Business Intelligence - BI, Power BI, Power BI Desktop, Power BI Exporter

Exporting Power BI Desktop Data Using Power BI Exporter

Exporting Power BI Desktop Data Using Power BI Exporter
Exporting Power BI Desktop Data Using Power BI Exporter

I am excited to announce that our amazing team at Data Vizioner has developed a lightweight and easy to use external tool for Power BI Desktop named Power BI Exporter. The Power BI Exporter is a free community tool available for download here. With External Tools General Availability, you can expect to see more and more External Tools built by our amazing community members. I personally stunned to see many amazing ideas turn into useful tools. Learn more about Power BI announcements about External Tools GA here. I am humbled to be named in the announcement though. So thank you to Microsoft for that.

Let me start with a little background. In the past few years, I wrote a series of blog posts about exporting data from Power BI Desktop and Power BI Service. Those posts are quite popular. They are in the top 10 most visited posts on my website, contributing to about 15% of my website visitors. Here are the previous posts I wrote on this specific topic:

Apart from my website statistics showing many people want to export data from Power BI Desktop, some of my customers asked the same question. They wanted to export the curated data from their data model within Power BI Desktop to CSV format and make the curated data available for their other platforms. While all the methods mentioned in my previous blog posts are working, some users still find them complex. So I thought, we can make it better. We can make a straightforward tool that exports the data with only two clicks. So we started building the Power BI Exporter as a micro-project. We added some more ideas to the original idea of only exporting the data. We thought it is good to export the data along with the table names, column names and relationships. Having that information handy, we can quickly build the same data model as the one we exported its data but using the CSV files as the data sources. The other idea was to pack everything in a ZIP file on the fly, so we have a single ZIP file, including the tables, columns, and relationships. As a result, the first version of the Power BI Exporter is born. In this post I explain how it works.

Downloading and Installing Power BI Exported

You can download Power BI Exporter from its official webpage from Data Vizioner website. You require to enter your email address then click the Download button as shown in the following image:

Downloading Power BI Exporter from Data Vizioner Website
Downloading Power BI Exporter from Data Vizioner Website
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Business Intelligence - BI, Dataflows, Excel, Power BI, Power BI Desktop, Power BI Desktop RS, Power BI Service, Power Query, Self-Service BI

Quick Tips: Renaming All Tables’ Columns in One Go in Power Query

Renaming All Tables' Columns in One Go in Power Query

I previously wrote a blog post explaining how to rename all columns in a table in one go with Power Query. One of my visitors raised a question in the comments about the possibility to rename all columns from all tables in one go. Interestingly enough, one of my customers had a similar requirement. So I thought it is good to write a Quick Tip explaining how to meet the requirement.

The Problem

You are connecting to the data sources from Power BI Desktop (or Excel or Data Flows). The columns of the source tables are not user friendly, so you require to rename all columns. You already know how to rename all columns of a table in one go but you’d like to apply the renaming columns patterns to all tables.

The Solution

The solution is quite simple. We require to connect to the source, but we do not navigate to any tables straight away. In my case, my source table is an on-premises SQL Server. So I connect to the SQL Server instance using the Sql.Database(Server, DB) function in Power Query where the Server and the DB are query parameters. Read more about query parameters here. The results would like the following image:

The Results of Sql.Database() Function in Power Query
The results of running the Sql.Database(Server, DB) function

As you see in the above image, the results include Tables, Views and Functions. We are not interested in Functions therefore we just filter them out. The following image shows the results after applying the filter:

Filtering out SQL Server Functions After Connecting from Power Query
Filtering out SQL Server Functions

If we look closer to the Data column, we see that the column is indeed a Structured Column. The structured values of the Data column are Table values. If we click on a cell (not on the Table value of the cell), we can see the actual underlying data, as shown in the following image:

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Business Intelligence - BI, Power BI, Power BI Desktop, Quick Tips, Self-Service BI, SQL Server Management Studio - SSMS

Quick Tips: Registering SQL Server Profiler as an External Tool in Power BI Desktop

Registering SQL Server Profiler as an External Tool

It has been a long time that I use SQL Server Profiler to diagnose my data models in the Power BI Desktop. I wrote a blog post in June 2016 about connecting to the underlying Power BI Desktop model from different tools, including SQL Server Management Studio (SSMS), Excel and SQL Server Profiler. In this quick post, I share a pbitool.json file that you can use to register the SQL Server Profiler as an external tool. Read more about how to register an external tool here. This is quite handy as this way to use SQL Server Profiler to diagnose Power BI Desktop without needing to find the diagnostic port. As an external tool, the SQL Server Profiler automatically connects to the data model via the diagnostic port. You can download the sqlserverprofiler.pbitool.json file from here. After you download the file you can open it in a text editor to see or modify the JSON code. If you are using SSMS 18, then you do not even need to modify the file. If you use a different version, the only thing you have to change is the “path”.

The contents of the sqlserverprofiler.pbitool.json file
The contents of the sqlserverprofiler.pbitool.json file
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Azure, Business Intelligence - BI, Data Catalog, Power BI, Power BI Governance, Purview, Self-Service BI

Power BI Governance, Good Practices: Setting up Azure Purview for Power BI

Power BI Governance, Good Practices: Setting up Azure Purview for Power BI

Microsoft newly announced a piece of very exciting news that Azure Purview now supports Power BI. This is massive news from a data governance point of view. Azure Purview is the next generation of Azure Data Catalog with more metadata discovery power and the ability to use sensitivity labels. After reading the news, I immediately decided to set up my test environment and give it a go. I followed the steps mentioned in this article on the Microsoft documentation website but I faced some difficulties to get it to work. And here we are, another blog post to help you to set up the Azure Purview for Power BI.

Note: In this blog post I am not intending to explain what Azure Purview is. You can find heaps of useful information here.

Creating an Azure Purview Resource

We first need to have an Azure subscription, if you don’t have, don’t worry, you can start your Azure free trial subscription here. The following steps explain how to set up Azure Purview for Power BI:Login to the Azure Portal

  1. Click Create a resource button
Creating Azure Purview resource in Azure Portal
Creating Azure Purview resource in Azure Portal

2. Type in Purview in the search box

3. Click Azure Purview

Searching for Purview resource in Azure Portal
Searching for Purview resource in Azure Portal

4. Click the Create button

5. Select your Subscription

6. Select a Resource group or Create new if you don’t have any

7. Type in a name in the Purview account name text box

8. Select the Location

9. Click Review + Create (if you require to do more configurations click Next:Configuration > button)

Creating Azure Purview Account
Creating Azure Purview Account

At this point, Azure validates the configurations and requirements. You may get an error message like below:

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