Working with several consulting clients, what best practices have emerged? Architecting enterprise scale projects, developing data engineering solutions; designing lakehouses, warehouses and large semantic models at-scale, let's talk about what we have learned - from our experience and the industry at large?
Fabric is amazing and will only improve but what gotchas, pitfalls and mistakes should you prepared to avoid?

How can you estimate workloads and plan for capacity? Should you use pipelines, notebooks or dataflows? How should you implement a medallion architecture using lakehouses or warehouses? What's the right option to manage version control, release control and DevOps? What about data governance, security and data quality control?

Learn from the experience of many others to get started on the right foot and make sure our organization is prepared and ready for success.