data Governance Best Practices
11:56 - Advice for Data Engineers and Closing
Key Quotes
2:09 "Monday is a data-driven company from day one. And data for us is not an option. It's a must."
5:00 "Nowadays you want a company with thousands of employees. Thousands of employees need access to data. And you need to do it in a controlled way."
8:12 "And it works like magic. We're able to create new databases and all the relevant things in one place easily. It's scalable."
11:29 "We do it in less than two weeks. It was like everyone was shocked."
