A Fine Slice Of SQL Server
Kurt Buhler crosses the streams:
If you use Power BI, Fabric, or Excel, connecting to Power BI datasets is straightforward. However if you use other BI tools like Tableau, it’s not obvious how you can leverage a Power BI semantic model in your workflow. In this article, I’ll explain how to connect to and use a Power BI dataset from Tableau Desktop.
Read on to see how. Also check out the notes in drill-down sections, as there’s a lot of content in there.
Comments closedNow I’m going to do something scary and try to explain some things. I tried to pay attention during the precon and had the pleasure of talking with Ljubica Vujovic Boskovic on the capacity usage. She, very patiently, helped me out where my mind completely lost all track. Her explanations were great, any errors are all mine and I will correct this blogpost if there are mistakes. If you want to know more, you can also read this blog by Chris Novak who digs a bit deeper into smoothing and bursting.
So let me give you a very quick and simple introduction into the capacity challenges we’re going to face.
Read on for an overview of how Microsoft Fabric capacity planning works and one concern with this style of “one capacity to rule them all.”
Comments closedReza Rad has a new video and article for us:
Since Microsoft Fabric is an end-to-end analytics service, it makes sense to have the means for data science, too. Here are tools, Fabric items, and libraries that help the Data Science to happen, or in other words, parts of the Data Science workload of Microsoft Fabric.
Reza also has plenty of links to other articles and videos for more detail.
Comments closedToby Smith looks at the current state of Data Activator in Microsoft Fabric:
Fabric is the newest all-in-one analytics solution from Microsoft. It combines multiple components (some existing, some new) into a single integrated environment. One of these new components is Data Activator. As Data Activator is still in development, there is still more functionality to be added. This blog shares some of the current abilities and uses for Data Activator, along with ideas for how you can use it in your own business situations.
One of the biggest challenges with big data is understanding it. With tools like Power BI, we are now able to understand and analyse data better than ever before. But when do we act on it? Do we have to manually look at these reports daily just to check everything is going ok? This is where Data Activator comes in. Data activator is a no-code tool that automatically takes actions when certain conditions are met in the data. These actions can vary from alerts in Microsoft Teams, calling stored procedures, triggering other fabric items like a pipeline, or even retraining AI models.
This is a feature which has enormous potential for near-real-time alerting and automating workflows. But do read on to learn about some of the limitations currently in the product.
Comments closedJose Mendes let us know what’s going on with Dataverse:
If like me, you’ve been keeping taps on what Microsoft has been up to on the Power Platform world, you would have noticed that there are two concepts that are regularly referenced in their architectures and generally associated to each other, Azure Data Lake Storage (ADLS) Gen 2 and Common Data Model (CDM).
As Francesco referred in his blog, Microsoft ultimate vision is for the CDM to be the de facto standard data model, however, although there is a fair amount of resources talking about the capabilities and features, it can be a bit confusing to understand how you can actually store your data in the CDM format in ADLS and use it to run data analytics such as data warehousing, Power BI reporting and Machine Learning.
Read on for more of what’s happening on that front. I will admit that Dataverse tends to be way down on my list of priorities, but that’s because I’m a relational database snob.
Comments closedJames Serra shares some thoughts on the Microsoft Fabric roadmap:
Just released was the Microsoft Fabric roadmap that you can check out at https://aka.ms/FabricRoadmap. It’s great to see Microsoft be transparent on what features they are working on and when they will be available.
Here are my top 18 features on the roadmap that I am most excited about (in the order found in the roadmap):
Seems like about half of what James is looking forward to releases in Q4 and the other half releases in mid-2024.
Comments closedNikola Ilic shows off one use case for Semantic Link:
I won’t spend time explaining what Semantic Link is – you can check a wonderful article written by my friend Sandeep Pawar, or refer to the official blog post. Sandeep’s blog post does a great job explaining not just what Semantic Link is, but also what are the possible use cases of this new feature.
Therefore, I will focus on explaining how you can leverage Semantic Link for a specific use case: I call it “Augmenting Gold Layer” (copyrights reserved). And, we will perform this “operation” by using SQL! Yes, you heard me well – we will leverage SparkSQL language to go above and beyond and “transform” the data currently sitting in Power BI datasets.
I will say that, for obvious reasons, this blog supports the Raw/Refined/Curated naming convention rather than Bronze/Silver/Gold, so I’d posit that this should be called the Augmented Curated Layer.
I can also recommend reading the blog post from Sandeep Pawar. It did a really good job of explaining why Semantic Link is worth getting excited about.
Comments closedMarc Lelijveld warms up the cache:
In the previous blog, I wrote about data temperature as part of Fabric when you’re using Direct Lake storage mode. In that blog, I explained how you can get insights in the temperature of a column, what that temperature means and what the impact of the temperature is on columns that are queried more often.
In this blog, I will continue this story by elaborating on a process called framing and how you can influence data eviction to drop data from memory. Finally, this blog goes into more details on how you could use Semantic Link in Fabric Notebooks to warm up the data for most optimal end-user performance.
The SQL Server analog here is having some automated queries which keep specific pages in the buffer pool, like a warm-up script for an instance with plenty of memory but slow disks.
Comments closedChris Webb refreshes our memories:
If you’ve heard about the new Direct Lake mode for Power BI datasets in Fabric you’ll know that it gives you the query performance of Import mode (well, almost) without the need to actually import any data. Direct Lake datasets can be refreshed though – in fact, they refresh automatically by default – and if you look at the dataset’s Refresh History you’ll see there’s a Direct Lake section which sometimes shows errors:
Chris goes on to ask and answer the question, what does it mean to refresh a Direct Lake dataset if you’re not actually importing the data into Power BI?
Comments closedKurt Buhler tries to limit information overload:
It’s just too much; I don’t have time for all this stuff.
I think this is a big problem. It’s a problem not just because people shouldn’t feel overwhelmed, but also because it says something about how effectively these new features, tools, and resources are being communicated, understood, and used. But what is the problem, exactly? And if you’re in the minority of people not feeling overwhelmed, why should you care?
Perhaps most importantly, how can we approach these new features, tools, and resources to ensure we understand them and can find value without feeling overwhelmed?
Read on for several tips on how to tackle learning about a product with a large surface area. And I’d also note that anybody who is comfortable working in SQL Server had to go through the same process.
Comments closed