A Fine Slice Of SQL Server
Treb Gatte has an interesting use case for Power BI Goals:
OKRs are but one of three emergent usage scenarios for Power BI Goals. I see some companies using Goals for Metric Aggregation and some for Balanced Scorecards. This post focuses on OKRs as I see the scenario offering broader benefits to the entire organization. OKRs are critical to creating an Action-centric culture.
Read on to understand what an OKR is and how Power BI Goals can help with tracking them.
Comments closedChris Webb explains the cost side of the ledger when it comes to measure creation:
You probably know that it’s a best practice to build your Power BI datasets in a separate .pbix file from your reports – among other things it means that different people can develop the dataset and reports. You may also know that if you are building a report in Power BI Desktop with a Live connection to a published dataset or Azure Analysis Services you can define your own measures inside the report. While this is very convenient, if you create too many measures there’s a price to pay in terms of query performance.
Click through for a demonstration of this.
Comments closedMarc Lelijveld continues a series on taking Power BI to the enterprise level:
On to the next topic, which is super important for global, enterprise grade solutions if you ask me. Security and information protection! The fifth blog in the series of transforming local into global Power BI solutions.
Good to know up front is that information protection is a feature that not specifically related to Power BI, but also applies to other Microsoft products and services. Though, in this blog I will explain the functionality of information protection, also known as sensitivity labels and how this applies to Power BI. Let’s first look at what the functionality is, where you can apply it and why it is important.
Read on for more information concerning sensitivity labels and where they become useful.
Comments closedIn this blog post I am going to cover how to implement Row Level Security (RSL) when using AAS and how this can be done on PPU.
In my example below I am going to show creating to simple RLS roles which will limit data for the users who belong to 2 roles.
Despite the simplification, we can see how row-level security applies to both products and how the two differ.
Comments closedMarco Russo and Alberto Ferrari share their take on a classic debate:
A question that is often asked during the design of a Power BI data model is whether it is better to use an Integer or a Datetime column to link a fact table with the Date dimension. Historically, using Integers has always been a better choice in database design. However, Tabular is an in-memory columnar database, and its architecture is quite different from the relational databases we might be used to working with.
Indeed, in Tabular there are no technical differences between using a Datetime or an Integer to create a relationship. The database size, the query speed, and any other technical detail are absolutely identical. Therefore, the choice is not related to technical aspects, but rather on the convenience of the design. Depending on the specific requirements of your model, you might favor one data type against the other. In the most common scenarios, a Datetime proves to be better because it provides more possibilities to compute values on dates without having to rely on relationships. With that said, if your model uses Integers and you do not need to perform calculations on the dates represented in the table, then you can choose the most convenient data type – that is, the one already used in the original data source.
The remaining part of the article aims to prove the previous sentences, and to provide you with the technical details about how we tested the respective performance of the two options.
Click through for Marco and Alberto’s analysis, noting that “date” here does not include time of day, so it would have the same cardinality as the integer date key. This was a more important thing fifteen years ago, before columnstore technologies (like columnstore indexes and VertiPaq) were readily available and that 4-byte integer was considerably smaller than an 8-byte DATETIME.
Welcome to part 8, where in this blog post, I am going compare deploying datasets.
For those people who are not exactly sure what deployments are, what this means is when you are using Power BI Desktop and you click on Publish, you are effectively deploying your changes to the Power BI Service (Which could also be a server in the cloud).
In this blog post I will show the differences when completing a deployment from AAS and then PPU.
Read on to see several techniques for deploying for each technology.
Comments closedWhen we look at the Power BI ecosystem, we can identify a bunch of different artifacts. For example, dataflows, datasets, reports, dashboards and many derivatives. As I explained in the previous post, the best practice for sharing content is through a Power BI App, which includes a list of users or active directory group containing multiple users. With that, the content becomes available after publishing to those who are granted access. Though, it can happen that one of the users shares the link with other users who do not have access to the content. As a property of the Power BI App, you can allow users to share the app and underlying dataset with share permissions. Though, working with sensitive data this might now be what you are looking for, as you might loose control over who has access.
Read on to see what constitutes a content access request and what you can do about them.
Comments closedPatrick LeBlanc has a video for us:
Using Smart Narratives and you’d like to add some conditional formatting in Power BI? Patrick shows you some tricks to take Smart Narratives to the next level!
Click through for the video.
Comments closedWhen creating a new dataset in AAS this is typically done with Visual Studio, there are a lot of similar items between Visual Studio and Power BI desktop, the biggest difference is how you access them are very different as well as their look and feel.
When starting with a new dataset the process is to create a new data source, import some data and then to create the tables.
Click through for the differences. This is one area where Power BI drags in comparison to Azure Analysis Services.
Comments closedKristyna Hughes links Power BI to a data source:
The step-by-step process below walks through connecting to data housed in Azure Blob Storage from Power BI using a SAS token. There are many ways to grab your data from Blob Storage, but this is the most efficient, scalable, and secure way that I found (with some security restrictions from watchful DBAs).
Click through for the solution, which is based on using SAS tokens.
Comments closed