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Top Interview Questions
Power BI is a powerful business intelligence (BI) and data visualization tool developed by Microsoft that enables organizations to transform raw data into meaningful insights. It helps businesses analyze data, create interactive reports and dashboards, and make data-driven decisions with ease. Power BI is widely used across industries because of its user-friendly interface, strong integration with multiple data sources, and advanced analytics capabilities.
Power BI is a suite of software services, apps, and connectors that work together to convert data from various sources into visually immersive and interactive insights. It allows users to connect to data, model it, and create reports that can be shared across an organization. Power BI supports both technical users like data analysts and developers, as well as non-technical users such as managers and business users.
Power BI is part of the Microsoft Power Platform, which also includes Power Apps, Power Automate, and Power Virtual Agents. This integration makes Power BI a central tool for analytics and reporting within the Microsoft ecosystem.
Power BI consists of several key components that work together to deliver end-to-end business intelligence solutions:
Power BI Desktop is a free Windows application used to connect to data sources, transform and clean data, create data models, and design reports. It provides a rich set of tools for data shaping using Power Query and for creating complex calculations using DAX (Data Analysis Expressions).
The Power BI Service is a cloud-based platform where reports created in Power BI Desktop are published. It allows users to create dashboards, schedule data refreshes, collaborate with others, and share reports securely.
Power BI mobile applications are available for Android, iOS, and Windows devices. These apps allow users to access dashboards and reports on the go, ensuring real-time insights anytime, anywhere.
The Power BI Gateway enables secure data transfer between on-premises data sources and the Power BI Service. It is especially useful for organizations that store data in local databases but want cloud-based reporting.
One of the major strengths of Power BI is its ability to connect to a wide variety of data sources. These include:
Relational databases such as SQL Server, Oracle, MySQL, and PostgreSQL
Cloud platforms like Azure SQL Database, Azure Data Lake, and Google BigQuery
Files such as Excel, CSV, XML, and JSON
Online services like SharePoint, Salesforce, Dynamics 365, and Google Analytics
Big data sources such as Hadoop and Spark
This flexibility allows organizations to consolidate data from multiple systems into a single analytical platform.
Power BI provides powerful data transformation and modeling capabilities that help prepare data for analysis.
Power Query is used for data extraction, transformation, and loading (ETL). It allows users to clean data, remove duplicates, merge tables, split columns, and apply business rules without writing complex code.
After data is transformed, Power BI enables users to create relationships between tables, define hierarchies, and optimize the data model. A well-designed data model improves performance and simplifies report creation.
DAX is a formula language used in Power BI to create calculated columns, measures, and custom aggregations. It allows users to perform complex calculations such as year-over-year growth, running totals, and time intelligence analysis.
Power BI is best known for its rich and interactive data visualizations. It provides a wide range of built-in visuals, including:
Bar and column charts
Line and area charts
Pie and donut charts
Tables and matrices
Maps and geospatial visuals
KPI indicators and gauges
Users can also import custom visuals from the Power BI marketplace or build their own visuals using development tools. Interactive features like slicers, filters, drill-downs, and drill-throughs allow users to explore data in depth and gain actionable insights.
Dashboards in Power BI provide a high-level view of business performance by combining visuals from multiple reports onto a single screen. These dashboards are interactive and update automatically when the underlying data changes.
Power BI offers robust sharing and collaboration features. Reports and dashboards can be shared with colleagues, embedded into websites or applications, or exported to formats such as PDF and PowerPoint. Role-based security ensures that users only see the data they are authorized to access.
Security is a critical aspect of Power BI. It includes features such as:
Row-Level Security (RLS): Restricts data visibility based on user roles
Azure Active Directory Integration: Ensures secure authentication and access control
Data Encryption: Protects data both at rest and in transit
Compliance Certifications: Supports standards like ISO, GDPR, and SOC
These features make Power BI suitable for enterprise-level deployments with strict data governance requirements.
Power BI includes advanced analytics and artificial intelligence features that enhance data analysis:
Built-in AI visuals such as Key Influencers and Decomposition Tree
Integration with Azure Machine Learning
Natural language queries using Q&A
Forecasting and anomaly detection
These capabilities help users uncover hidden patterns and trends without deep statistical or programming knowledge.
