In the new workspaces, the Power BI Service offers a set of 4 roles where 3 of them (Admin, Member, and Contributor) have rights for deleting a dataset and everything that is connected to it. A catastrophe can occur with just 3 clicks. Today, I would like to show you how to protect a dataset from an unwanted deletion.
The purpose of this article is to explain how to generate an Organization Chart in an industrialized and fast manner, without error and with the minimum of manual interventions, in order to be able to display it in Power BI.
If you prefer a video rather than an article, go to the bottom of this post.
This organization chart should allow you to visualize complex organizations, with large quantities of entities (up to several hundreds), several levels of ownership (ex: level 1: holding company, level 2: company A and company B, level 3: company A1, A2, and B1 and B2), as well as multi-parent relationships (e.g. Company X is owned by both Company A at 49% and Company B at 51%.)
In order to make this possible, we describe, in detail, all the steps that are necessary. We unsuccessfully tried many custom visuals (see image below), and the use of Microsoft Visio, through the use of the Organization Chart Wizard, is the optimal solution that we had envisioned.
EARLIER () may be one of the more confusing functions to understand. Many of us deal with it by using an index to track on which row we are located and to which we can refer when writing our DAX formulas. Or we use a date column because of its sequential order. What if we have a date column that has duplicate dates that lead the engine to return an error? What if there is a way to have an Index column to be more than just a signpost? This is what I discovered when answering a question on this forum.
In the last few months I have been answering dozens of users’ questions. And there were at least three or four of you with different use cases but the same nominator: I have a table with two columns From and To. And for every distinct value of the column From I want to see all nodes which I can reach by traversing the edges From --> To. This problem has a name: transitive closure.
I have prepared an article about a transitive closure in Power Query (coming in 2 weeks). I wanted to publish the article already, but I decided to wait a little bit and write another one about a performance boost I’ve used in the code. It is a lookup table in Power Query.
Power BI is a business analytics service by Microsoft. It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end-users to create their own reports and dashboards. Currently, there is no direct way of Implementing CICD in PowerBI. Using the Publish menu from the PowerBI Desktop is the easiest way to deploy/publish a report as of now. In this article, we are going to see how we can implement source control and CICD for PowerBI using Azure DevOps.
Our customers often ask us in our projects or workshops why Power BI is so successful in the area of Business Intelligence. Besides all the advantages like Self-Service BI (especially for non-technical persons), connectivity to a lot of data sources, creation of stunning reports and dashboards, great possibilities for sharing and collaboration etc. there is one big reason for it: DAX!
Azure Analysis Services (AAS) doesn’t have a native Azure Data Lake Gen 2 (ADLSg2) connector yet, but now there’s a preview of “ADLSg2 Multi-Protocol Access” which allows using Blob’s API to access files in ADLSg2. This post describes a short step-by-step on connecting AAS to ADLSg2 using Blob API.
If you have spent any time in the Power BI Community, you have probably noticed regular contributors through community blog posts, activity in the Power BI forum discussions, and authored accepted solutions. Super Users are outstanding participants and expert users who regularly contribute useful solutions. Their advice is invaluable and it shows because they are in the Top Kudoed Authors Leaderboard in the Microsoft Power BI Community. See some familiar names? Their Community contributions and Power BI expertise continues to make the Power BI Community a valuable place.
What I wanted to do in this example is to show you how you can manage multiple dates in your Power BI tables. It's very common when I see Power BI users first seeing or coming across this particular scenario with their developer. There's always a bit of confusion on how you actually set up the data model correctly so that you can generate these insights that you need to work across multiple dates and this mainly lies within the data model.
I want to dive into two essential DAX functions that you absolutely need to understand well when using Power BI. These functions are CALCULATE and CALCULATETABLE. They are very similar in some aspects but also very different in others. I want to go through these with the accompanying tutorials during this post.
I wanted to dive into the topic of supporting tables inside of Power BI in this particular blog. Supporting tables are a unique development technique and are used for supporting logic that you might run through your core data model. Think of your core data model as the look up and fact tables that come from your raw data.
If you have a dataset in Power BI Desktop and you want to see what happens under the roof of the Vertipaq Engine, there is a great tool known as Vertipaq Analyzer. It can tell you how much space tables and columns consume, what their data types are like, what compress algorithms they use and so on. But before you can start analyzing your dataset, you need to set everything up.
Power BI's slicers provide a powerful way to hide rows in a table - but no built-in feature allows columns to be shuffled and sliced in a similar way. That doesn't mean it can't be implemented, however, and in a way that is close to seamless for an end user. Using a layer of measures, we can abstract the columns of raw data from the displayed columns, and allow columns to be dynamically displayed in any position.
We are all used Google location for whenever we travel into the new areas or find exactly where we are. So we simply turn on the location in our mobile. As soon as we turn on the location google will track our location with exact Latitude and Longitude. Infact google will track our lat and lon for every 3-5 seconds. Considering this amount of data for every one across the world, it's pretty big.
In this article we will see how we visualize our own location data from Google using the Microsoft PowerBI Tool. So, this article is going to combine the power of two big Shots
Google for Data
Microsoft for Technology
Before diving into this article further let see how the final report will look like,
In any reporting project, access to data is not enough. You have to access instantly to its explanations, its insights. Moreover, these insights must be contextual, that means they have to be related to the data they explain. This link between data and insights must be clear, obvious for the human eye, unequivocal.
For that, the ideal chart in Power BI is called the Pulse Chart.
This article is designed to go with my recent Data Stories Gallery submission, 3 Year Analysis of Gartner Magic Quadrant Leaders for Analytics and Business Intelligence. It's a rather lengthy title I know! Luckily however, the analysis was rather quick and easy. But, I thought that a few more insights could be shared around this than simply what appears in the Data Story Gallery posting or within the Power BI report.