A Fine Slice Of SQL Server
Gilbert Quevauvilliers builds a report:
How much data is being stored in my Fabric OneLake (Lakehouse files and tables)
I recently had a question from someone in the fabric community asking how much storage was being used by the Lakehouse and tables.
This got me thinking that currently there is not an easy way to do this.
Read on to see how Gilbert found the answer.
Comments closedNicky van Vroenhoven performs a search:
You probably also use the same method as I did to search through the Admin portal and tenant settings: CTRL + F from your browser. It does the trick, but not very well.
For example, it only searches the titles of the settings, not the descriptions.
Next to that, you also can get a lof matches that you have to scroll or loop through, which makes it not very clear because more often than not, you don’t know in what section of the tenant settings you ended up.
Read on for an alternative method of searching. Or, I guess, two of them because without Nicky’s post, it can be easy to confuse the two search boxes.
Comments closedDavid Eldersveld talks licensing:
To facilitate a smooth transition from Power BI to Fabric (new capabilities), Microsoft ensured customers could access these new Fabric workloads as well as Copilot for Power BI on their existing Power BI Premium capacity P SKUs.
However, with the introduction of Azure-billed pay-as-you-go and annual reservation F SKUs for Microsoft Fabric, Microsoft recently announced the eventual retirement of the Power BI Premium per capacity SKUs that needs to consider an organization’s Enterprise Agreement (EA) timing.
Read on to learn more, especially if you currently have a Power BI Premium P1 (or higher) SKU.
Comments closedMarc Lelijveld builds a pipeline:
Recently, Microsoft released a new activity type to trigger Power BI Semantic Model refreshes. A great step forward to have a native pipeline activity and no longer need to setup complex steps with APIs and authentication manually. Or is there still a case?
In this blog I will elaborate on what this new Pipeline activity exactly is, various scenarios in which it can be applied and finally some edge cases and shortcomings.
Click through to see how it works.
Comments closedReza Rad hogs the photocopier:
Microsoft Fabric offers an end-to-end SaaS analytics solution; however, the world is using all kinds of data sources in its implementation. Mirroring is a new functionality in Fabric that allows customers to keep their data wherever they are, but then they can use Fabric analytics solutions with the same speed and performance as if their data were in Fabric. Best of all, this won’t cost extra. If you wonder what it is and how it works, read this article.
Click through for the video and article.
Comments closedAndy Leonard shares some thoughts on design:
When assigned a project, it’s tempting – and dangerous – to Just Start Coding. If you suffer from the urge to develop first and design later, you are not alone (there’s at least one other developer like you and he’s typing this post). Do yourself a favor and…
Read on for more information on Andy’s design-first mentality and a sample of how you might lay out that initial design.
Comments closedDennes Torres holds up a mirror:
You need to read data from production to build a single source of truth. If you create pipelines reading directly from production, you will create additional load over the production environment. The mirror allows you to do much of the production reporting from the mirror, leaving the production environment to serve other users. Keep in mind, production report, but not analytics report.
Mirroring a production database to Fabric is one method to ensure the load over production will be as low as possible and the data will be transferred fabric to complete the transformations from this point.
Only this? What about avoiding pipeline creation? Not really, you still need to create pipelines, as I will explain ahead.
Click through for the demo and explanation. This is an important thing for people to note: mirroring doesn’t eliminate ELT. You still have the data lake process to work through, as your transactional system does not and should not look like your reporting system.
Comments closedKevin Chant gives it the ol’ college try:
In this post I cover some initial testing of Mirroring Azure Cosmos DB Databases in Microsoft Fabric that I performed.
I wanted to do this post for various reasons. Including the fact that it was announced during the Microsoft Fabric Community Conference that Mirroring is now in Public Preview.
Which means that you can now mirror data from Azure SQL Database, Azure Cosmos DB and Snowflake into your own Microsoft Fabric tenant. Even trial tenants.
Kevin takes us through the process and gives it a try, sharing with us the results of some testing, including a test insertion of 100 million rows.
Comments closedMarc Lelijveld fills us in on the details:
This morning, I was looking for a specific tenant setting in the Fabric admin portal. While scrolling through a few of the tenant settings, I came across a specific one, which I like to elaborate on a bit more in detail, given I recently also had some questions around this topic from customers.
What happens if you delete a Fabric workspace? Is there a way to recover? How and for how long? Well, we now have a tenant setting to control this!
Click through for the details.
Comments closedMarco Russo compares and contrasts:
What is the right choice between Direct Lake and Import mode in Power BI?
At SQLBI, we do not publish content until we have had enough time to experiment with and collect data about new features. We usually don’t break the news unless we have enough time to test a feature in preview and consider the released service solid enough. This did not happen with Direct Lake, and we have not published any Direct Lake content yet, but it seemed not urgent for reasons we will see soon. However, the feedback collected from many attendees of SqlBits 2024 and the first Microsoft Fabric Conference raised the alarm: too many people have an incorrect perception of Direct Lake, which should be addressed as soon as possible to avoid architectural mistakes and unnecessary additional implementation costs.
Click through for the tl;dr version, followed by the explanations.
Comments closed