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Day: September 25, 2026

A Medallion Architecture Primer

Andy Brownsword takes us through a concept:

Medallion architecture is the go-to for handling analytical data, particularly with the prominence of lakehouses in Databricks and Fabric.

Whilst the layers are well defined, their definitions don’t tell you where particular tasks belong. So here I wanted to present my view from a more practical perspective of what goes into each layer.

What I’ve found interesting is that, despite almost everyone agreeing on the rules of what goes where, you can easily get into debates with other data architects and lakehouse practitioners once you start asking concrete questions around specific datasets and specific levels of transformation. The edges between silver and gold get really fuzzy.

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Managing Resources via Azure Cloud Shell

Jordan Boich isn’t afraid of the command line:

As a DBA or any data professional, it is becoming more valuable and vital to have a well rounded understanding of your data estate and environment. However, sometimes it can be a bit cumbersome, especially when connecting to Azure resources via PowerShell. You have to fumble with authentication, connection cmdlets and more, which can be a bit discouraging to use at times.

There are some interesting and useful tools to help circumvent that overhead and manage your Azure resources. Azure Cloud Shell is a great quick tool to use if you want to have a lightweight, and easily accessible way to help manage and administer your Azure resources.

Read on to see how you can connect and some of the things you can do with it. You also get your choice of bash versus PowerShell.

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Clustering in Fabric Data Warehouse

Louis Davidson does some exploring:

Clustering is one of the data terms that could not have been created by a database design person. Why? Because it has multiple meanings. In PostgreSQL it means the same thing as an instance in SQL Server. In server architecture it means connecting multiple servers together to form a “single” unit of some form to protect against failure. Then it means an index that determines the physical storage of a table in some manner. This usage of the word means the former.

The weirdest part of using a Fabric Data Warehouse when you first try to look at a query is the lack of indexes. So (currently as of writing this is late 2026), you only have this one tool to affect your performance. The tool allows you to order the data physically in your files so query processing can be reduced when searching the physical file.

Read on for an introduction of how it works, with the caveat that Louis is about two pages ahead of most people in the book.

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Tracking Microsoft Fabric Capacity Operation Events

Gilbert Quevauvilliers stores some data:

This blog post will explain how to capture the data from real-time events for Fabric Operation Events and store the results in a Lakehouse.

My approach is to use a Python notebook to query Eventhouse.

The reason for this is the Python notebook runs very quickly and because it consumes very little Capacity Units, it is a very efficient way to store the Fabric Operational Events to be analyzed over a long period of time.

Read on for the instructions and the notebook that Gilbert used.

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Checking archive_mode on pgBackRest

Stefan Fercot shares some advice:

A recent question on the community channels described a difficult situation: a standby had been promoted with archive_mode=off, and restarting the new primary was something the team wanted to avoid. Could they enable archiving on a downstream standby and take a pgBackRest backup from there instead?

Their attempt failed with archive_mode must be enabled, even with archive-mode-check=n. Removing the checks from pgBackRest’s source code allowed their proof of concept to succeed, but was that enough to trust the approach?

My recommendation was to return to a supported configuration, either through a restart or a controlled switchover. But I wanted to take a closer look and see whether archive-mode-check=n might allow the standby-based approach.

Read on for that answer, as well as some of the issues you might run into.

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