... Freedяжning, prer, der ikkejign .. some of the biggest things to the conference in Wien in mid-september, where we from Fellow Mind is also with. And we're of course going to be able to get the new things, and the new things that come to Fabric live from event, when they're going to go out of the stable. But there are some things, some new things, which I think is worth going through and going through. And then I'm also going to talk about a feature that already exists in Fabric, but which is really, really good at kunne in its daily work with developing BI-lösninger. So let's hopped out of it. Yeah, as I said, there's not so much on the sun, but there are alligethes three things I've been looking at from Microsoft's website, which I think I will be able to do here today. And the one, it's maybe a little update, but it's alligethes a very important function. It's the collision-instilling for warehouses and lakehouses in Fabric. And the collision is actually just the rules that are set up, or that are set up for a database, for example, in text, case-sensitivity or insensitivity. So now you can choose the one or the other, but it could you not before. And it could potentially be a great thing if you could migrate to Fabric, and the existing code-based doesn't support the default. So it's a kind of a hindrance, which Microsoft has scored away, so it's even more to migrate over to Fabric, even if you have existing data-platform-lösninger and other steds. So there's also a new billing-model from Microsoft, which is called AutoScale Billing for Spark, and the other is now generally to be able to do. It's a PSU Go-model for Spark workloads. It means that you can have your basic capacity, which is the capacity model, where you have a certain capacity. And so at the side of the end, so you can have the AutoScale Billing, where you pay for your Spark workloads, for example, your notebooks, you're using. And it can be really smart to have a hybrid, if you have a large set-up with a very tung Spark compute, or if your notebooks are a little bit of a possibility, if you don't have the same for use of a month, so it can be a great idea to have a hybrid-lösning, where you use the new AutoScale Billing for your Spark, and then have your other workloads, for example, Powerberg-rapports, or Lakehouse and Warehouses, which are on the capacity model. And it opens up for, at Fabric can understøtte many more scenarios and many more setups in the Q. And it's not a substitute for capacity model, it's more a compliment to it. So, the last thing I've chosen to take here is, at Microsoft now drop the semantics model, which automatically gets opened, when you made a warehouse or Lakehouse and also SQL database, when it came forth. So, when you made these artifacts, so became there automatically a semantics model, and it was a little from Microsoft's side of a plug-and-play for, at come in and get in and get in. And with a power-back-rapporter, so had man a default model, so you could get in and get in and get in. But they had maybe seen that, at the brugers would like to have more control, and they had of course their own use cases, so the default semantics model would have just created more confusion and more rued in one's work-space, than what there was actually to think. So, the one has I've chosen to say goodbye to. And it's a bit of a great pleasure, at we can do that in our work-space. So, three mindre new things. Not at the end of the time, but all of the things I think viser, at Microsoft also lytter to the customer and do what they need to do for, and it becomes more and more to migrate and work with Fabric. So, I would like to talk a little bit about a existing feature in Fabric. What's the name of Semantic Link and Semantic Link Labs. Oh, yeah, in the end of the day, I'll just throw a slag for Microsoft's roadmap tool, where you can see all the features, which are in roadmap, when they come, at least when they are planned to come, and a little description of what they actually do. So, I think it's a great fit for me to hold me orient to it, what's the name of there. But like the same thing, Semantic Link and Semantic Link Labs, and it's something that has been there for years, but because it's so useful for us at work with both the Fabric Data Platform, but also just the development of semantics of the model and the power of the reporter, so I think it was really nice to get a focus on it in Fabric Friendship Broadcast. What is Semantic Link Labs? It is a Python-bibliotek, which you can use in Fabric Notebooks. It is specifically specific to Fabric Notebooks. Biblioteket consists of a number of functions, which are really brugers. You can't be an expert in Python for using these functions. And it gives programmatic adgang to semantics models, praguebæreports, lakehouses, warehouses, and all other things in Fabric. And the idea with Semantic Link Labs has been to make it easier for the developers and admins to use. Some of the things that were created by the people, which were able to use a lot of APIs, which were brugers and make it easier for the people to automate. Some of the things that make the day a lot easier to work with Power BI and Fabric and semantics models. The whole project is open source. It is on Microsoft's official GitHub site. I will just go over to the GitHub site. I will just go