How to Enter Data Manually in Power BI

While Power BI excels at connecting to large, complex data sources like databases and cloud services, sometimes you just need to add a small bit of information quickly. Maybe it's a list of sales targets for the quarter, regional manager names, or a handful of product categories that don't live in a formal database. This guide will show you exactly how to manually enter data directly into Power BI, creating a new table from scratch without needing an external file.

Why Would You Manually Enter Data in Power BI?

Connecting to a database or a live service is usually the go-to method, but the manual "Enter Data" feature has several practical use cases where it shines. It's a handy tool in any data analyst's pocket for specific situations.

Fast Prototyping and Testing: Need to test a visualization or a DAX measure but don’t want to load an entire massive dataset? You can quickly create a small, representative table with a few rows to build and validate your visuals and formulas before connecting to the real data source.
Creating Static Lookup or Reference Tables: It's perfect for small, static tables that don't change often. For instance, you could create a table to map product IDs to user-friendly product descriptions, list department heads for each division, or define custom sorting orders that aren’t in your source data.
Creating Simple 'What If' Parameters: You can create a simple one-column table of numbers (e.g., 1% to 10%) and use it in a slicer to power 'what if' analysis, allowing users to see the impact of changing a variable in your report.
Consolidating One-Off Data: Sometimes, the data you need is in an email, a PDF, or a simple text note. Instead of creating a whole new spreadsheet file for just a few rows of data, you can input it directly into your Power BI model, keeping everything neat and contained within your PBIX file.

A Step-by-Step Guide to Entering Data in Power BI Desktop

The process of creating a new table by hand is straightforward. Let's walk through it step-by-step.

1. Open the "Enter Data" Tool

First, you need to find the feature within Power BI Desktop. It’s located in a prominent spot on the main ribbon.

Make sure you’re on the Home tab in the main ribbon.
Look for the Data section, and you'll see a button labeled "Enter Data." Click on it.

Clicking this button will open a new window called "Create Table." This is where you'll build your new table.

2. Create Your Columns and Add Your Data

The "Create Table" window looks and feels like a very minimalist spreadsheet, making it intuitive to use.

To Add Columns:

By default, you have one column named "Column1." To rename it, simply double-click the header and type your desired name (e.g., "Salesperson"). Press Enter.
To add a new column, click the asterisk (*) icon in the next column header. Type the name for your second column (e.g., "Region") and press Enter.
Repeat this process for every column you need. Let’s add a third one named "Monthly Target."

To Add Rows of Data:

Click on the first empty cell under your first column (the one with the blank asterisk to the left of the row).
Start typing your data. For example, type "Anna Smith."
You can press the Tab key to move to the next cell in the same row or press the Enter key to move down to the next row in the same column.
To add a new row, just keep typing in the last empty row, marked with an asterisk.

Let's populate our table with a few example rows:

3. Name and Load Your Table

Once you are happy with the data you've entered, don’t just click "Load." It's a crucial best practice to give your table a meaningful name first.

At the bottom of the "Create Table" window, there’s a text box labeled Name. By default, it might say "Table."
Replace the default name with something descriptive, like "Sales Targets Q4" or "RegionManagerMapping."
After naming your table, click the Load button.

Power BI will now load this data into your data model. You'll see your newly created table appear in the Data pane on the right-hand side of your canvas, right alongside any other data sources you might have loaded.

Your manually-entered table now acts like any other table in your model. You can see its contents in the Data View, create relationships to other tables in the Model View, and use its fields to build visualizations in the Report View.

How to Edit a Manually Entered Table

What if you realize you made a typo or need to add a new person to your sales target list? It's not immediately obvious how to get back to that entry-friendly spreadsheet view. You can't just edit the cells in the Data view.

The key is to go through the Power Query Editor, which is Power BI's data transformation engine. Here's how:

On the main Power BI screen, make sure you are in the Home tab.
Click the Transform Data button. This will launch the Power Query Editor window.
In the Queries pane on the left, you'll see a list of all your data sources, including the table you created manually. Click on its name (e.g., "Sales Targets Q4").
Now, look at the Query Settings pane on the right. You will see a list of steps under APPLIED STEPS. The very first step should be named Source.
Click the small gear icon (⚙️) next to the Source step.

This action will re-open the original "Create Table" dialog where you first entered your data! From here, you can make any changes: fix typos, add or delete rows, or even add new columns. Once your edits are complete, click OK. Finally, click Close & Apply in the upper-left corner of the Power Query Editor to save your changes and return to the main Power BI report.

Important Considerations and Limitations

Manually entering data is convenient, but it’s important to understand its limitations to avoid future headaches.

Good for Small, Static Data Only

This feature is designed for small amounts of data. Trying to manually input and manage hundreds or thousands of rows is incredibly inefficient and prone to errors. If your data lives in a spreadsheet and totals more than 30-40 rows, you are almost always better off connecting to the file directly using the "Get Data from Excel workbook" connector. Manually entered data is best for information that is truly static and short.

No Automatic Updates

The data you enter is embedded within your Power BI file. It's completely disconnected from any external source. If the original source of that information changes (e.g., a manager updates their team's targets in an email), you must manually go through the editing process described above to update it in Power BI. It will not refresh automatically.

Data Types

Power BI does a good job of guessing the data type for each column (e.g., Whole Number, Text, Date). However, it's always a smart idea to double-check this after loading your table. You can easily change a column's data type in the Power Query Editor by clicking the icon next to the column's name (e.g., ABC for text, 123 for whole number).

Example: Linking Targets to Actual Sales

To make this tangible, let's see how our manually created "Sales Targets Q4" table can be useful. Imagine you already have a main "Sales Transactions" table loaded from your database. That table has columns for Salesperson and SaleAmount.

Go to the Model View in Power BI (the third icon on the left vertical bar).
You will see boxes representing your tables. Find your "Sales Targets Q4" table and your "Sales Transactions" table.
Click and drag the Salesperson field from your "Sales Targets Q4" table and drop it directly onto the Salesperson field in your "Sales Transactions" table.

Power BI creates a relationship between them. Now, you can build a chart that compares performance against goals. For example, you could create a clustered column chart with Salesperson on the X-axis, and add both Sum of SaleAmount and Monthly Target to the Y-axis. This instantly lets you see who is meeting their targets and who is falling behind - all powered by a simple table you created in under a minute.

Final Thoughts

The "Enter Data" feature in Power BI is a deceptively simple tool that can significantly speed up your workflow for prototyping, testing, and handling small reference tables. By mastering how to create and edit these manual tables, you can add valuable context to your reports without the overhead of sourcing small datasets externally.

Manually entering information is great for tiny tables, but the real challenge is unifying data from all your different platforms - like Google Analytics, Salesforce, or Facebook Ads. At Graphed, we've designed an AI data analyst to solve this by eliminating manual work. We believe you should be able to get answers from your data using simple conversational language, not tangled spreadsheets. We let you connect all your tools in a few clicks so you can build real-time, interactive dashboards instantly. You can stop wrestling with reports and get started with Graphed for free.