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How to Get Data from Another Power BI Report

Cody Schneider••7 min read

Recreating the same data model every time you build a new Power BI report is a massive time-sink. Not only is it inefficient, but it also creates inconsistencies when different reports define the same metric (like "Total Sales") in slightly different ways. Fortunately, Power BI has a powerful feature designed to solve this exact problem. This article will show you how to connect to and get data from another Power BI report, establishing a "single source of truth" that saves you time and keeps your reporting consistent.

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Why Re-use a Power BI Dataset?

Before jumping into the "how," let's quickly cover the "why." Connecting to an existing data model, often called a "shared dataset" or "golden dataset," is a best practice in the BI world for several key reasons:

  • Consistency is King: When your whole team builds reports from the same foundational dataset, everyone is using the same definitions, calculations, and business logic. A "customer," a "lead," or a "conversion" means the same thing everywhere, eliminating confusion and debates during meetings about whose numbers are correct.
  • Unmatched Efficiency: A data analyst or a BI developer has likely already spent hours cleaning data in Power Query, building a relational model, and writing complex DAX measures. Reusing their work means you don't have to reinvent the wheel. You get to skip the tedious data prep and jump straight to visualizing insights.
  • Better Performance and Governance: Instead of having five different reports refreshing data from the same source (like a Salesforce or Shopify account), you have one central dataset that refreshes. This reduces the load on your source systems. It also allows an owner to manage data governance, access, and row-level security in one central place.

The Core Concept: A Report is Not a Dataset

Understanding how Power BI handles your files is the key to this whole process. When you build a report in Power BI Desktop and publish it to the Power BI Service (the cloud-based platform), Power BI actually splits your .pbix file into two separate, but connected, components:

  1. The Report: This is the visual layer - the charts, tables, cards, slicers, colors, and layouts that you designed across your report pages.
  2. The Dataset: This is the underlying data model - the tables of data, the relationships between them, any transformations you made in Power Query, and all of your DAX measures.

Once published, this dataset can be "shared" and made available for other users to build entirely new reports on top of it. All you need is the right permission, which is called "Build" permission on that dataset.

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Step-by-Step: Connecting to a Power BI Dataset from Power BI Desktop

Ready to connect to that trusted "Sales Analytics" dataset your colleague built? Let’s walk through the steps inside Power BI Desktop. The process creates what is known as a "live connection" to the dataset in the Power BI service.

1. Open Power BI Desktop and Access the Data Hub

Start with a fresh, blank Power BI Desktop file. In the Home tab of the ribbon, instead of choosing a specific data source like Excel or SQL Server, click on Get Data and select Power BI datasets. Recently, this has been integrated into a feature called the OneLake data hub, which is Power BI's built-in data catalog.

2. Find and Select Your Desired Dataset

A new window will appear, showing all the datasets you have permission to access from across all the workspaces you're in. This view is incredibly helpful, providing key information at a glance:

  • Name: The name of the dataset.
  • Endorsement: Look for labels like Promoted or Certified. These are signs of quality. A "Certified" dataset is officially sanctioned by your organization as a trusted source of truth.
  • Owner: See who created the dataset so you know who to ask if you have questions.
  • Workspace: Know which workspace the dataset belongs to.
  • Refreshed: See when the data was last updated.

Browse or use the search bar to find the dataset you need. For this example, let's pretend we're connecting to a "Company Financials" dataset. Click its name, and then click the Connect button at the bottom right.

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3. Start Building Your Report

Once you connect, you'll be taken back to the report canvas. You may notice something different right away. The Data view and Model view icons on the left-hand pane are gone.

This is expected behavior for a live connection. Because the entire data model is being managed by the source dataset, Power BI won't let you alter it. You can't add new tables, edit relationships, or make Power Query transformations.

However, if you look at the Data pane on the right, you'll see all the tables, columns, and measures from the shared dataset, ready for you to use. You can now build a brand new report with complete visual freedom. Drag and drop fields onto the canvas, create new charts, and design the layout however you see fit.

Working with a Live Connection: Limitations and Superpowers

Connecting to a shared dataset gives you the best of both worlds: central governance and local flexibility. But it’s important to understand the rules of the road.

What You Can't Do:

  • Modify the Data Model: As mentioned, you cannot change the underlying model. If you need a new column or a relationship adjustment, you'll need to ask the dataset owner to add it to the original source.
  • Combine with Other Sources (Traditionally): By default, a live connection report can only get data from that one connection. You can't pull in a local Excel file and merge it. (There is an advanced feature called "DirectQuery for Power BI datasets" that allows this, but it adds significant complexity and is a topic for another day.)

What You Can Do (Your Superpower):

  • Create Report-Level Measures: This is the game-changer. While you can’t add calculated columns, you can write your own new DAX measures that exist only within your report. This is perfect for when you need a calculation specific to your report's context without cluttering the central dataset for everyone else. Simply click New Measure in the ribbon and write your DAX as usual. For example, you could create a measure for sales in a specific region:
West Region Sales =
CALCULATE(
    [Total Sales],
    'Locations'[Region] = "West"
)

Making Your Datasets Discoverable and Trusted

If you're on the other side of this equation - building the datasets that others will use - your job is to make them easy to find and trustworthy.

1. Promote or Certify Your Dataset

In the Power BI Service, go to the settings for your dataset. In the "Endorsement" section, you can mark it as either Promoted or Certified.

  • Promoted: This is an informal stamp of approval. You, the creator, are vouching that this is a quality dataset ready for others to use.
  • Certified: This is a formal, organizational endorsement. Typically, only a certain group of designated reviewers can certify a dataset after verifying its accuracy, completeness, and adherence to company standards. Certified datasets are the gold standard.

Endorsed datasets appear at the top of the list in the Data Hub, making it easy for users to find the best data quickly.

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2. Manage Permissions Wisely

For someone to connect to your dataset, they need Build permission. Users who are Admins, Members, or Contributors in a workspace get this permission automatically. You can also grant Build permission to users individually without adding them to the workspace itself. This lets them use your data without being able to see or edit the other reports in the workspace.

Final Thoughts

Getting data from another Power BI report by connecting to a shared dataset is a fundamental skill for creating scalable and reliable business intelligence. It moves your organization away from data chaos and towards a culture of consistency, where everyone builds on a centrally-governed, single source of truth.

This goal of simplifying data access for everyone is also at the heart of what we're building. While sharing datasets is a huge step up from manual spreadsheet wrangling, it still requires technical know-how. We created Graphed because we believe getting insights shouldn't require navigating BI tools at all. Instead of having to find the right Power BI dataset, you simply connect your raw data sources - like Shopify, Google Analytics, and Salesforce - and then ask questions in plain English. Graphed automatically builds real-time dashboards and reports for you, turning hours of analysis into a simple, 30-second conversation.

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