to Semantic Link Labs GitHub site. I will find inspiration. I am almost sure that, at the development, or governance or optimisation, is there a function in Semantic Link Labs, which can help with it or make it easier for it. So it's somehow a ken of a full partner. It's almost all about a second. It's quite clear to use it to be some key to use it for,"Semantic Link Labs. Both are ensuring that, in other words, answers your computer. There are also a kon yoardi thinking of multiple tools for, whenever you work with Power BI. And it's not because of Semantic Link Labs at the same steps, which I likely assume is, We're going to start with all the products, but we have many things, the other can, together at one sted, and we have the opportunity to automate and schedule for example check-in report on best practices, because you can schedule your notebook. So you can do it a part of the development lifecycle in the development of your platform. I will give you a little example on how you can use Semantic Link Labs. It takes about five minutes before you say wow, it's a old Microsoft slogan for the time Power BI was launched. The idea was to get to get to get to the data, to get to the illustrations and get to the data and get to the data. So I have it with Semantic Link Labs, because it really really takes a lot of time to get to the data. Let's try to take a quick demo here of Semantic Link Labs. I hopped over to Fabric platform, and I have a notebook open. And it's like, you can have Semantic Link Labs installed in your own environment. If you don't have it, you can install it in every session, you will use it. And I don't have a place where it is already. So I started with it. And semantic link labs, so I have a lot of them and been working on semantic linkin, so I have been working on some of them and then I have been working on some my own movement. It does not take too much longer, so I still have worked on the existing machine, so I make it a État Raceway and I need to start with Power BI. Let's see here, I don't need to get started at metISS新атurain assign camera. And these functions I have in my notebook are just some of my friends at take fat in on GitHub. There are the packers I would like to have. And an example I have taken out of the best practice analysis. That means we can carry out the best practice analysis on our semantins model and then the other places we can carry out the best practice. There are the ones that are going to carry out the run model BPA and I will carry out the fabric frenzy report. The report I have made on the front, which is in my workspace. So a job, which is a lieutenant that should be for otherwise I would use a particular geen innovation plan, which is a software servers. Den is the case and sheidoes. and then I'll be able to use my semantics model on the Dax, Format, Performance, etc. All the places where I don't hold best practice in relation to analyzer. I've also been able to do this here where I've analyzed all semantics models in my workspace, because it takes a little time than what I think we should look at here. But again, the one-in-the-code that will be can be made a semantics model on the basis of the best practice analyzer. On the semantics model can be made a report. This has been made up and made it in the way. Why is it so smart? It's smart because we find the report here. Model BPA. It's smart because you have a sample of an overview of one's organizations report. And which are the semantics model that are holding best practices and which are not more relevant, which are not relevant. And the notebook here, where you can see on the basis of workspaces and semantics models, which are the rules, which are the ones that are overtrod, and which degree it is. If it's an error, warning, info, etc. And the notebook, because you can schedule your notebooks, so you can take it in a day and have an overview of our semantics models in our workspace and our organization. And see, if there is something we should do with it and take a look at it. And as I said, Semantic Link Labs, it's not only a reporter, it's not only semantics models, it's not only a lake houses, it's not only a fabric platform, it's not only a fabric platform, it's not only a fabric platform. So you can go in and check it out, if you don't use it. I can't guarantee it, at there's a place where you think, it's not only a place where you can use it. And allered there, so you have you, so you have you, so you have you, so you have you, so you have you, so you have to optimize your time. So Semantic Link Labs, give it a shot. It was actually, it was really, it was a lot of things I had with today from fabric, or from fabric broadcasting. I just wanted to move on to make one of our own broadcasts. I had to make one of our own refreshments. From Bronze to Brilliance, Mastering Fabrics Medallion Architecture. Where Oliver Nygaard og Kevin Burns kommer til at gå igennem, hvordan man designer og bygger en fremtidssikret dataplatform i fabric. Og det er altså tre forskellige sessioner, hvor den første starter den 24. september. Og man kan tilmelde sig på linket der, broadcast.fellermind.dk. And remember to check with us when we are to a conference in Wien. We will be able to share all the new things from Fabric and Microsoft directly from Wien. We are glad to see you. Thank you for today.