Power BI Interview Questions & Detailed Answers

1. What is Power BI?

Answer:
Power BI is a Microsoft business intelligence tool used to transform raw data into meaningful insights. It allows for data visualization, dashboard creation, and interactive reporting.

Scenario: A retail company can track daily sales per store, top-selling products, and inventory levels, all in interactive dashboards.

SEO Tip: Use phrases like Power BI analytics, Power BI dashboard creation.

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2. What are the main components of Power BI?

Answer:
Power BI has five main components:

1. Power BI Desktop – Used to connect to data sources, create reports, and perform modeling.

2. Power BI Service (Cloud) – Allows sharing dashboards and collaborating online.

3. Power BI Mobile – View reports on phones or tablets.

4. Power BI Gateway – Connects on-premises data sources to the cloud.

5. Power BI Report Server – Stores reports on-premises for organizations with security needs.

Diagram:

graph LR
A[Power BI Desktop] --> B[Power BI Service]
B --> C[Mobile Access]
B --> D[Collaborate & Share]

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3. What are the data sources Power BI supports?

Answer:
Power BI can connect to cloud and on-premises data. Examples:

• Files: Excel, CSV, XML, JSON

• Databases: SQL Server, Oracle, MySQL

• Cloud services: Azure, Salesforce, Google Analytics

• Web APIs: REST APIs

Scenario: Connecting Power BI to an Azure SQL database allows you to track real-time sales data for analysis.

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4. Difference between Power BI Desktop, Service, and Mobile

Answer:

Scenario: Create a report in Desktop, publish to Service, view on Mobile app.

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5. What is DAX?

Answer:
Data Analysis Expressions (DAX) is used in Power BI to perform calculations and create measures. It works on tabular data models.

Example: Calculate total sales dynamically:

TotalSales = SUM(Sales[Amount])

Scenario: Use DAX to create YTD Sales or Profit Margin measures.

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6. What is Power Query?

Answer:
Power Query is the ETL tool in Power BI: Extract, Transform, Load. It helps in:

• Cleaning data (removing nulls, duplicates)

• Merging tables

• Transforming formats

Example: Remove duplicate customer rows from a CSV:

let
    Source = Csv.Document(File.Contents("Customers.csv"),[Delimiter=",", Columns=5, Encoding=1252, QuoteStyle=QuoteStyle.None]),
    RemoveDuplicates = Table.Distinct(Source)
in
    RemoveDuplicates

Scenario: Combine sales data from multiple Excel files into a single dataset.

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7. Difference between Calculated Column & Measure

Answer:

Example:

-- Calculated Column
ProfitMargin = Sales[Profit]/Sales[Amount]

-- Measure
TotalProfit = SUM(Sales[Profit])

Scenario: Use a calculated column to show profit margin per transaction, use a measure for total profit on a dashboard.

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8. What are Power BI visualizations?

Answer: Visualizations allow you to represent data graphically. Types include:

• Bar, column, line, pie charts

• Maps (ArcGIS, Shape maps)

• KPI cards, tables, matrices

Scenario: Show monthly sales per region with a stacked bar chart, add a map visualization for regional sales distribution.

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9. What is a dashboard in Power BI?

Answer: A dashboard is a single-page, interactive view combining multiple visualizations or tiles.

Scenario: Combine KPI cards, charts, and maps to monitor sales, inventory, and marketing KPIs.

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10. What is Row-Level Security (RLS)?

Answer: RLS restricts access to data for specific users based on roles.

Scenario:

• Sales Manager in East region sees only East region data.

• Sales Manager in West region sees only West region data.

Diagram:

graph LR
A[All Sales Data] --> B[East Region Role]
A --> C[West Region Role]
B --> D[East Manager View]
C --> E[West Manager View]

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11. Explain Power BI architecture.

Answer: Power BI architecture has three layers:

1. Data Layer: Connects to various data sources

2. Data Transformation Layer: Cleans and models data using Power Query & DAX

3. Visualization Layer: Creates reports & dashboards

Diagram:

flowchart LR
A[Data Sources] --> B[Transformation (Power Query/DAX)]
B --> C[Data Model]
C --> D[Reports & Dashboards]

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12. Difference between Import mode and DirectQuery

Scenario: Use DirectQuery for live database dashboards; Import mode for smaller datasets with heavy calculations.

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13. What is the use of Power BI Gateway?

Answer: Connects on-premises data sources to Power BI Service, allowing scheduled or live refreshes.

Scenario: SQL Server database in office → refresh sales dashboards in Power BI cloud service.

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14. Difference between Power BI and Excel

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15. Explain the term “Data Modeling” in Power BI

Answer: Data modeling organizes data into tables, relationships, and hierarchies for efficient analysis.

Scenario:

• FactSales table connects to DimProduct, DimCustomer, DimDate for analysis.

Diagram:

graph LR
FactSales --> DimProduct
FactSales --> DimCustomer
FactSales --> DimDate

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16. What are slicers in Power BI?

Answer: Interactive filters that allow users to select specific values for visualization.

Example: Date slicer to filter sales by month.

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17. Difference between a Table and Matrix visual

• Table: Simple grid, static, row-wise

• Matrix: Allows row and column hierarchies, supports drill-down

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18. Explain Drill-through in Power BI

Answer: Drill-through allows users to navigate to a detailed report page from a selected data point.

Scenario: Click on East Region sales bar → drill-through page shows all East Region transactions.

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19. What is Q&A in Power BI?

Answer: Natural language query that generates visualizations automatically.

Example: Type “Total sales by region for 2025” → Power BI generates a chart dynamically.

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20. How to handle large datasets in Power BI?

Answer:

• Use DirectQuery

• Remove unnecessary columns & rows

• Use aggregations

• Optimize DAX measures

• Apply incremental refresh for large datasets

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Hard Questions (21–30)

21. How to optimize Power BI performance?

Answer:

• Use star schema for modeling

• Avoid calculated columns if possible

• Reduce visuals per page

• Aggregate data where feasible

• Optimize DAX formulas

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22. What is a Star Schema?

Answer: Central fact table connects to multiple dimension tables for optimized reporting.

Diagram:

graph LR
FactSales --> DimProduct
FactSales --> DimCustomer
FactSales --> DimDate

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23. Difference between SUM and SUMX

-- SUM
SUM(Sales[Amount])

-- SUMX: Row-wise
SUMX(Sales, Sales[Quantity]*Sales[UnitPrice])

Answer: SUMX allows row-wise calculations, SUM aggregates a column.

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24. What is a calculated table?

TopProducts = FILTER(Products, Products[Sales] > 1000)

Answer: A table created dynamically using DAX formulas.

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25. Drill-down vs Drill-through

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26. How to implement dynamic titles in Power BI?

Title = "Sales for " & SELECTEDVALUE(Product[Category])

• Updates automatically based on slicer selection.

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27. Dynamic Row-Level Security

[Region] = USERPRINCIPALNAME()

• Filters rows based on logged-in user.

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28. Explain Aggregations in Power BI

Answer: Pre-calculated summaries improve query performance.

Scenario: Aggregate daily sales to monthly totals to reduce processing time.

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29. Connect Power BI to Python/R

Answer: Use Python/R scripts in Power Query to process data or create custom visuals.

import pandas as pd
dataset = pd.read_csv('Sales.csv')
dataset['ProfitMargin'] = dataset['Profit']/dataset['Amount']

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30. What is incremental data refresh?

Answer: Only refresh new or modified rows, improving performance on large datasets.

Scenario: For a 10 million row sales dataset, refresh only last month’s data.