Power BI offers several benefits that make it a popular BI tool:
Easy to use with minimal learning curve
Seamless integration with Microsoft products
Scalable for small businesses and large enterprises
Cost-effective compared to many traditional BI tools
Strong community support and frequent updates
Power BI is used across various domains, including:
Sales and marketing performance analysis
Financial reporting and budgeting
Supply chain and inventory management
Human resources analytics
Customer behavior and trend analysis
Organizations use Power BI to monitor KPIs, track performance, and support strategic decision-making.
Answer:
Power BI is a Business Intelligence (BI) tool developed by Microsoft that helps users collect, transform, analyze, and visualize data. It allows businesses to create interactive reports and dashboards from multiple data sources, enabling better decision-making.
Power BI converts raw data into meaningful insights using charts, tables, KPIs, and maps. It is widely used because of its ease of use, integration with Microsoft products, and strong data visualization capabilities.
Answer:
Power BI consists of the following components:
Power BI Desktop – Used to create reports and data models.
Power BI Service (PowerBI.com) – Cloud service to publish and share reports.
Power BI Mobile Apps – Used to view dashboards on mobile devices.
Power BI Gateway – Connects on-premises data sources to Power BI Service.
Power BI Report Server – On-premises solution for hosting reports.
Answer:
Power BI Desktop is a Windows-based application used for:
Connecting to data sources
Transforming data using Power Query
Creating data models
Designing reports and visualizations
After creating reports, users publish them to Power BI Service.
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Power BI supports a wide range of data sources such as:
Excel
CSV files
SQL Server
Oracle
MySQL
PostgreSQL
Azure SQL Database
SharePoint
Web APIs
Google Analytics
Salesforce
This flexibility allows integration with both on-premises and cloud data.
Answer:
Power Query is a data transformation and preparation tool in Power BI. It allows users to:
Clean data
Remove duplicates
Merge and append tables
Change data types
Filter rows
Power Query uses M language behind the scenes.
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DAX (Data Analysis Expressions) is a formula language used in Power BI for calculations and data analysis. It is mainly used to create:
Calculated columns
Measures
Calculated tables
Example:
Total Sales = SUM(Sales[Amount])
Answer:
| Calculated Column | Measure |
|---|---|
| Stored in the table | Calculated at runtime |
| Uses row context | Uses filter context |
| Increases data size | Does not increase size |
| Used for row-level calculations | Used for aggregations |
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A dashboard is a single-page view that shows important KPIs and visuals. Dashboards are created in Power BI Service by pinning visuals from multiple reports.
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A report is a multi-page collection of visualizations created in Power BI Desktop. Reports provide detailed insights and interactive analysis.
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| Dashboard | Report |
|---|---|
| Single page | Multiple pages |
| Created in Power BI Service | Created in Power BI Desktop |
| Read-only | Highly interactive |
| Combines visuals from multiple reports | Based on a single dataset |
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A dataset is a collection of data tables and relationships that Power BI uses to create reports and dashboards.
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Data modeling is the process of:
Creating relationships between tables
Defining keys
Optimizing schema for analysis
Power BI mainly uses a Star Schema for best performance.
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Relationships connect tables using common columns (primary and foreign keys). Types:
One-to-Many
Many-to-Many
One-to-One
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A Star Schema consists of:
One fact table (sales, transactions)
Multiple dimension tables (customer, product, date)
It improves performance and simplifies data analysis.
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Filters are used to restrict data shown in visuals.
Types:
Visual-level filters
Page-level filters
Report-level filters
Slicers (interactive filters)
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A slicer is a visual filter that allows users to filter data interactively using dropdowns, buttons, or lists.
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Visualizations are graphical representations of data such as:
Bar chart
Line chart
Pie chart
Table
Matrix
KPI
Map
Card
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Refresh updates data in reports from the source.
Types:
Manual refresh
Scheduled refresh
Automatic refresh
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Power BI Gateway enables secure data transfer between on-premises data sources and Power BI Service.
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Roles define Row-Level Security (RLS) to restrict data access. Users see only data allowed by their role.
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RLS restricts data access at row level based on user roles. It is implemented using DAX filters.
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Q&A allows users to ask questions in natural language and get answers as visuals.
