Customer Data Platforms (CDPs) promise better engagement, higher operational efficiency, and revenue growth by centralizing and streamlining access to customer data. However, consolidating sensitive information from a variety of sources creates complex challenges around data governance, security, and privacy. We’ve studied, built, and managed data protection strategies at some of the world’s biggest retailers. We’ll showcase business requirements, common architectural components, and best practices to deploy data protection solutions at scale, protecting billions of sensitive records across regions and countries. Learn how a data vault pattern with granular, policy-based access control and monitoring can improve organizational privacy posture and help meet regulatory requirements (e.g., GDPR, CCPA, e-Privacy). Walk away with a clear framework to deploy such architecture and knowledge of real-world issues, performance optimizations, and design trade-offs

In this session, we will explore the Australian Red Cross Lifeblood's approach to synchronizing an Azure SQL Datavault 2.0 (DV2.0) implementation with Unity Catalog (UC) using Lakeflow Connect. Lifeblood's DV2.0 data warehouse, which includes raw vault (RV) and business vault (BV) tables, as well as information marts defined as views, required a multi-step process to achieve data/business logic sync with UC. This involved using Lakeflow Connect to ingest RV and BV data, followed by a custom process utilizing JDBC to ingest view definitions, and the automated/manual conversion of T-SQL to Databricks SQL views, with Lakehouse Monitoring for validation. In this talk, we will share our journey, the design decisions we made, and how the resulting solution now supports analytics workloads, analysts, and data scientists at Lifeblood.