Tag: Power BI Desktop

Business Intelligence - BI, Microsoft Fabric, Power BI, Power BI Desktop

Incremental Refresh in Power BI, Part 2; Best Practice; Do NOT Publish Data Model Changes from Power BI Desktop

Incremental Refresh Best Practice, Do NOT Publish Changes from Power BI Desktop

In a previous post, I shared a comprehensive guide on implementing Incremental Data Refresh in Power BI Desktop. We covered essential concepts such as truncation and load versus incremental load, understanding historical and incremental ranges, and the significant benefits of adopting incremental refresh for large tables. If you missed that post, I highly recommend giving it a read to get a solid foundation on the topic.

Now, let’s dive into Part 2 of this series where we will explore tips and tricks for implementing Incremental Data Refresh in more complex scenarios. This blog follows up on the insights provided in the first part, offering a deeper understanding of how Incremental Data Refresh works in Power BI. Whether you’re a seasoned Power BI user or just getting started, this post will provide valuable information on optimising your data refresh strategies. So, let’s begin.

When we publish a Power BI solution from Power BI Desktop to Fabric Service, we upload the data model, queries, reports, and the loaded data into the data model to the cloud. In essence, the Power Query queries, the data model and the loaded data will turn to the Semantic Model and the report will be a new report connected to the semantic model with Connect Live storage mode to the semantic model. If you are not sure what Connect Live means, then check out this post where I explain the differences between Connect Live and Direct Query storage modes.

The Publish process in Power BI Desktop makes absolute sense in the majority of Power BI developments. While Power BI Desktop is the predominant development tool to implement Power BI solutions, the publishing process is still not quite up to the task, especially on more complex scenarios such as having Incremental Data Refresh configured on one or more tables. Here is why.

As explained in this post, publishing the solution into the service for the first time does not create the partitions required for the incremental refresh. The partitions will be created after the first time we refresh the semantic model from the Fabric Service. Imagine the case where we successfully refreshed the semantic model, but we need to modify the solution in Power BI Desktop and republish the changes to the service. That’s where things get more complex than expected. Whenever we republish the new version from Power BI Desktop to Fabric Service, we get a warning that the semantic model exists in the target workspace and that we want to Overwrite it with the new one. In other words, Power BI Desktop currently does not offer to apply the semantic model changes without overwriting the entire model. This means that if we move forward, as the warning message suggests, we replace the existing semantic model and the created partitions with the new one without any partitions. So the new semantic model is now in its very first stage and the partitions of the table(s) with incremental refresh are gone. Of course, the partitions will be created during the next refresh, but this is not efficient and realistically totally unacceptable in production environments. That’s why we MUST NOT use Power BI Desktop for republishing an already published semantic model to avoid overriding the already created tables’ partitions. Now that Power BI Desktop does not support more advanced publishing scenarios such as detecting the existing partitions created by the incremental refresh process, let’s discuss our other options.

Alternatives to Power BI Desktop to Publish Changes to Fabric Service

While we should not publish the changes from Power BI Desktop to the Service, we can still use it as our development tool and publish the changes using third-party tools, thanks to the External Tools support feature. The following subsections explain using two tools that I believe are the best.

Continue reading “Incremental Refresh in Power BI, Part 2; Best Practice; Do NOT Publish Data Model Changes from Power BI Desktop” →
Business Intelligence - BI, Copilot, Microsoft Fabric, Power BI, Power BI Desktop, Power BI Service

Microsoft Fabric: Use Copilot to Generate Data Model Synonyms

Microsoft Fabric: Use Copilot to Generate Data Model Synonyms

One of my older posts explains how to enable Copilot on Fabric and how to use Copilot to generate Power BI reports. In this post, I aim to explain yet another use case for Copilot that can help us to make a better and more useful semantic model in Power BI using synonyms. In an old post published in May 2016, I explained how to use Power BI synonyms to take our Power BI Q&A experience to another level. In that post, I explained how we could use synonyms to translate data model objects in different languages so the end-user could ask questions in their native language and get the results in Power BI. That was such a cool use case for synonyms, I suppose, wasn’t it? Fast track to December 2023, I believe the Q&A is still one of the coolest Power BI features that stands out when demoing the solutions to the customers; therefore, it makes absolute sense to use synonyms to improve the Q&A‘s efficiency and accuracy. This blog post explores the possibility of using Copilot to define synonyms in Power BI Desktop.