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KPI (Key Performance Indicator) measures business performance using metrics like:
Target
Actual value
Status indicator
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Publishing uploads reports from Power BI Desktop to Power BI Service so they can be shared with others.
Answer:
Easy to use
Real-time dashboards
Strong Microsoft integration
Affordable pricing
Cloud and on-premises support
Answer:
Dataset size limits
Complex DAX learning curve
Performance issues with poor data models
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| Power BI | Tableau |
|---|---|
| Lower cost | More expensive |
| Strong Microsoft integration | Strong visualization |
| Uses DAX | Uses Tableau calculations |
Answer:
SQL
Excel
Data modeling
DAX
Data visualization concepts
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Excel is used as:
A data source
A reporting tool integrated with Power BI
For quick data analysis
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Power BI helps organizations make data-driven decisions by providing real-time insights, interactive dashboards, and easy data analysis.
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| Import Mode | DirectQuery |
|---|---|
| Data is stored in Power BI | Data stays in source |
| Faster performance | Slower compared to Import |
| Requires refresh | Real-time data |
| Limited dataset size | Depends on source |
Import mode is recommended for better performance, while DirectQuery is used when real-time data is required.
Answer:
Live Connection connects Power BI directly to:
SSAS
Azure Analysis Services
Power BI datasets
Data modeling is done in the source system, not in Power BI.
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Power Query Editor is used to clean and transform data before loading it into Power BI. It helps in:
Removing null values
Splitting columns
Changing data types
Merging and appending tables
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M Language is a functional language used in Power Query. It defines data transformation steps.
Example:
= Table.RemoveRowsWithErrors(Source)
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A Fact Table stores transactional data such as:
Sales
Revenue
Quantity
Profit
It contains foreign keys that link to dimension tables.
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Dimension tables contain descriptive attributes such as:
Customer
Product
Date
Location
They provide context to the fact table.
Answer:
Cardinality defines the relationship type between tables:
One-to-One
One-to-Many
Many-to-Many
Correct cardinality improves performance and accuracy.
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It determines how filters flow between tables:
Single direction
Both directions
Single direction is recommended for better performance.
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A measure is a dynamic calculation evaluated at runtime based on filters.
Example:
Total Profit = SUM(Sales[Profit])
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Filter context refers to filters applied to data through:
Slicers
Filters pane
Visual interactions
Measures respond to filter context.
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Row context means calculations are done row by row, mainly used in calculated columns.
Answer:
COUNT – Counts numeric values
COUNTA – Counts non-null values
DISTINCTCOUNT – Counts unique values
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CALCULATE changes the filter context of a measure.
Example:
Total Sales India = CALCULATE(SUM(Sales[Amount]), Sales[Country] = "India")
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ALL removes filters from a column or table.
Example:
Total Sales All = CALCULATE(SUM(Sales[Amount]), ALL(Sales))
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A Date Table is used for time intelligence such as:
Year-to-Date (YTD)
Month-over-Month (MoM)
Year-over-Year (YoY)
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Time Intelligence functions analyze data over time.
Examples:
TOTALYTD
SAMEPERIODLASTYEAR
DATEADD
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Hierarchy allows drill-down analysis such as:
Year → Quarter → Month → Day
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Drill Down: Navigate within the same visual
Drill Through: Navigate to another page with detailed data
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Conditional formatting highlights data using colors, bars, or icons based on rules.
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Bookmarks capture the current state of a report, including filters and visuals, useful for storytelling.
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Performance Analyzer helps measure:
Visual load time
DAX query time
Report performance
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A workspace is a collaboration area where reports, datasets, and dashboards are shared.
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An App is a packaged collection of reports and dashboards shared with users.
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Sensitivity labels classify data as:
Public
Confidential
Highly Confidential
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Data lineage shows data flow from source to report, helping in impact analysis.
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Custom visuals are additional visuals downloaded from AppSource.
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Users can export visuals or data to:
Excel
PowerPoint
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Embedding allows Power BI reports to be integrated into web or mobile applications.
