One takeaway: don’t underestimate data ingestion and engineering concepts; I focused too much on KQL in my prep. I’ll personally go deeper into Databricks next, as Delta Lake + Databricks is still very common for core data engineering workloads on Azure today, even as Fabric continues to evolve. Thanks to the community and best of luck to everyone still preparing!

Preparing for the Microsoft Fabric Analytics Engineer certification has been nothing but an experience. The questions in the exams are entirely scenario based, requiring you to understand in depth how Microsoft analytical asses operate, together and in unison and testing your knowledge in DAX, SQL and a little bit of PySpark. I want to extend a thank you to the Skool community and to @Will Needham ’s DP:600 practice videos, it provides a lot of clarity on understanding a real world scenario. As I prepare for my DP:700, I am motivated to explore more on PySpark,SQL and KQL. I’m deeply interested in understanding how Microsoft Fabric manages real time data. Goodluck to those in preparation mode as-well!