A Fine Slice Of SQL Server
Brian Bønk gets in on the Microsoft Fabric fun:
Microsoft has released the final piece of the current puzzle around the OneLake as a one-stop-shopping service for dat in Fabric. Until now we had only access to the KQL data in the KQL database.
With this addition, we can now finally say that OneLake is the one place for your data in Fabric.
Read on to see how you can make data in an existing KQL database usable in OneLake.
Comments closedSoheil Bakhshi doesn’t want to forget to turn off the power at night:
In the previous blog post, I explained Microsoft Fabric capacities, shedding light on diverse capacity options and how they influence data projects. We delved into Capacity Units (CUs), pricing nuances, and practical cost control methods, including manually scaling and pausing Fabric capacity. Now, we’re taking the next step in our Microsoft Fabric journey by exploring the possibility of automating the pause and resume process. In this blog post, we’ll unlock the secrets to seamlessly managing your Fabric Capacity with automation that helps us save time and resources while optimising the usage of data and analytics workloads.
Right off the bat, this is a rather long blog, so I added a bonus section at the end for those who are reading from the beginning to the end. With that, let’s dive in!
To spoil the bonus a little bit, Soheil shows us not only how to turn things on and off on a schedule, but also how to ignore certain days of the week. Read the whole thing to get that.
Comments closedAndy Leonard kicks off a trial:
Are you interested in learning more about Microsoft Fabric?
One way to begin tinkering with the new platform is to start a free trial. At the time of this post, a free trial is available here:
Read on for instructions on how to try Fabric out. Now that Fabric is in GA, you’ll have to pay once the trial is over, but this does at least give you some time to check it out before then.
Comments closedSandeep Pawar wants readability:
JSON is ubiquitous, particularly when working with APIs and logs. Its unstructured nature makes it highly flexible for handling anything from a simple array to a complex nested structure. However, this can also make it challenging for data analysis. When parsing JSON, it’s crucial to understand its structure so you can flatten it and convert it into a tabular format for analysis. Once the structure is identified, you can use pandas or PySpark to explode or normalize it into the desired shape. In this article, I will explain the method I use. While this approach is applicable to any notebook, there is a specific trick to make it work in a Fabric notebook.
Read on for that trick.
Comments closedEugene Meidinger is ready to be at the intersection of Dunning-Kreuger and Imposter Syndrome:
I’ve written before about struggling to learn Azure Synapse, and I’ve struggled as well with getting excited about Microsoft Fabric. I think the pitch and the potential of Microsoft Fabric is real. The issue is that it solves problems I don’t have. In my work, I don’t deal with data so big that Power BI can’t handle it. I don’t deal with data so unstructured that Power Query can’t handle it.
But I know I need to learn Fabric. Power BI is a part of Fabric, the integrations are only going to continue to improve. If nothing else, I need to be able to tell customers if they should look into using Fabric or not. So what do you do when there is a technology you aren’t excited about, but have to learn?
Read on for Eugene’s scenario, which is certainly more interesting than Adventure Works.
Comments closedReitse Eskens shares some advice:
Last week the big announcement came at Microsoft Ignite, Fabric is GA.
Very cool, a lot of noise again for this shiny toolbox, but do we need to abandon everything and focus solely on the new toys?
Before I’ll answer that question, let’s look at a few moving parts of Fabric.
I think it’s still 1-2 years out from being fully baked. My hope is that there are (or will be) enough pieces in place to make it useful for enough scenarios that people don’t notice the gaps too much. There’s a lot of potential here and I don’t want Fabric to end up with a reputation of “too much stuff is missing to use it” because that reputation is hard to shake.
Comments closedSandeep Pawar scripts out some lakehouse work:
At MS Ignite, Microsoft unveiled a variety of new APIs designed for working with Fabric items, such as workspaces, Spark jobs, lakehouses, warehouses, ML items, and more. You can find detailed information about these APIs here. These APIs will be critical in the automation and CI/CD of Fabric workloads.
With the release of these APIs, a new method has been added to the
mssparkutilslibrary to simplify working with lakehouses. In this blog, I will explore the available options and provide examples. Please note that at the time of writing this blog, the information has not been published on the official documentation page, so keep an eye on the documentation for changes.
This looks to be quite useful for CI/CD work.
Comments closedMatt Gordon gives us the lowdown:
At their Microsoft Build conference in May 2023, Microsoft announced the company’s new unified analytics solution, Microsoft Fabric. As with any major product launch from a major cloud provider, a tremendous amount of noise and smoke accompanied the debut.
After all, when a company the size of Microsoft invests significantly in a product, you can be assured that the marketing blitz will be significant, too – and that was certainly the case with Fabric. The blitz will ramp up even further now that Microsoft announced at Microsoft Ignite that Fabric is already generally available (GA).
Behind that noise and smoke, though, all many of our customers and partners want to know is: Should I care? And if so, why? Let’s dive into this topic together from the perspective of a few key personas found at many companies.
Read on for Matt’s thoughts on the topic.
Comments closedReza Rad talks version control:
Power BI and Microsoft Fabric use Azure DevOps as the core component for their version and source control. The integration with Azure DevOps and Git helps maintain a copy of the source code and version it. It allows access to it anytime needed, plus the multi-development aspect added. In this article and video, you will learn how this integration works.
Click through for the article and video.
Comments closedLet’s try to break down these concepts and explain them as simple as possible:
Bursting lets you use more power than you purchased (within the specific timeframe)! Smoothing takes care that this power is “under control” within that same timeframe. Easy, right:)? I know, I know, so let’s break this further down…
Read on for some of the nuance behind this.
Comments closed