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Author: Kevin Feasel

A Primer on Data Analysis with Python and SQL Server

Published 2026-01-09 by Kevin Feasel

Eduardo Pivaral shows off a few examples of analysis techniques:

With the rise of cloud, automation and managed services, the role of the Database Administrator has pivoted towards Data Engineering.  The focus is to maintain, secure, and cleanse data in order for data analysis and decision making by the business.

How can we start using modern data analysis tools with our current SQL Server infrastructure? Further, how can we start providing end users and decision makers with important insights about our data, without spending extra money on enterprise data analysis tools?

Click through for demonstrations of k-means clustering for discerning categorical groups of data, simple demand forecasting, and generating customer segments.

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Learning Fabric REST APIs via FUAM

Published 2026-01-09 by Kevin Feasel

Kristina Mishra digs into the Fabric Unified Admin Monitoring tool:

Recently a colleague of mine was inquiring about creating a service principal to use with a Microsoft Fabric Rest APIs proof of concept project we were wanting him to develop for some governance and automation. Since he was still in the research phase, I told him we already had one he could use and did a brief demo on how we use it with FUAM (Fabric Unified Admin Monitoring tool). It occurred to me that others may find this a useful way to learn how to use Fabric or PBI Rest APIs. If you are also fairly new to using pipelines and notebooks in Fabric, then you can get the added bonus of learning through an already created, well-designed and active live Fabric project in your own enviroment. If you do not have FUAM installed in a Fabric capacity, or do not have permissions to see the items in the FUAM workspace, or have no intention/ability do change either of those blockers, then you can stop reading here. Unless you are just generally curious – then feel free to read-on. Or not. You do what works for you.

I personally recommend reading on. It’s kind of a thing I do here.

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Checking if a Microsoft Fabric Data Pipeline is Running

Published 2026-01-09 by Kevin Feasel

Jon Lunn checks the status of a data pipeline:

How do you check if a pipeline is running, not from the monitor, but from your Data Pipelines?

Maybe you’re like me and you have a  Data Pipeline process that needs to check if some other pipeline else is running. In my case I have to check if a process is running due to Delta tables liking you to have one process writing to them, otherwise you can get concurrency issues as two items are trying to update the same delta table metadata file.

Those tricky metadata items like the process to be exclusive. It’s not just a Delta table issue; this can happen with regular SQL databases tables. So you can use this for anything you want to stop a locking issue or have an exclusive access to an object or just don’t want a process to run while another is doing its thing. 

Read on to see how you can check the current status of a data pipeline from within a different data pipeline.

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A Primer on Fabric Real-Time Intelligence

Published 2026-01-09 by Kevin Feasel

Greg Low fills us in:

Let’s start with a simple idea. Real time intelligence (or RTI) is about shrinking the delay between when data is created and when you can act on it. In traditional systems, we’re often used to data being collected, stored, and only analyzed later, maybe overnight or even weekly. That’s fine for long term reporting, but it’s too slow for situations where immediate action matters.

Assume that I levy my standard complaint here about how “internet speed” is not real-time. But leaving that aside, Greg gives a few use cases for RTI, and I do think it’s a good part of the Microsoft Fabric platform.

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A Data Model for Git

Published 2026-01-09 by Kevin Feasel

Julia Evans updates the Git documentation:

After a while working on the documentation, we noticed that Git uses the terms “object”, “reference”, or “index” in its documentation a lot, but that it didn’t have a great explanation of what those terms mean or how they relate to other core concepts like “commit” and “branch”. So we wrote a new “data model” document!

You can read the data model here for now. I assume at some point (after the next release?) it’ll also be on the Git website.

Click through for the documentation as well as some more thoughts on Git documentation in general and contributing to Git.

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Notes on Axis Scale in Visuals

Published 2026-01-08 by Kevin Feasel

Amy Esselman keeps track of axis:

One of the most common pitfalls in data visualization is manipulating axis scales in ways that distort the story. A frequent example is the use of logarithmic scales where they are not appropriate.

Let’s walk through a case where this choice can mislead, even if unintentionally.

Amy has some good guidance on when you should use log scale, as well as a good example of a case where applying it incorrectly can lead to distorted results.

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Data Correlation Optimization and Cross-Database Data Leaks

Published 2026-01-08 by Kevin Feasel

Fabiano Amorim shows off a vulnerability:

This vulnerability involves restoring a database into a DBaaS and uses a “corrupted” internal view, effectively turning the engine’s own intelligence against itself.

The exploit is elegant in a disturbing way, since there’s no need for xp_cmdshell, CLR, or any of the usual suspects – just a carefully crafted .bak file and SQL Server’s unwavering belief in its own metadata integrity.

The payload hides where no DBA would look – system tables that are supposed to be immutable – and executes under a context that was never meant to be controllable by the user.

This is not a misconfiguration or a permission trick – it’s a design flaw rooted in how the SQL Server engine trusts its persisted metadata, and how that trust persists across the boundary between a user-managed instance and a cloud-managed environment.

This kind of fits in the “Neat, but not incredibly practical” bucket for me, so I can understand Microsoft marking this as a low-risk security issue.

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Parameter Sensitivity Training

Published 2026-01-08 by Kevin Feasel

Erik Darling finally gets HR involved. The sad and/or clever part is that I wrote that line before Erik made the joke.

This is Part 1 in a set of videos covering Erik’s talk for PASS Data Community Summit in 2025. As is usual, Erik’s videos are worth watching even though he doesn’t give me even one paragraph that I can copy and include as a graf here, meaning that I need to type in more in order to make it so that any RSS feed reader connected to Curated SQL doesn’t panic and force you to open the post because it’s too short, and thus causing me to write even longer run-on sentences than I normally would write, though I typically indulge myself in run-on sentences so the blame isn’t 100% on Erik; in short, Erik allows me to use semi-colons more often, and I appreciate it.

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Configuring a Point-to-Site VPN in Azure

Published 2026-01-08 by Kevin Feasel

Aleksey Vitsko wants access to private endpoints:

You have resources in Azure (including, but not limited to, Azure SQL), and you have a task at hand to eradicate usage of public endpoints. Security requirements are to start communicating with resources, such as database servers through encrypted VPN channels.

This is the “people in my office will use this” VPN, whereas Azure also has a Point-to-Point VPN for individuals and remote workers.

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Using Fabric Cost Analysis

Published 2026-01-08 by Kevin Feasel

James Serra tries out a tool:

Enter Fabric Cost Analysis (FCA) – a free, open-source solution available to everyone on a Microsoft GitHub repository, designed to shine a light on all your Microsoft Fabric costs. FCA was developed by a multidisciplinary team (Cedric Dupui, Manel Omani, Antoine Richet, and led by Romain Casteres) with expertise spanning FinOps, Data, and Go-To-Market, with a clear goal: turn a major adoption barrier into a strategic lever for growth.

Conceived directly from customer questions, FCA answers the things people actually want to know: What are we really paying for? What’s included? Where are the optimization opportunities? It doesn’t just track costs—it builds trust, helps organizations explain spend internally, and ultimately accelerates Fabric adoption.

Read on to see what it includes and how it works.

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