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AI visuals provide advanced insights like:
Key Influencers
Decomposition Tree
Smart Narrative
Answer:
Use star schema
Reduce columns
Use measures instead of calculated columns
Avoid bi-directional relationships
Use Import mode
Answer:
Cleaning messy Excel data
Creating sales dashboard
Applying filters and slicers
Writing basic DAX
Publishing reports
Answer:
| Free | Pro |
|---|---|
| Create reports | Share reports |
| Personal use | Collaboration |
| No sharing | Requires license |
Answer:
Incremental refresh updates only new or changed data, improving refresh performance.
Answer:
Data View: See tables and columns
Model View: Manage relationships
Report View: Create visuals
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It allows developers to automate Power BI tasks like publishing reports.
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Usage metrics show how users interact with reports.
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Composite model combines:
Import
DirectQuery
Live connection
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On-object interaction allows direct editing of visuals.
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Tooltips show extra information when hovering over visuals.
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Because it is:
Easy to learn
Cost-effective
Highly interactive
Strong Microsoft ecosystem support
Answer:
Power BI architecture includes:
Data Sources – SQL Server, Azure, Excel, APIs, etc.
Power Query (ETL layer) – Data extraction, transformation using M language.
Data Model (VertiPaq Engine) – Columnar, in-memory storage optimized for fast analytics.
DAX Engine – Performs calculations and aggregations.
Power BI Service – Cloud hosting, sharing, refresh, security.
Visualization Layer – Reports, dashboards, apps.
Answer:
VertiPaq is an in-memory columnar storage engine that:
Compresses data using encoding
Stores data by columns, not rows
Scans only required columns during queries
This results in high performance and low memory usage.
Answer:
| Import | DirectQuery | Live |
|---|---|---|
| Data stored in memory | Data queried from source | Model in external source |
| Best performance | Real-time | Centralized model |
| Needs refresh | No refresh | No modeling in Power BI |
Answer:
Composite model allows combining Import + DirectQuery + Live in a single model.
Used when:
Historical data is imported
Real-time data is queried live
Answer:
RLS restricts data at row level using DAX filters.
Scenario:
Sales managers should see only their region’s data.
[Region] = USERPRINCIPALNAME()
Roles are created in Power BI Desktop and applied in Service.
Answer:
| Static RLS | Dynamic RLS |
|---|---|
| Hardcoded values | User-based filtering |
| Not scalable | Highly scalable |
| Manual updates | Automatic mapping |
Answer:
Row context: Calculation per row (calculated column)
Filter context: Filters applied by slicers, visuals
Total Sales = SUM(Sales[Amount])
This responds to filter context, not row context.
Answer:
CALCULATE modifies filter context and is the most powerful DAX function.
Sales India =
CALCULATE(SUM(Sales[Amount]), Sales[Country] = "India")
Answer:
Context transition converts row context to filter context, mainly triggered by CALCULATE.
Answer:
ALL: Removes all filters
ALLEXCEPT: Keeps selected filters
% Contribution =
DIVIDE(
SUM(Sales[Amount]),
CALCULATE(SUM(Sales[Amount]), ALL(Sales))
)
Answer:
| SUM | SUMX |
|---|---|
| Aggregates column | Row-by-row calculation |
| Faster | More flexible |
Answer:
Star schema:
One fact table
Multiple dimension tables
Benefits:
Faster queries
Simpler DAX
Better compression
Answer:
Use star schema
Remove unused columns
Avoid calculated columns
Reduce cardinality
Use measures
Optimize relationships
Use Performance Analyzer
Answer:
Cardinality defines relationship type. High cardinality columns increase memory and reduce performance.
Answer:
Incremental refresh
Aggregation tables
DirectQuery for real-time data
Partitioning
Composite models
Answer:
Refreshes only new or modified data instead of entire dataset, reducing refresh time.
Answer:
Aggregations pre-summarize data to improve performance when using DirectQuery.
Answer:
Columns increase model size
Measures are evaluated at query time
Measures respond to filters dynamically
Answer:
YTD Sales = TOTALYTD(SUM(Sales[Amount]), Date[Date])
Used for:
YTD
YoY
MoM analysis
Answer:
Date table ensures:
Accurate time calculations
Proper relationships
Performance optimization
Answer:
Allows navigating from summary to detailed report pages.
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Dashboards are read-only, while reports support:
Drill down
Tooltips
Cross-filtering
Answer:
Gateway securely transfers data from on-premises sources to Power BI Service.
