How to Insert Data in Power BI

Getting your data into Power BI is the first step to creating clear and insightful reports. This guide will walk you through the most common and practical ways to load data, from simple Excel files to online sources and databases, using straightforward instructions for each method.

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The Easiest Starting Point: Power BI Desktop

While you can view and share reports in the online Power BI service, most data import and transformation work happens in the free Power BI Desktop application. This is where you connect your data sources, clean them up, and build your data models. Nearly every method we'll cover starts with a single, central button: Get Data.

You can find this button conveniently located in the Home tab of the ribbon. Clicking it reveals the most common data connectors, and clicking "More..." opens a window with hundreds of available options.

Method 1: Importing Data from Files

Connecting to files stored on your computer or a shared drive is one of the most frequent tasks in Power BI. Let's cover the most popular file types.

Connecting to an Excel Workbook

Excel files are a staple in business reporting, and Power BI makes connecting to them incredibly simple. If your boss emails you a weekly sales spreadsheet, this is how you get it into your dashboard.

1. On the Home tab, click Get Data > Excel Workbook.
2. Navigate to your file's location, select the .xlsx or .xls file, and click Open.
3. A Navigator window will appear. This window shows you all the available tables and worksheets within your Excel file. Select the checkboxes next to the items you want to import. A preview will appear on the right.

Once you’ve selected your data, you have two important choices at the bottom of the Navigator window:

• Load: Use this if you are confident your data is clean and perfectly formatted. It loads the tables directly into your Power BI data model, ready for you to start building visuals.
• Transform Data: This is almost always the better option. It opens the Power Query Editor, a powerful tool for cleaning, shaping, and preparing your data before it gets loaded. Here, you can remove blank rows, change data types, split columns, and much more.

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Connecting to a CSV or Text File

CSV (Comma-Separated Values) files are another universal standard, commonly used for exporting data from web applications or databases. The process is very similar to connecting to an Excel file.

1. Navigate to Get Data > Text/CSV.
2. Find and select your .csv or .txt file and click Open.
3. A preview window will appear. Power BI is smart enough to detect the settings correctly most of the time, but you should double-check them.

Key settings in this window include:

• Delimiter: This is the character that separates values. For a CSV, it's typically a comma, but it could also be a tab, semicolon, or something else.
• File Origin: Leave this as is unless your file contains special characters that are not displaying correctly.
• Data Type Detection: Power BI will guess the data type for each column (e.g., number, text, date). You can leave this on "Based on first 200 rows" or choose not to detect types if you prefer to set them manually in the Power Query Editor.

Just like with Excel, you will then choose between Load and Transform Data. Always lean towards transforming your data to ensure its quality.

Connecting to a Folder to Combine Files

This is an incredibly powerful feature. What if you get a separate sales report CSV every single month? Instead of importing them one by one, you can simply point Power BI to the folder where they are stored, and it will combine them into a single table automatically.

1. Go to Get Data > More....
2. In the new window, select Folder from the list and click Connect.
3. Browse to the folder containing your files and click OK.
4. A preview of the files in the folder will appear. Instead of "Load," you will see options like Combine & Transform Data or Combine & Load.

Choosing "Combine & Transform Data" tells Power BI to use the first file as a template, apply the same cleaning steps to every file in the folder, and then stack them all together. This automates a ton of manual work and ensures that when you drop a new file into the folder and hit refresh, it will be automatically included in your report.

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Method 2: Using the "Enter Data" Feature

What if you just need a small, static table? Maybe you want to create a quick reference table that maps product numbers to product categories, or a list of regional sales targets. You don't need a separate file for this, you can type the data directly into Power BI.

1. On the Home tab, click Enter Data.
2. A blank grid will appear. You can start typing data directly into the cells, just like in Excel. You can also paste data copied from a spreadsheet or web page.
3. To add a new column, click the asterisk (*) icon in the column header. Double-click "Column1" to rename it.
4. Give your table a meaningful name at the bottom of the window.
5. Click Load.

This method is perfect for small, simple lookup tables. However, keep in mind it’s not designed for large datasets. To edit the data later, you'll need to go into the Power Query Editor, find the query for your manual table, and click the gear icon in the "Source" step of the Applied Steps panel.

Method 3: Importing Data from Web Pages and APIs

Power BI can also pull data directly from the Internet. This can range from scraping a public data table on a website to connecting directly to a powerful application programming interface (API).

Scraping Data from a Web Page

Let's say you want to analyze data from a list of market caps on a financial website or demographic data from a Wikipedia page. As long as the data is in an HTML table, Power BI can usually grab it.

1. Click on Get Data > Web.
2. Paste the full URL of the web page containing the data into the dialog box and click OK.
3. Power BI will analyze the page, and the Navigator window will appear, showing you all the HTML tables it was able to detect.
4. Select a table from the list on the left to see a preview. You can also view the full page in the "Web View" tab.
5. Once you've found the table you need, select it and click Transform Data to clean it up. Web data almost always requires a bit of transformation to remove extra promotional text or reformat columns.

Note: This functionality works best on simple, static web pages. It may struggle with sites that require you to log in or use heavy JavaScript to display data.

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Connecting to Online Databases

For more robust reporting, you'll often need to connect directly to a cloud or on-premise database. Power BI supports a huge list, with SQL Server being one of the most common.

1. Navigate to Get Data > SQL Server.
2. In the dialog box, enter the Server name and, optionally, the Database name if you know it.
3. Here, you'll face your most important choice: Data Connectivity mode.

• Import: This mode makes a copy of your data and stores it inside your Power BI file (the .pbix file). Reports are incredibly fast because all the data is held in-memory. The downside is that the data is only as fresh as your last refresh. This is the default and most common mode.
• DirectQuery: This mode creates a live connection to the database. No data is stored in your file. When you interact with a visual, Power BI sends a live query to the database to get the latest results. This is ideal for very large datasets that won't fit in memory or for reports that need real-time data. The performance will depend on how fast your underlying database is.

1. Click OK. After entering your credentials, the Navigator window will appear, letting you select the specific tables and views you want to bring into your model.

Final Thoughts

Knowing how to connect to various data sources is the foundation of any Power BI project. Whether you're importing a simple spreadsheet with "Get Data," typing a lookup table with "Enter Data," or establishing a live database connection, Power BI Desktop provides a robust and user-friendly interface for everything.

Once you get comfortable connecting individual sources, you may find the real work begins when trying to blend data from everywhere at once—like Google Analytics, Salesforce, and your ad platforms. Manually stitching that data together is where most teams lose valuable time. We built Graphed to solve exactly that problem. Imagine connecting all those marketing and sales sources in seconds and then simply describing the dashboard you need in plain English. That's what we do, turning hours of manual data wrangling into a simple conversation.