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Category: Naming

Using a Naming Convention for Microsoft Fabric Items

Published 2025-02-19 by Kevin Feasel

Marc Lelijveld asks, what’s in a name?

In Fabric, you can have many different items in your Workspace. So many, that you easily get lost! Luckily there are tools at hand like Taskflows and Workspace folders. But still, it can be challenging to easily find all your items that ingest data, or find all items that are used for inbetween layers to transform data.

In this blog, I will tell you more about my personal best practice for naming convention of Fabric items that helps me to structure everything in my workspace.

This kind of thing typically doesn’t matter much when you only have a dozen or so items in your workspace. But as that number increases and different teams are working on different sets of items, it gets harder to figure out what’s going on without a proper naming convention.

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Renaming a Database in SQL Server

Published 2024-11-14 by Kevin Feasel

Steve Jones asks, what’s in a name?:

I had someone ask me how to rename a SQL Server database recently. They were doing some development work and wanted to rename databases to test an application. I thought I remembered, but in this post, I show I learned something.

Read on for the answer, as well as some notes about it. One additional thing I’d point out is that renaming the database doesn’t rename the underlying files.

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Renaming Factor Levels in R

Published 2024-03-06 by Kevin Feasel

Steven Sanderson renames factor levels of a categorical variable:

Before we jump into renaming factor levels, let’s quickly recap what factors are and why they’re useful. Factors are used to represent categorical data in R. They store both the values of the categorical variables and their corresponding levels. Each level represents a unique category within the variable.

Click through for three methods you can use to pull this off.

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Power BI Datasets? Semantic Models!

Published 2023-11-20 by Kevin Feasel

Chris Webb shares some thoughts:

The name change proved to be surprisingly uncontroversial. Of course it’s very disruptive – trust me, I know, I have around 500 blog posts that I need to do a search-and-replace on at some point – so I have a lot of sympathy for people with books or training courses that need updating or who are getting calls from confused end users who are wondering where their datasets have gone. But there was a general consensus that the change was the right thing to do:

Read on for a bit more of the story, as well as some great links to get additional information on semantic modeling.

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Naming Artifacts in Microsoft Fabric

Published 2023-08-18 by Kevin Feasel

Johnny Winter shares some advice:

With Fabric being a unified platform, the worlds of Power BI Developer and Data Engineer collide. So is a solid naming convention a good idea?

At Advancing Analytics, we say yes.

In fact, given the breadth of the platform and the variety of artifacts available for use in Fabric, it becomes even more important to have a strategy to be able to organise these items and make them quick and easy to identify.

Read on to see what Johnny recommends.

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Don’t Start Stored Procedure Names with sp_

Published 2023-08-16 by Kevin Feasel

Chad Callihan provides solid advice:

Everyone has an opinion on naming stored procedures. One opinion that can be agreed upon is that starting a stored procedure with “sp_” is not the way to go. Using “sp_” can only do harm. Let’s take a look at why that is.

Read on for Chad’s reasoning.

I don’t like prefixes at all for stored procedures (or tables). It’s a common misunderstanding of Hungarian notation, as you don’t provide any new and relevant information in the object name: of course it’s a stored procedure; I’m using “EXEC” to execute it, so what else could it be?

The exception to a very good rule is something which you intend to put in the master database and execute from any database context. The best example of this is sp_whoisactive.

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Role Analysis: DBA, Data Engineer, DB Reliability Engineer

Published 2023-07-27 by Kevin Feasel

Kendra Little disambiguates roles:

Much has changed: development patterns transformed from Waterfall to Agile, DevOps drives automation and shared ownership of code, and cloud services have made many more kinds of PAAS databases, data lakes, and data lakehouses available to organizations of all sizes.

These changes have introduced new and varied career paths for data folks which have different emphases on skill sets. In this post, I talk through the commonalities and differences between DBAs, Database Reliability Engineers (DBREs), and Data Engineers (DEs). Whether you’re a hiring manager or data professional, it’s worth knowing about these roles.

And a fourth one I’d include is Database Engineer, which I’ve also called a development DBA (versus a production DBA): focus on one platform, like SQL Server, and specialize in code development and tuning on that platform. I’d expect a Data Engineer to be familiar with at least one or two non-SQL programming languages—Python, Scala, Java, C#, F#, pick your poison—but that wouldn’t necessarily hold for a DBE.

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