Power BI Interview Questions and Answers 2025

Power BI is a business analytics tool by Microsoft that enables users to visualize data, share insights, and make data-driven decisions. Its main features include interactive dashboards, data modeling, data transformation, and integration with various data sources.

Power BI allows users to connect to a wide range of data sources such as Excel, SQL Server, SharePoint, cloud services, and web APIs. Connections can be established using built-in connectors, and users can import or directly query data.

Power BI Desktop is a Windows application used for creating reports and data models locally. Power BI Service is a cloud-based platform where users can publish, share, and collaborate on reports and dashboards online.

A Power BI dashboard is a single-page, interactive view of data, often used to monitor key metrics. Reports are multi-page documents that provide detailed data analysis. Dashboards can aggregate visuals from multiple reports.

Power BI allows users to schedule automatic data refreshes for datasets published to the Power BI Service. This ensures that dashboards and reports display the most up-to-date information without manual intervention.

DAX (Data Analysis Expressions) is a formula language used in Power BI for creating custom calculations and aggregations. It is essential for building calculated columns, measures, and advanced analytics within reports.

Power BI reports can be shared by publishing them to the Power BI Service, where users can grant access to colleagues or stakeholders. Reports can also be embedded in websites, shared via links, or exported as PDF or PowerPoint files.

Power BI offers a variety of visualizations such as bar charts, line graphs, maps, and tables. The choice of visualization depends on the data and the insights you want to convey. Selecting the right visual helps communicate information effectively.

Data modeling in Power BI involves creating relationships between tables, defining hierarchies, and building calculated fields. A well-designed data model ensures accurate analysis and efficient report performance.

Power Query is a data transformation and preparation tool integrated into Power BI. It allows users to clean, reshape, and combine data from multiple sources before loading it into the data model for analysis.

Calculated columns are computed during data refresh and stored in the data model, while measures are calculated on the fly based on the context of the report. Measures are more efficient for aggregations and dynamic calculations.

Row-level security restricts data access for certain users by defining roles and DAX filters on tables. You can configure RLS in Power BI Desktop by creating roles and assigning DAX expressions, then publish to Power BI Service and assign users to roles.

Relationships define how tables are connected in Power BI, typically through primary and foreign keys. You can create one-to-many, many-to-one, or many-to-many relationships, and set cross-filter direction to control data flow.

Performance can be improved by reducing the number of visuals, optimizing DAX queries, using star schema data models, minimizing calculated columns, and aggregating data before importing. Monitoring with Performance Analyzer helps identify bottlenecks.

Bookmarks capture the current state of a report page, including filters and visuals. They are used to create interactive navigation, storytelling, and custom user experiences by linking bookmarks to buttons or images.

After creating a report in Power BI Desktop, you publish it to the Power BI Service. Updates are made by republishing the report. You can schedule data refresh, manage permissions, and share reports with users in the service.

Many-to-many relationships are managed using bridge tables or by leveraging the composite model feature. This ensures accurate aggregations and avoids data duplication or ambiguity in relationships.

'Edit Interactions' allows you to control how visuals on a report page interact with each other. You can specify whether a visual filters, highlights, or does not affect other visuals, enabling customized user experiences.

Import mode loads data into Power BI's in-memory model for fast performance, while DirectQuery leaves data in the source and queries it in real time. DirectQuery is suitable for large datasets but may have performance and feature limitations.

Drill-through enables users to right-click on a data point and navigate to a detailed report page filtered for that context. You set up drill-through by creating a dedicated page and adding relevant fields to the drill-through filters.

Custom visuals are user-created or third-party visuals that extend Power BI's default visualization options. You can import them from the AppSource marketplace or develop your own using the Power BI Visuals SDK.

Parameters allow users to dynamically change values used in queries, filters, or calculations. They are useful for scenario analysis, what-if analysis, and making reports more interactive and flexible.

CALCULATE modifies the context in which a DAX expression is evaluated by applying filters. It is essential for creating complex measures and performing context transitions in calculations.

Troubleshooting involves checking error messages, verifying data source credentials, ensuring gateway connectivity, and reviewing query performance. The Power BI Service provides detailed logs and notifications for refresh issues.

The Power BI Gateway acts as a bridge between on-premises data sources and the Power BI Service. It is required for scheduled refresh or live queries against on-premises databases from the cloud.

Power BI Aggregations allow you to create summary tables that improve query performance by reducing the amount of data scanned. Unlike traditional data modeling, which relies on detailed tables and relationships, aggregations optimize large datasets for faster analysis, especially in DirectQuery scenarios.

Incremental data refresh enables you to refresh only new or changed data rather than the entire dataset. This is configured in Power BI Desktop using parameters and range filters, and then published to the Power BI Service. It significantly reduces refresh time and resource consumption for large datasets.

Composite Models allow you to combine data from multiple sources, such as Import and DirectQuery, within a single report. This enables flexibility in data modeling, letting you balance performance and real-time data access, and is useful when working with both historical and live data.

Optimizing DAX involves minimizing row context transitions, avoiding complex calculated columns, using variables to store intermediate results, and leveraging built-in functions like SUMX or FILTER efficiently. Monitoring with DAX Studio and Performance Analyzer helps identify bottlenecks.

Enterprise deployment involves version control, using deployment pipelines, separating development, test, and production workspaces, and automating report publishing with tools like Power BI REST API or Azure DevOps. Security, governance, and documentation are also critical.

Advanced RLS uses DAX functions like USERNAME() or USERPRINCIPALNAME() to filter data dynamically based on the logged-in user. You can maintain a mapping table of users and roles, and apply DAX filters to restrict data access at a granular level.

Calculation groups, created in Tabular Editor, allow you to define reusable calculations (such as time intelligence) that can be applied across multiple measures. This reduces redundancy, simplifies maintenance, and enables advanced analytics scenarios.

The Power BI REST API provides endpoints for automating tasks such as uploading PBIX files, refreshing datasets, managing workspaces, and assigning permissions. It is commonly used in CI/CD pipelines and for integrating Power BI with other enterprise systems.

Circular dependencies occur when calculated columns or measures reference each other in a loop. To resolve them, refactor calculations to remove direct references, use variables, or redesign the data model to eliminate ambiguous relationships.

Azure Analysis Services and Power BI Premium provide dedicated resources for hosting large tabular models, supporting higher dataset sizes, faster refresh rates, and advanced features like XMLA endpoints for programmatic access and management.

Power BI provides audit logs, usage metrics, and activity reports in the Power BI Service and Microsoft 365 compliance center. These tools help track report access, sharing, data exports, and user activities for governance and compliance.

Embedding Power BI reports involves generating embed tokens using the Power BI REST API, configuring authentication (such as Azure AD), and using the Power BI JavaScript SDK to render reports within web or mobile applications, enabling interactive analytics for end users.

DirectQuery mode is limited by source system performance, query complexity, and certain unsupported DAX functions or features. Mitigation strategies include optimizing source queries, using aggregations, limiting visuals, and caching frequently accessed data.

Advanced time intelligence uses DAX functions like SAMEPERIODLASTYEAR, PARALLELPERIOD, and DATESBETWEEN to create custom period comparisons, rolling averages, and YTD/QTD/MTD calculations. Calculation groups can further streamline these measures.

Troubleshooting involves using Performance Analyzer to identify slow visuals, optimizing DAX queries, reducing the number of visuals, simplifying data models, and monitoring dataset refresh times. Tools like DAX Studio and SQL Profiler can help analyze query performance in detail.