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Author: Kevin Feasel

Maintaining Existing Power BI Data while Loading More with Fabric

Published 2023-09-25 by Kevin Feasel

Chris Webb looks back on an older post:

To be honest I’m slightly ashamed of this fact because, as I say in the post, the solution I describe is a bit of a hack – but at the same time, the post is popular because a lot of people have the problem of needing to add new data to the data that’s already there in their Power BI dataset and there’s no obvious way of doing that. As I also say in that post, the best solution is to stage the data in a relational database or some other store outside Power BI so you have a copy of all the data if you ever need to do a full refresh of your Power BI dataset.

Why revisit this subject? Well, with Fabric it’s now much easier for you as a Power BI developer to build that place to store a full copy of your data outside your Power BI dataset and solve this problem properly.

Read on for an example of the new solution.

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Dynamic Highlighting of Data Points Based on Slicer Selection

Published 2023-09-25 by Kevin Feasel

Nikola Ilic shines a light on the data:

To quickly explain: when a user selects, for example, Contoso in the slicer, the Contoso bar should be highlighted by using a different color. As much as this sounds like a very basic and common business request, there is no straightforward solution in Power BI (or, at least, I’m not aware of it:))

However, the client’s wish is (almost) always our command – so, let’s see how this feature can be implemented with a little bit of data model tweaking and leveraging some DAX code.

Spoilers: there is a solution, though it does involve quite a few steps.

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Using DAX to Find Products Missing Sales

Published 2023-09-25 by Kevin Feasel

Marco Russo and Alberto Ferrari observe the dog that didn’t bark:

What products did not sell in a specific area, store, or time period? This may be an important analysis for several businesses. There are multiple ways to obtain the desired result. Some specific implementations might be needed because of the user or model requirements, whereas developers can choose any formula in several cases. Or you might just find a solution on the web and blindly implement it without questioning whether there is a better way to achieve what you want.

It turns out that different formulas perform very differently. Choosing the right one in your scenario can make a slow report fast. This article analyzes the performance of different formulations of one same algorithm. 

It’s interesting to see the performance profile here: most are reasonably close together, although you can still get a 2x gain from using the fastest approach versus the second-slowest. And then there’s the slowpoke.

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Attacks on Row-Level Security

Published 2023-09-25 by Kevin Feasel

Ben Johnston continues a series on row-level security in SQL Server:

As mentioned in previous sections, RLS is an addition to security and should not be used as the primary method to limit access to data. It is a supplementary layer, useful in specific scenarios. There are also instances where RLS can be defeated by an unauthorized user. The attacks listed below are broken down into direct attacks, indirect attacks, and side-channel attacks. The categorizations could be changed, but the important part of each is the vulnerability discussed.

The one scenario I’m a bit surprised about is the divide by zero attack, as I had figured the filter predicate would apply before the computation leading to a divide by zero scenario.

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Kafka Message Compression

Published 2023-09-22 by Kevin Feasel

Lucia Cerchie and Dave Troiano give us the rundown on compression of individual messages in Apache Kafka:

Topic partitions are the main “unit of parallelism” in Kafka. What’s a unit of parallelism? It’s like having multiple cashiers in the same store instead of one. Multiple purchases can be made at once, which increases the overall amount of purchases made in the same amount of time (this is like throughput). In this case, the cashier is the unit of parallelism. 

In Kafka, each partition leader can live on a different broker in a cluster, and a producer can send multiple messages, each with a different destination topic partition; that is, a producer can send them in parallel. While this is the main reason Kafka enables high throughput, compression can also be a tool to help improve throughput and efficiency by reducing network traffic due to smaller messages. A well-executed compression strategy also means better disk utilization in Kafka, since stored messages on disk are smaller. 

Click through for the various options and some guidance on using each.

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Oracle: RMAN and Non-Synchronizing Standby Database

Published 2023-09-22 by Kevin Feasel

David Fitzjarrell proffers advice on recovering from a non-synchronizing standby database:

Occasionally the unthinkable can occur and the DBA can be left with a standby database that is no longer synchronizing with the primary. A plethora of “advice”will soon follow that discovery, most of it much like this:

“Well, ya gotta rebuild it.”

Of course the question to ask is “how far out of synch is the standby>” That question is key in determining how to attack this situation. Let’s go through the two most common occurrences of this and see how to address them.

Read on to see David’s advice.

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Deployment Pipelines for Microsoft Fabric

Published 2023-09-22 by Kevin Feasel

Reitse Eskens crosses a line:

It’s a bit of a challenge to keep up with all the changes, updates and all the new stuff coming out for Fabric. As I’m not really invested in the PowerBI part of the data platform (yay pie charts ;)), some things that are very common for the PowerBI community are very new to me. I have it on good authority that this blog covers a feature that is well know within PowerBI but quite new in the data engineering part. When I say that, I need to add that at the time of writing, only the PowerBI side of things are fully supported but I have very good hopes that pipelines and notebooks will be supported as well.

Supporting pie charts are fightin’ words here. Nonetheless, read on to see how deployment pipelines work in Microsoft Fabric.

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Query Execution Concepts and SQL Server

Published 2023-09-22 by Kevin Feasel

Erik Darling answers the question, why is it so hard to figure out why my query sometimes sucks:

Sometimes people will ask me penetrating questions like “why does SQL Server choose a bad execution plan?” or “why is this query sometimes slow?”

Like many things in databases, it’s an endless spiral of multiverses (and turtles) in which many choose your own adventure games are played and, well, sometimes you get eaten by a Grue.

In this post, I’m going to talk at a high level about potential reasons for both.

Read on for a smorgasbord of factors to consider based on the steps SQL Server takes.

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