How Does Power BI Import Website Data: HTML or XML?

Pulling data from a website into your reports doesn't have to involve endless copy-pasting into a spreadsheet. Microsoft Power BI has a built-in feature that lets you connect directly to web pages to import data from HTML tables or XML files. This article walks you through exactly how to do it, from finding the right data to cleaning it up for analysis.

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Why Bother Importing Data Directly from a Website?

Manually copying and pasting data is not only tedious but also prone to errors. Worse, the data is static, it's outdated the moment you paste it. Connecting Power BI directly to a web source automates this entire process, offering a handful of powerful advantages:

• Saves Time and Reduces Errors: Forget the manual drudgery. Set up the connection once, and you can refresh it with a single click to pull in the latest information. This eliminates the risk of copy-paste mistakes and saves you hours every week.
• Access to Public Data: The web is a massive repository of public data. You can pull information like competitor pricing, stock market data, government statistics, or sports results directly into your reports for competitive analysis or market research.
• Near Real-Time Reporting: When you schedule a refresh in the Power BI service, your reports and dashboards stay current automatically. If you're tracking data that updates daily, like exchange rates or public health statistics, your dashboards will always reflect the latest numbers without you lifting a finger.

Essentially, it turns any structured table on the web into a potential data source for your analysis, unlocking insights you might have previously considered too difficult to track.

Before You Start: Finding the Right Web Page

The success of importing web data hinges entirely on the structure of the source web page. Power BI is incredibly smart, but it works best with data that's already organized. The ideal sources are web pages that present information in clean, simple HTML tables (using the <table> tag).

What to Look For:

• Structured Tables: Wikipedia pages are classic examples. Pages listing populations by country, Oscar winners by year, or sports league standings are perfect candidates. Look for clear rows and columns that are easy for both a human and a machine to read.
• A Stable URL: The URL of the page should be consistent. If the URL changes every day (for example, with a new date embedded in it), you'll face challenges keeping your connection alive without some advanced Power Query work.
• Publicly Accessible Content: The page must not require a login. Power BI's web connector is designed for public anonymous access. If you need to log in to see the data, you'll need a more advanced solution or a dedicated API connector.

For example, a Wikipedia page listing the largest companies by revenue will have a well-formatted HTML table. This is the kind of clean, structured source that will give you the best results. Once you have the URL of your target page, you're ready to head into Power BI Desktop.

Step-by-Step: How to Import Website Data in Power BI

With your URL in hand, the process of importing the data is surprisingly straightforward. Here's how you do it in Power BI Desktop.

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1. Open the Web Connector

Start by navigating to the Home tab on the Power BI ribbon. From there, follow these clicks:

Click Get Data > More... in the pop-up window, choose Other > Web and then click Connect.

Pro Tip: The Web connector is one of the most common sources, so you can often find it directly in the main Get Data dropdown menu without needing to click "More...".

2. Enter the URL

A small dialog box titled "From Web" will appear. This is where you'll paste the URL of the website you want to grab data from. You'll primarily use the Basic option. Paste your URL into the text box and click OK.

The Advanced tab offers more options for constructing URLs in multipart, but for most standard use cases, the Basic option is all you need.

3. Choose Your Data in the Navigator Window

After you click OK, Power BI will connect to the URL and analyze its content. A new window called the Navigator will appear, displaying everything it found. This is where you'll select the specific data table you want to import.

On the left-hand pane, you'll see a list of items Power BI detected. These typically include:

• Suggested Tables: Power BI is smart enough to identify what looks like a structured data table and will list these at the top. This is almost always what you're looking for.
• A Full HTML Document Folder: This represents the entire HTML code of the page, which is rarely useful unless you're an advanced user trying to scrape unstructured data.

Click on one of the tables (e.g., "Table 1" or a specific name if the page provided one). The right-hand pane will show a preview of its data.

