Web Scraping Power BI

However, you can incorporate web scraping into your Power BI reports and data analysis workflows using the following methods:

1. Power Query (M Language):

   • Power Query, the data transformation and data connection component in Power BI, allows you to create custom data sources that can include web scraping.
   • You can write custom Power Query functions in M language to scrape data from websites by sending HTTP requests, parsing HTML, and extracting desired information.
   • This method requires some knowledge of web scraping techniques and M language.

2. Power Automate (formerly Microsoft Flow):

   • Power Automate can be used to automate various tasks, including web scraping, and it can work in conjunction with Power BI.
   • You can set up a Power Automate flow to periodically scrape data from a website and then push that data into a data source that Power BI can connect to, such as a SQL database or an Excel file.
   • Once the data is in a compatible source, you can connect Power BI to it and create reports.

3. Python or R Scripts:

   • Power BI allows you to run Python or R scripts within your data models. You can use Python or R libraries like Beautiful Soup or rvest to perform web scraping tasks.
   • By creating custom scripts, you can extract data from websites and bring it into Power BI for analysis.

4. Web Data Connector (For Cloud Services):

   • If the data you want to scrape is hosted on a web service with an API, you can create a custom Web Data Connector (WDC) in HTML and JavaScript.
   • This WDC can be used to pull data from web services and connect it to Power BI as a data source. This method is suitable for cloud-based data sources with APIs.