Prerequisites

As explained here, we first need to enable Copilot on Fabric Service. Please note that the technique explained in this post requires either Power BI Premium Capacity or at least F64 Fabric capacity and won’t work on PPU, Embedded capacities, Fabric capacities smaller than F64 or Fabric Trial (FT) capacities.

We also need to have the latest version of Power BI Desktop installed on our machine. With that, let’s begin.

Using Power BI Copilot to generate synonyms

While defining synonyms for the semantic model objects significantly helps with the Q&A experience, it is still a cumbersome process if done manually. So, if we meet the prerequisites, we can summon Copilot to the rescue. Follow these steps after opening a Power BI file in Power BI Desktop:

  1. Ensure you’re signed into Fabric service with your account
  2. Click the Insert tab
  3. Select the Q&A visual
  4. On the Q&A visual, click the Q&A Setup button shown with a gear icon
  5. On the Q&A Setup window, you must see a message offering to “Improve Q&A with synonyms from Copilot” on top of the window; click the Add synonyms button

The following image shows the preceding steps:

Improve Q&A with synonyms from Power BI Copilot in Microsoft Fabric
Improve Q&A with synonyms from Copilot
Continue reading “Microsoft Fabric: Use Copilot to Generate Data Model Synonyms” →
Power BI, Power BI Desktop

Quick Tips: Find Power BI Desktop Local Port Number with Model Explorer

Quick Tips: Find Power BI Desktop Local Port Number with Model Explorer

In March 2018, I wrote a blogpost called Four Different Ways to Find Your Power BI Desktop Local Port Number. Last week, Zoe Doughlas from Microsoft left a comment reminding me of a fifth method to get the port which encouraged me to write this quick tip. Thanks to Zoe!

As the name suggests, the blog was about finding Power BI Desktop’s local port number. If you do not have any clue what I mean by local port number, I strongly suggest reading that blog.

This blog focuses on yet another method that wasn’t available back then. Indeed, it is a new feature added to the October 2023 release of Power BI Desktop. This is a Quick Tip so let’s jump straight to the topic and learn how we find the port number (and more) in Power BI Desktop (Oct 2023 and later releases).

Prerequisites

As mentioned, this new feature was added to Power BI Desktop’s October 2023; therefore, we must install that release on our local machine. Indeed, the October 2023 release was packed with many other features, including the Model Explorer (the topic of this blog) and the ability to define calculation groups directly in Power BI Desktop. Many of these features are still in preview; hence, they require enabling.

The following few steps explain how to enable Preview Features in Power BI Desktop:

  1. Open Power BI Desktop and click Settings (the gear icon) from the right pane
  2. On the Options page, from the GLOBAL section, click the Preview features tab
  3. Enable the desired features; for this blog, we need the Model explorer and Calculation group authoring
  4. Click OK

The following image shows the above steps:

Enabling Preview Features in Power BI Desktop
Enabling Preview Features in Power BI Desktop

Depending on the selected features, you may need to restart your Power BI Desktop to allow them to enable.

Looking at the above image, some of you may ask “Soheil, are you using an older version of Power BI Desktop?” and I am glad you asked. The answer as always is “It depends”. And, this time it depends on the timing of writing this blog which is early December 2023, and the fact that Power BI Desktop November 2023 was released a couple of weeks ago, therefore, Power BI Desktop October 2023 is kind of OLD! And, YES! I installed Power BI Desktop Nov 2023 for the sake of writing this blogpost.