At the top of the preview pane, you can toggle between two views:

• Table View: This shows you a clean grid of the data as Power BI interprets it. It's perfect for confirming you've selected the right table of information.
• Web View: This shows you a mini-render of the actual live webpage. It helps you visually confirm which part of the page the table data corresponds to.

4. Load or Transform Your Data

Once you've found the correct table, you have two options at the bottom of the Navigator window:

• Load: This option will load the data directly into your Power BI data model as is. Only use this if you are 100% certain the data is perfectly clean, with correct headers, data types, and no extra columns.
• Transform Data: This is almost always the better choice. It opens the selected table in the Power Query Editor, a powerful tool where you can clean, shape, and prepare the data before loading it.

Click Transform Data to proceed.

Power Up Your Data: Using Power Query to Clean Your Import

Web data is rarely perfect. It often comes with extra columns, incorrect formatting, or missing headers. The Power Query Editor is where you turn this messy raw data into a clean, usable dataset for your reports.

When you click "Transform Data," the editor opens up. Here are some of the most common cleaning steps you'll perform on web data:

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Promote Headers

Oftentimes, the actual column headers (like "Company," "Revenue," "Year") are imported as the first row of data, while the headers are generic ("Column1," "Column2").

To fix this, go to the Home tab in the Power Query Editor and click Use First Row as Headers. Power Query will instantly promote that first row to become the official column headers.

Remove Unnecessary Columns and Rows

Web tables frequently contain extra baggage—"edit" links, footnotes, or image columns that you don't need for analysis. Simply right-click on the header of any column you don't need and select Remove. You can do the same for rows using the options under "Remove Rows" in the Home tab.

Change Data Types

Power BI might misinterpret data types. For example, a column of revenue figures might be imported as text instead of a number, meaning you can't perform calculations on it. Power Query lets you fix this easily.

Click the icon on the left of a column header (e.g., "ABC" for text, "123" for a whole number). A dropdown menu will appear where you can select the correct data type, such as Decimal Number, Date, or Whole Number.

Replace Values and Split Columns

Sometimes your text data needs tidying up. You might have currency symbols ($) or commas mixed in with your numbers. Use the Replace Values feature (found on the Transform tab) to find and replace these characters with nothing, leaving only the numbers.

You can also use the Split Column feature to break up a single column into multiples. For example, if you have a "Location" column with "New York, USA," you can split it by the comma delimiter to create separate "City" and "Country" columns.

Once you're happy with your cleaned and shaped data, click the Close & Apply button in the top-left corner. This will load the clean data model into Power BI, ready for you to build visualizations.

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What About Importing XML Data?

The process for importing data from an XML file or feed is nearly identical. XML (eXtensible Markup Language) is another common format for structuring data on the web. Instead of tables with rows and columns, it uses a hierarchical tree of tags.

To connect to an XML source, you follow a similar path:

Get Data > More... in Power BI, find and select XML, then click Connect.

From there, you can provide a URL that points to an .xml file or browse to a local XML file on your computer. Power BI will parse the XML structure and present it in the Navigator window. You may need to click through and expand several levels of the XML tree to find the data table you need. Once selected, the process of using the Power Query Editor to transform and clean the data remains exactly the same.

Final Thoughts

Connecting Power BI directly to web pages unlocks a vast universe of data for your analysis, automating what used to be a painful manual process. By selecting a structured source and using the Power Query Editor to shape your data, you can build refreshable reports that stay up-to-date with minimal effort, bringing external context right into your dashboards.

While Power BI's web connection is fantastic for public HTML tables and XML files, pulling data from business applications like Google Analytics, Shopify, or Facebook Ads often involves dedicated connectors that still require significant setup and cleaning. At an even simpler level, we believe insights should come from just asking questions. Instead of clicking through menus and transforming data, you should be able to ask for what you need in plain English. That's why we built Graphed, where you can connect your marketing and sales tools in seconds and simply ask, "Show me my top-performing ad campaigns by revenue," to get a real-time dashboard instantly.