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Category: Warehousing

Star Schemas and Keys

Published 2025-10-27 by Kevin Feasel

Chris Barber provides a primer on the types of keys that are critical for a star schema:

Keys are a core component of star schema modelling; relationships between tables are built using the keys. This article covers:

  1. The main key types
  2. Star Schema diagrams
  3. Best practices when using Keys

An understanding of keys become increasingly important with more complex solutions. Not only do you need to understand them from a modelling perspective, but a common vernacular is required to communicate with team members.

It’s easier to think of the keys Chris describes in two separate classes rather than four unique items. Surrogate and natural keys are descriptors of a primary key (or any other unique/alternate key), after all.

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Resolving Write Conflicts in Microsoft Fabric Data Warehouse

Published 2025-10-10 by Kevin Feasel

Twinkle Cyril has a conflict:

Fabric Data Warehouse (DW) supports ACID-compliant transactions using standard T-SQL (BEGIN TRANSACTION, COMMIT, ROLLBACK) and uses Snapshot Isolation (SI) as its exclusive concurrency control model. All operations within a transaction are treated atomically—either all succeed or all fail. This ensures that each transaction operates on a consistent snapshot of the data as it existed at the start of the transaction, which means.

Read on to see what this means, as well as what happens when multiple writers interfere with one another and how to avoid these sorts of issues. My Kimball-coded brain says that, if you have a data warehouse, you should have one data loading process. In that case, it’s not easy for the single data loading process to get tripped up on its own.

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Locks in Microsoft Fabric Data Warehouse

Published 2025-10-09 by Kevin Feasel

Twinkle Cyril enumerates the lock types in Fabric Data Warehouse:

Fabric DW supports ACID-compliant transactions using standard T-SQL (BEGIN TRANSACTION, COMMIT, ROLLBACK) and enforces snapshot isolation across all operations. Locks in Fabric Data Warehouse are used to manage concurrent access to metadata and data, especially during DDL operations. Here’s how locking works:

Click through for a chart. The locking policy is a lot simpler than what we see in SQL Server and you can see a description of the pros and cons of that simpler approach.

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Tag-Based Masking in Snowflake

Published 2025-10-01 by Kevin Feasel

Kevin Wilkie gets tagging:

If you’ve followed our site for a while, you would have seen in a previous post how powerful tag-based masking policies are in Snowflake. They let you enforce consistent data masking rules across columns without constantly rewriting logic. But Snowflake hasn’t stopped there—recent enhancements now make it even easier to classify, tag, and mask data at scale. In this post, we’ll recap the essentials of tag-based masking, highlight the new functionality, and share some practical tips for rolling it out in your environment.

Kevin has a new blog theme and everything.

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Contrasting Microsoft Fabric, Databricks, and Snowflake

Published 2025-09-24 by Kevin Feasel

Ron L’Esteve builds a comparison chart:

Databricks and Microsoft Fabric are two of the most innovative Unified Data and Analytics intelligence platforms available on the market today. While similar, each brings their own advantages and limitations. Snowflake joins these two powerhouses when data warehouse decisioning comes into play. Sometimes it is challenging to decide which one to pick for your organization’s needs. This tip will help with uncovering when to choose Databricks vs Fabric vs Snowflake.

When it comes to Spark performance, Databricks is always going to win—they keep most of their optimizations to themselves, so anyone starting from open-source Spark is at a disadvantage. Otherwise, it’s a bit of a slugfest between Fabric and Databricks. At the end, Ron also brings in Snowflake, focusing on the data warehousing side of things for that three-way comparison. I don’t think there’s a clear winner among the three, and on net, that’s probably a good thing, as it forces the groups to continue competing.

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Microsoft Fabric Data Warehouse July 2025 Recap

Published 2025-08-06 by Kevin Feasel

Charles Webb lays out some updates:

Welcome to What’s New in Fabric Warehouse, where we’ll spotlight our work improving quality, delivering major performance enhancements, boosting developer productivity, and our continuous investments in security. Whether you’re migrating from Synapse, optimizing your workloads, writing SQL in VS Code, or exploring new APIs, this roundup has something for every data professional. With quality and experience at the forefront, we’ve summarized and highlighted key improvements we think you’ll love, organized into three sections:

  1. What’s New
  2. Docs Updates
  3. Roadmap Updates

Read on for that update.

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Building a Snowflake Dashboard that Uses Filters

Published 2025-07-30 by Kevin Feasel

Kevin Wilkie does a bit of filtering:

Snowflake Dashboards can do a lot more than just show pretty numbers. Today, let’s focus on something that every data pro eventually has to deal with—filters that make navigating your dashboards less painful, especially when it comes to everyone’s favorite task: AUDITING.

Ah yes, auditing—because nothing says “data dream job” like tracing permissions. Whether it’s quarterly compliance checks or a sudden request from an overly curious auditor, somebody, at some point, will ask, “Who has access to what in Snowflake?” So let’s make that answer easy to deliver.

Click through for the process, using the development of a permissions auditing dashboard as the example.

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Result Set Chaining in Snowflake

Published 2025-07-17 by Kevin Feasel

Kevin Wilkie tries out a new operator:

In a recent Snowflake release, a slick new operator quietly entered the scene: ->>. This little guy can make certain query workflows both more readable and more efficient—especially when you’re dealing with multi-step commands like SHOW, LIST, or DESCRIBE.

Click through to see how it works. Seems that this operator has some pretty strict limitations, but for certain use cases, it’s quite nice.

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Writing Back to a Fabric Data Warehouse via UDF

Published 2025-07-08 by Kevin Feasel

Jon Vöge continues a series on write-back options into Microsoft Fabric:

In that article, we took advantage of some of the built-in sample code from the User Data Function editor, as well as some great code examples from Sujata: Example User data functions for Translytical task flows · GitHub

The problem? All of these samples use SQL Databases in Fabric as the backend item.

Jon switches this from a SQL database into a Fabric Data Warehouse, and notes some of the challenges along the way.

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