How to Architect your Data Platform for Success

on YouTube ↗19m

" summary

Ten practical rules and concrete tool choices for Azure data platforms: start with Cloud Adoption Framework and Enterprise Scale landing zones deployed via Bicep/Terraform; decide NFRs up front (security, cost, latency, cross‑region recovery) to pick data‑warehouse vs data lakehouse; enforce metadata‑driven ingestion and code generation with Data Factory, Databricks Delta Live Tables or WhereScape/YETTL; automate CI/CD and tests with Azure Pipelines, pytest/Great Expectations; monitor via Log Analytics and design for staged MVPs and ops.

AI-written summary · about

" chapters (10)

1. 0:00Introduction and foundation
2. 1:53Building a strong foundation
3. 3:34Non-functional requirements
4. 5:52Planning for the future
5. 8:18Standardization and patterns
6. 10:30Automating the lifecycle
7. 12:47Skills and training
8. 14:04Defining the use case
9. 15:28Testing and learning
10. 16:55Monitoring and operations

" related talks

• 50mBest practices for implementing a modern data architecture with AzureElvis D'Souza, Raheel Retiwalla · Global Summer 2020 Azure Data Fest 2020
• 21mScalable Data Management and AnalyticsMike Boswell · All Around Azure | Unlocked: Cloud Scale Analytics
• 51mIntroduction to Azure Data PlatformJavier Villegas · AzConf 2020
• 55mDesigning performant and scalable data lakesRukmani Gopalan · SQLBits 2020
• 21mHow Not to Build a Data Platform Lessons from Failure to SuccessDanny Kruge · DevOpsDays Amsterdam 2025
• 30mFive Secrets to Enterprise Data SuccessPete Cooney · Data Summit 2025
• 22mA Microsoft Hybrid Approach to Data Mesh and Data FabricEmerson Gatchalian · All Around Azure | Unlocked: Cloud Scale Analytics
• 54mBehind the Hype - Architecture Trends in DataSimon Whiteley · SQLBits 2024