Get Started with Power BI
Learn how to use the Power BI collection of tools to connect data, transform it, and create compelling visualizations like charts, maps, and graphs, available across desktop, web, and mobile.
Those using Mac or Windows computers can view reports, add comments, download data, create subscriptions, and receive alerts through our . You can also use the service to make new reports and build data models directly.
Essentials
Become familiar with fundamental terminology and concepts, and learn how to navigate the Power BI environment.
- Review the to master core terms and concepts.
- Learn how to to locate workspaces, apps, and dashboards.
- Practice: Log in to and explore the interface.
- Switching from Tableau? Review our Tableau to Power BI Comparison [PDF].
Data Connections and Ingestion
Learn how to connect Power BI to various data sources safely and efficiently.
- Know where to prepare your data to guarantee better report performance, scalability, and maintainability.
- Understand the difference between Import and Direct Query.
- Connect to our Snowflake enterprise data lake.
- Practice: Connect to a Snowflake schema and perform basic data cleanup in Power Query before loading.
- (Optional) Connect to an . Note: Snowflake is the preferred data source.
Report Creation
Transform raw data into compelling visuals and leverage.
- Review the tutorial to learn how to develop charts, maps, and graphs.
- (Pro Licenses) .
- Ensure your report meets the guidelines outlined in the documentation.
- Practice: Build a single-page report that includes at least three distinct visual types (e.g., a bar chart, a trendline graph and a KPI card).
Sharing, Lifecycle, & Governance
Share reports securely with internal or external stakeholders while adhering to university data governance policies.
- Understand your workspace roles by reviewing the Workspace Setup guidelines.
- Review sharing protocols: use for internal teams, and understand the strict parameters of using for external audiences.
- (Optional) Learn how to manage your content lifecycle .
- Practice: if you don’t already have one. Practice publishing your completed report to a test app.
Next Steps
- New to Power BI: Attend the session or take the in FocusU.
- Keep Learning: Join the for ongoing support after completing your training. As a member of the Power BI User Group, you can ask real-time questions in the .
Quick Reference
Workspace Setup
Every Power BI user gets a personal workspace called My Workspace. This space is ideal for working on projects alone, such as developing, testing, or exploring content. However, it’s not meant for sharing or production use. For collaboration or sharing reports, users should use shared workspaces. These workspaces enable controlled access, improved version management, and publishing content through Power BI apps.
Access to the workspace should be configured according to the following guidelines:
- Admin - Teams should appoint one or more members as workspace administrators. Workspace administrators can update settings, manage access, and create apps.
- Member - Workspace administrators can designate other team members as members. Members can add additional users to the workspace with fewer permissions (i.e., contributors and viewers).
- Contributors - Contributors added to the workspace can develop or modify content, but they cannot change workspace access.
- Viewers - Do not use the Viewer role to share content with external users. Instead, users should access the content through an .
Get Data from Snowflake
Snowflake is the preferred data lake. When discussing enterprise data sources, we will focus on Snowflake. However, you can also get data from other sources, such as SQL databases, CSV files, and existing Power BI models.
To connect to Snowflake from Power BI Desktop:
- Select Get Data > More… from the toolbar.
- Search for Snowflake in the Get Data window.
- Select it, and click Connect.
- Enter the following information in the Snowflake window:
- Server: cmu-data.snowflakecomputing.com
- Warehouse: powerbi
- Click OK.
- (Optional) Use Advanced options to query your database using SQL if you prefer.
- When prompted to authenticate, do one of the following:
- Log In with your Andrew account - select Microsoft Account, click Sign In, and Connect.
- Use KeyPair - select KeyPair and enter your username and service account Private Key. Be sure to include begin and end statements in the key.
IMPORTANT: If this is your first time connecting to a service account using a keypair and you do not have an existing ODBC driver, you must download the before using this connection method. If you are using Power BI Service, you do not need to download the driver.
- Use the Navigator to find your database, schema, and table/view.
- Do one of the following:
- Use the data as is - select Load.
- Preview, modify, or filter the data - select Transform Data.
Data Preparation Decision Guide
There are three main options for data prep for Power BI. Knowing where to prepare your data guarantees better report performance, scalability, and maintainability.
- Snowflake (Source): Best for heavy lifting — complex joins, enterprise cleansing, pre-aggregations, and global filtering before data reaches Power BI.
- Power Query (Transformation): Best for report-specific tweaks — light dimension joins, field renaming, and filtering out unneeded rows to keep the dataset lean.
- DAX (Modeling): Best for dynamic interactivity — user slicers, custom KPIs, dynamic aggregations, and time-intelligence calculations
Connection Settings and Storage Modes
Import vs Direct Query
When you first connect to a data source such as Snowflake, SQL Server, or an enterprise database, Power BI asks, "How should we connect to and load this data?"
The table below compares the key features of each.
| Feature | Import Mode | DirectQuery Mode |
| Data Location | Stored in Power BI (In-memory) | Remains in Source (e.g., Snowflake) |
| Data Freshness | Refreshed on schedule | Real-time / Live |
| Performance | Fast (Processed in memory) | Variable (depends on source & network) |
| Dataset Size | Small to Medium datasets | Very Large datasets |
| DAX & Modeling | Full functionality | Limited (some functions restricted) |
| Source System Load | Low (Only loads during refresh) | High (queries the source on every user interaction) |
| Offline Access | Yes | No (requires continuous connection) |
Key Takeaways:
- Choose Import for fast report performance, full modeling/DAX capabilities, and standard dataset sizes.
- Choose DirectQuery when dealing with massive datasets, when real-time data is mandatory, or when strict database-level security policies apply.
Security Feature Comparison
In addition to differences in key features, the table below highlights the primary distinctions between the two connection modes concerning granular data access and governance.
|
Security Feature |
Import (Power BI RLS) |
DirectQuery (Snowflake RAPs) |
|
Security Location |
Power BI Semantic Model (Dataset) |
Snowflake |
|
User Identity |
Service Account (RLS applied post-refresh) |
End-User Identity (passes via SSO) |
|
Access Control |
DAX Security Roles in Power BI |
Native Snowflake Policies / Secure Views |
|
Security Audit |
Split between Power BI & Source |
Centralized in Snowflake Query Logs |
|
Data Governance |
Duplicated logic across multiple reports |
Centralized governance across all tools |
|
Best Used For... |
Small data volumes with simple, static rules |
Strict security needs with complex, dynamic rules |
Key Takeaways:
- Import (Power BI RLS): Best for static, straightforward security setups where dataset performance is the main priority. Logic must be maintained inside Power BI.
- DirectQuery (Snowflake RAPs): Best for strict enterprise governance. Security rules are managed centrally in Snowflake and enforced in real time using those users' SSO identity across all tools.