A Fine Slice Of SQL Server
Andy Brownsword sends an e-mail:
SQL Agent jobs allow us to schedule and automate tasks on a SQL Server instance. Crucially, when things go wrong we need to know about them. That’s why we use notifications.
Setting up Operators and job Notifications is as expected on a Managed Instance. However, when it comes to sending the notifications we may have a challenge, as shown in the SQL Agent Error Logs:
Read on for the solution.
Comments closedJeffrey Wang digs into a new feature:
The October 2024 Power BI update introduces an inconspicuous yet significant preview feature: Value Filter Behavior. This feature is activated by setting a new model-level property, ValueFilterBehavior, to Independent. The default setting of Automatic preserves the existing behavior, at least during the public preview period. This property controls how the DAX SUMMARIZECOLUMNS function behaves, which is central to most DAX queries generated by Power BI visuals.
Don’t just take my world for it — create any Power BI visual by adding columns, filters, and measures. If you are familiar with the Performance Analyzer or other tools that capture the DAX query issued by the visual, you will see something like this:
Read on for Jeffrey’s example and a dive into what’s going on.
Comments closedWe are using Microsoft Fabric for our analytical data platform. The data is hosted in a warehouse and modeled in a star schema. Using the GraphQL API for Fabric, we are exposing it to end users, and for some reports, we want to join data together. Is this possible in a GraphQL query?
Read on for Koen’s solution to this issue.
Comments closedKelly Broekstra recommends against jumping right in:
Who has been told by a manager or business person to just connect to the source data and start creating a new report? Here is my tip:
DON’T DO IT
All Power BI and Fabric reports must have a semantic model, which Microsoft describes as “a logical description of an analytical domain, with metrics, business-friendly terminology, and representation, to enable deeper analysis.” – Source
Read on to learn why and what you should instead do if you want to have a better long-term experience with Power BI.
Comments closedGilbert Quevauvilliers builds a report:
One of the things I have found when working with my customers in Microsoft Fabric is that there is currently no way to easily view the total storage for the entire tenant.
Not only that, but it would also be time consuming and quite a challenge to then find out what is consuming the storage. Could it be large files or tables or warehouse tables?
In this blog post I will show you how using a Notebook you can get details of the storage across your Microsoft Fabric Tenant.
Click through for an image of the Power BI report and how you can get there.
Comments closedMatt Dancho shows off an R package:
Supply chain management is all about balancing supply and demand to ensure that inventory levels are optimized. Overestimating demand leads to excess stock, while underestimating it causes shortages. Accurate inventory projections allow businesses to plan ahead, make data-driven decisions, and avoid costly errors like over-buying inventory or getting into a stock-outage and having no inventory to meet demand.
Read on to learn more about the package and how it works. H/T R-Bloggers.
Comments closedDanica Fine continues a series on Kafka internals:
Welcome back to the third installment of our blog series where we’re diving into the beautiful black box that is Apache Kafka® to better understand how we interact with the cluster through producer and consumer clients.
Earlier in the series, we took a look at the Kafka producer to see how the client works before following a produce request as it’s processed by the cluster.
In this post, we’ll switch our attention to Kafka Consumer clients to see how consumers interact with the brokers, coordinate their partitions, and send requests to read data from your Kafka topics.
Read on to see what it takes for a consumer to operate in Apache Kafka.
Comments closedMarco Russo and Alberto Ferrari work in weeks:
Weekly calendars are common in manufacturing, retail, and any business that is sensitive to weekends or to the number of working days. For example, the scenario described in this article uses the number of pageviews on a website from 2019 to 2024, with data available until September 3, 2024. The website analyzed has a clear weekly trend, with slower traffic over the weekend, as shown in the following line chart with a daily granularity. It seems like a business website. A sports website would probably display the opposite trend.
Read on to see some of the challenges around week-based calendars. There’s a reason I have a “Dates and Numbers” category on Curated SQL and it’s exactly for things like this: some of the most common things we as humans work with are extremely complex and fraught with exceptions, including calendars.
Comments closedTim Mitchell hires some data detectives:
Earlier this month, I hosted the monthly T-SQL Tuesday invitation in which I asked, “What’s in your data detective toolkit?” We got some great responses which I’ll recap here, and I’ll share a few thoughts of my own at the end.
Click through this month’s responses, as well as Tim’s answer to the question.
Comments closedKristina Mishra takes us down an alley of pain:
If you’ve bought a P1 reserved capacity, you may have been told “No worries – it’s the same as an F64!” (Or really, this is probably the case for any P to F sku conversion.) Just as you suspected – that’s not entirely accurate. And if you are trying to create Fabric shortcuts on a storage account that uses a virtual network or IP filtering – it’s not going to work.
The problem seems to lie in the fact that P1 is not really an Azure resource in the same way an F sku is. So when you go to create your shortcut following all the recommend settings (more on that in a minute), you’ll wind up with some random authentication message like the one below “Unable to load. Error 403 – This request is not authorized to perform this operation”:
On the “oof” scale, this rates as “big oof.” Kristina shows some of the differences between P SKUs and F SKUs and why it matters, as well as two unpalatable solutions if you happen to be using a P SKU.
Comments closed