We’re all largely familiar with the common modern data warehouse pattern in the cloud, which essentially delivers a platform comprising a data lake (based on
Detecting And Anonymizing PII Data With Azure Synapse Analytics
This isn’t a deep technical post, but more of an attempt to increase awareness of a utility created by Microsoft’s Commercial Software Engineering (CSE) team
Change Data Capture Upsert Patterns With Azure Synapse Analytics and Databricks
Change Data Capture (Referred to as CDC for the rest of this article) is a common pattern used to capture change events from source databases
Cross Database Queries With Azure Synapse (Serverless)
I had a recent challenge from a customer that involved the need to join together datasets from different regions and present them as a unified
Putting the “T” into “ELT”
In my last blog post (From Warehouse To Lakehouse – ELT/ETL Design Patterns With Azure Data Services) I talked about the different patterns that exist
From Warehouse To Lakehouse – ELT/ETL Design Patterns With Azure Data Services
I like a good pattern. I also like a good framework. From a data perspective, nothing lends itself better to having both of these as
SQL Of The North 