Microsoft Excel is one of the most common data sources for Power BI. We can store Excel files in various storage types. The way we get data from Excel varies depending on the storage type. In this post, I quickly show two methods to connect to an Excel file stored in SharePoint Online.
Method 1: Getting the Excel File Path from the Excel Desktop App
This method requires you to have the Excel application installed on your machine. In this method, we open the Excel files stored in SharePoint Online in the Excel Desktop App in our machine and get the file path from there.
In SharePoint Online go to the desired document library then follow these steps to make it work:
Select the Excel file
Click the Open button
Click Open in app
Opening Excel file from SharePoint Online in Excel Desktop App
This opens the Excel file in the Excel Desktop application. In the Excel follow these steps:
Click the File menu
Click Info
Click the Copy path button
Copying Excel Path from Excel Desktop App
So far we got the Excel file path. The step is to get data from the copied path in Power BI Desktop.
Open Power BI Desktop and follow these steps:
Click Get data
Click Web
Getting data from Excel stored in SharePoint Online in Power BI Desktop
Paste the path we copied from Excel in the URL text box
Delete the ?web=1 from the end of the copied path
Click OK
Modifying the path copied from Excel to get the data in Power BI Desktop
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:
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 DBare query parameters. Read more about query parameters here. The results would like the following image:
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
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:
I am involved with a Power BI development in the past few days. I got some data exported from various systems in different formats, including Excel, CSV and OData. The CSV files are data export dumps from an ERP system. Working with ERP systems can be very time consuming, especially when you don’t have access to the data model, and you get the data in raw format in CSV files. It is challenging, as in the ERP systems, the table names and column names are not user friendly at all, which makes sense. The ERP systems are being used in various environments for many different customers with different requirements. So if we can get our hands to the underlying data model, we see configuration tables keeping column names. Some of the columns are custom built to cover specific needs. The tables may have many columns that are not necessarily useful for analytical purposes. So it is quite critical to have a good understanding of the underlying entity model. Anyhow, I don’t want to go off-topic.
The Problem
So, here is my scenario. I received about 10 files, including 15 tables. Some tables are quite small, so I didn’t bother. But some of them are really wide like having between 150 to 208 columns. Nice!
Looking at the column names, they cannot be more difficult to read than they are, and I have multiple tables like that. So I have to rename those columns to something more readable, more on this side of the story later.
Background
I emailed back to my customer, asking for their help. Luckily they have a very nice data expert who also understands their ERP system as well as the underlying entity model. I emailed him all the current column names and asked if he can provide more user-friendly names. He replied me back with a mapping table in Excel. Here is an example to show the Column Names Mapping table:
Column Names Mapping
I was quite happy with the mapping table. Now, the next step is to rename all columns is based on the mapping table. Ouch! I have almost 800 columns to rename. That is literally a pain in the neck, and it doesn’t sound quite right to burn the project time to rename 800 columns.
But wait, what about writing automating the rename process? Like writing a custom function to rename all columns at once? I recall I read an excellent blog post about renaming multiple columns in Power Query that Gilbert Quevauvilliers wrote in 2018. I definitely recommend looking at his blog post. So I must do something similar to what Gilbert did; creating a custom function that gets the original columns names and brings back the new names. Then I use the custom function in each table to rename the columns. Easy!
