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Category: Power BI

Incremental Refresh in Power BI Desktop

Soheil Bakhshi starts off a series on incremental refresh in Power BI:

Incremental refresh, or in short, IR, refers to loading the data incrementally, which has been around in the world of ETL for data warehousing for a long time. Let us discuss incremental refresh (or incremental data loading) in a simple language to better understand how it works.

Read on for the explanation as well as how you can implement it in Power BI Desktop. There are a lot of instructions here but they include publication and testing as well as development.

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Power BI Delivery Options

Paul Turley has a list:

When you sign-up for the Power BI service at PowerBI.com (this address redirects to App.PowerBI.com), use establish a tenant for your organization, hosted in the Azure cloud. Even if you setup a 90-day trial account, you have a tenant that you can upgrade later on. By default, all of the datasets, reports and other assets you publish to the workspaces in your tenant, are in a shared capacity. This means that Microsoft will manage the storage and resource allocation among shared servers in their data centers. Larger organizations will benefit from a dedicated capacity “Premium” tenant. This means that Microsoft dedicates at least one virtual machine in the Azure data center, with guaranteed capacity, for your tenant. With Premium-per-User (PPU) licensing, you pay per user.

Click through for a list of available options and some of the implications of each.

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Paginated Reports vs Interactive Power BI Reports

Paul Turley explains when to use each type of report:

Technology evolves, the industry changes and the way businesses use technology changes. The road that has brought us to the current state of reporting capabilities in the Microsoft data platform has been long and winding. Ten years ago, we were using SQL Server Reporting Services (SSRS) to create interactive, dashboard-like reports scorecard reports. It wasn’t easy and the report interactivity wasn’t exactly “snappy” as the report server had to re-query data and re-render the report every time a link or chart series was clicked. But, because SSRS was the best tool that we had back in the day, the techniques we used for advanced report development were arcane by today’s standards. Over the years, I’ve written a few articles and posts about how to create reports with interactive KPI gauges, charts and scorecards using SSRS. Today we have a better tool for that style of reporting and analytics. Reporting Services remains a powerful and flexible tool for a few different styles of reports. Now that SSRS has been integrated into the premium Power BI service as “Paginated Reports”, this raises questions about how and when to use each tool – and how to use them together.

Read on for more information, including a handy set of bullet points to help you make a decision.

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Azure Data Explorer Dynamic Columns in Power Query

Chris Webb blows out the margins:

Now you can easily extract the individual property values from this column in KQL, and indeed I did so in the KQL queries in this post, but the interesting thing is you can also extract these values in Power Query M very easily and – crucially – maintain query folding using the Record.FieldOrDefault M function in a custom column without needing to write any KQL yourself, in both Import mode and DirectQuery mode.

Read on to see how.

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Automating Power BI Data Model Metadata Extraction

Gerhard Brueckl avoids manual processes:

In the past I have been working on a lot of different Power BI projects and it has always been (and still is) a pain when it comes to the deployment of changes across multiple tiers(e.g. Dev/Test/Prod). The main problem here being that a file generated in Power BI desktop (.pbix) is basically a binary file and the metadata of the actual data model (BIM) cannot be easily extracted or derived. This causes a lot of problems upstream when you want to automate the deployment using CI/CD pipelines. Here are some common approaches to tackle these issues:

Click through to see several bad to palatable options and then check out Gerhard’s solution, which is significantly better. CI/CD is a huge pain point for Power BI developers but people like Gerhard are doing what they can to help.

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Tracking Table and Column Usage for Power BI Premium/PPU

Gilbert Quevauvilliers wants to see who’s using what tables:

I was reading through the blog post Announcing on-demand loading capabilities for large models in Power BI and I got a thought would it not be great to better understand which columns and tables are being used in my Power BI Premium/Premium per user datasets?

To do this, using the new DMV I could now look at the temperature of the tables-column.

The higher the temperature the more the table-column is being used in my reports!

Click through to see how Gilbert put this together but also pay attention to the caveats.

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Syntax for Scripting Calculation Groups

Marco Russo and Alberto Ferrari are linguists:

When calculation groups were introduced in 2019, we did not have a way to describe them in a textual form. A calculation group was represented as a table with one visible column and one or more rows, one for each calculated item. Each calculation item could have one or two DAX expressions associated with it – one for the calculation item itself and an optional one for the format string. Describing a calculation group in an article often required the writer to include screenshots of the Tabular Editor user interface, plus comments in the sample code to explain where each DAX expression should be placed in the user interface.

From the start we proposed a syntax to describe an entire calculation group in a textual form. However, there was no tool able to convert that syntax into the actual object in the Tabular model. For this reason, in the initial version of the articles about calculation groups we used a “pseudo-syntax” and we included comments that made the code more verbose and not necessarily easier to read. However, Tabular Editor 3 introduced the full DAX script syntax for calculation groups that we had hoped would be available in 2019. We decided to adopt that syntax in our content. We use this article as a guide to introduce and explain the DAX Script syntax for calculation groups.

Go check it out.

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Power BI Workspace Permissions

Marc Lelijveld continues a series on Power BI workspace configuration:

After Power BI Workspace setup – part 1, which was mainly about creating your workspace, giving it the right name etcetera, this blog will elaborate on workspace permissions. If you did not read part 1 yet, I encourage you to start at that blog to get the basic setup in place.

You might think, permissions is an easy topic, but often underestimated! In this blog I will describe the different workspace roles, and how you can apply them in your project. Also we will look at sharing specific content from a workspace perspective, such as sharing dataflows.

Read on to learn more.

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A Free Power BI Sandbox

Reza Rad has the right price in mind:

A question I often get from many students is: “How can I practice Power BI service features if I do not have a Power BI Account?”. Not having a Power BI account can happen because of many scenarios; your company might close this option so that the process be only channeled through a specific process within the company. Or you may not have the permission to do so. Not having an account makes it difficult to practice Power BI Service options such as workspace, datasets, dashboards, dataflows, apps, and many other features. On the other hand, even if you have the Power BI Service account, in most of the organizations, you are not the service administrator, so you cannot practice tenant-settings configurations in the service.

Fortunately, there is a way to create your own Power BI sandbox; which means an environment just for yourself, with 25 accounts. You will be the administrator of your environment. The environment will be up for at least 90 days, and you can practice whatever you want for the Power BI service there. The best of all, it is FREE. You don’t have to pay a cent for it. Credit card detail is not needed. What better you could wish for?

Read on to see how.

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Reviewing Power BI Query Sessions with Log Analytics

Chris Webb continues a series on Power BI monitoring:

In my last post I showed how to use Log Analytics data to analyse Power BI query activity. The problem with looking at a long list of queries, though, is that it can be overwhelming and it can be hard to get a sense of when users were and weren’t actively interacting with a report. In this post I’ll show you how you can write a KQL query that gives you a summary view that solves this problem by grouping queries into sessions.

Click through to see what Chris means by the term “session” and for the KQL to do the job.

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