Continue reading “Quick Tips: Find Power BI Desktop Local Port Number with Model Explorer” →
Azure SQL Database, Data Visualisation, Dataflows, Fabric Administrator, Lakehouse, Microsoft Fabric, Notebook, OneLake, Power BI, Power BI Desktop, Power BI Embedded Capacity, Power BI Premium Capacity, Power BI Service, Power Query, Self-Service BI, Synapse Data Engineering, Synapse Data Science, Synapse Data Warehouse

Unveiling Microsoft Fabric’s Impact on Power BI Developers and Analysts

Unveiling Microsoft Fabric’s Impact on Power BI Developers and Analysts

Microsoft Fabric is a new platform designed to bring together the data and analytics features of Microsoft products like Power BI and Azure Synapse Analytics into a single SaaS product. Its goal is to provide a smooth and consistent experience for both data professionals and business users, covering everything from data entry to gaining insights. A new data platform comes with new keywords and terminologies, so to get more familiar with some new terms in Microsoft Fabric, check out this blog post.

As mentioned in one of my previous posts, Microsoft Fabric is built upon the Power BI platform; therefore we expect it to provide ease of use, strong collaboration, and wide integration capabilities. While Microsoft Fabric is getting more attention in the market, so we see more and more organisations investigating the possibilities of migrating their existing data platforms to Microsoft Fabric. But what does it mean for seasoned Power BI developers? What about Power BI professional users such as data analysts and business analysts? In this post, I endeavor to answer those questions.

I have been blogging predominantly around Microsoft Data Platforms and especially Power BI since 2013. But I have never written about the history of Power BI. I believe it makes sense to touch upon the history of Power BI to better understand the size of its user base and how introducing a new data platform that includes Power BI can affect them. A quick search on the internet provides some interesting facts about it. So let’s take a moment and talk about it.

The history of Power BI

Power BI started as a top-secret project at Microsoft in 2006 by Thierry D’Hers and Amir Netz. They wanted to make a better way to analyse data using Microsoft Excel. They called their project “Gemini” at first.

In 2009, they released PowerPivot, a free extension for Excel that supports in-memory data processing. This made it faster and easier to do calculations and create reports. PowerPivot got quickly popular among Excel users, but it had some limitations. For example, it was hard to share large Excel files with others, and it was not possible to update the data automatically.

In 2015, Microsoft combined PowerPivot with another extension called Power Query, which lets users get data from different sources and clean it up. They also added a cloud service that lets users publish and share their reports online. They called this new product Power BI, which stands for Power Business Intelligence.

In the past few years, Power BI grasped a lot of attention in the market and improved a lot to cover more use cases and business requirements from data transformation, data modelling, and data visualisation to combining all these goods with the power of AI and ML to provide predictive and prescriptive analysis.

Who are Power BI Users?

Since its birth, Power BI has become one of the most popular and powerful data analysis and data visualisation tools in the world used by a wide variety of users. In the past few years, Power BI generated many new roles in the job market, such as Power BI developer, Power BI consultant, Power BI administrator, Power BI report writer, and whatnot, as well as helping many others by making their lives easier, such as data analysts and business analysts. With Power BI, the data analysts could efficiently analyse the data and make recommendations based on their findings. Business analysts could use Power BI to focus on more practical changes resulting from their analysis of the data and show their findings to the business much quicker than before. As a result, millions of users interact with Power BI on a daily basis in many ways. So, introducing a new data platform that sort of “Swallows Power BI” may sound daunting to those whose daily job relates to content creation, maintenance, or administrating Power BI environments. For many, the fear is real. But shall the developers and analysts be afraid of Microsoft Fabric? The short answer is “Absolutely not!”. Does it change the way we used to work with Power BI? Well, it depends.

To answer these questions, we first need to know who are Power BI users and how they interact with it.

Continue reading “Unveiling Microsoft Fabric’s Impact on Power BI Developers and Analysts” →