Answer:
Using Deployment Pipelines:
Dev
Test
Prod
Answer:
Apps package content securely for end users with controlled access.
Answer:
Labels classify data and enforce security policies across Microsoft ecosystem.
Answer:
Helps track:
Report usage
User engagement
Optimization opportunities
Answer:
Custom visuals add flexibility but may cause:
Performance issues
Security risks
Answer:
Store PBIX in Git
Use separate workspaces
Follow naming standards
Answer:
Securing regional sales data
Optimizing slow reports
Handling 100M+ records
Designing enterprise dashboards
Answer:
Power BI excels in cost and Microsoft integration, while Tableau leads in visualization depth.
Answer:
Use DAX Studio
Analyze query plans
Simplify calculations
Answer:
Measures visual, DAX, and rendering performance.
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Tracks dependencies across datasets, reports, and dashboards.
Answer:
Strong fundamentals in:
Data modeling
DAX optimization
Performance tuning
Security
Business understanding
Answer:
Power BI Service – Cloud-based, supports sharing, dashboards, and collaboration. Requires internet.
Power BI Report Server – On-premises, hosts reports and dashboards internally. Supports paginated reports, ideal for regulated environments.
Answer:
Dynamic RLS uses a mapping table to control access based on the user.
Example:
Create a table with UserEmail and Region.
Define DAX filter in the role:
[Region] = LOOKUPVALUE(UserRegion[Region], UserRegion[Email], USERPRINCIPALNAME())
This allows dynamic user-based filtering.
Answer:
| Single Direction | Both Directions |
|---|---|
| Filter flows one way | Filter flows both ways |
| Recommended for performance | Use carefully, can create ambiguity |
| Default in star schema | Required in snowflake or advanced scenarios |
Answer:
A composite model can use multiple storage modes:
Import mode – data stored in Power BI
DirectQuery mode – queries sent to source
Dual mode – acts as Import for local calculations but DirectQuery for external queries.
Useful for large datasets with summary + detail combination.
Answer:
Avoid calculated columns; use measures
Use SUMX / FILTER efficiently
Reduce context transition when possible
Use variables (VAR) to store intermediate results
Avoid heavy row-by-row calculations on large tables
Answer:
Variables improve:
Performance – evaluates once per row/context
Readability – cleaner formulas
Example:
VAR TotalSales = SUM(Sales[Amount])
RETURN
TotalSales * 0.1
Answer:
USERNAME() – Returns Domain\Username, used in old versions
USERPRINCIPALNAME() – Returns email ID, standard in dynamic RLS
Answer:
ALL() – Removes all filters from a table or column
REMOVEFILTERS() – Explicitly removes filters from specified columns
ALLEXCEPT() – Removes all filters except those specified
Answer:
Configure parameters: RangeStart, RangeEnd
Enable incremental refresh on the table
Choose store historical data and refresh only recent data
Ideal for large fact tables (>10M rows)
Answer:
Aggregations precompute summary data for DirectQuery tables.
Improves performance for large datasets
Power BI automatically uses aggregations if configured
Works with Import + DirectQuery in composite models
Answer:
Check query performance in Performance Analyzer
Remove unnecessary columns and tables
Use star schema
Optimize DAX formulas
Use aggregations and incremental refresh
Reduce visuals on a page
Answer:
Use DAX Studio to analyze query plans
Use Evaluate Table to check intermediate results
Test with smaller datasets
Check filter and row contexts
Answer:
TOTALYTD – Year-to-date
DATESYTD – Date table version
SAMEPERIODLASTYEAR – YoY comparison
DATEADD – Shift dates
PARALLELPERIOD – Previous period comparison
Answer:
Composite key = combination of multiple columns as primary key
Handled by creating a calculated column or concatenated key
Example:
CustomerProductKey = Customer[ID] & "-" & Product[ID]
Answer:
Control how visuals affect each other using Edit interactions
Configure highlight, filter, or none
Improves usability for complex dashboards
Answer:
Use Power BI workspaces: Dev, Test, Production
Apply Deployment Pipelines
Manage permissions and RLS before publishing
Version control PBIX files in Git
Answer:
Create a Currency table with exchange rates
Use DAX measure to convert amounts dynamically:
Amount in USD = SUMX(Sales, Sales[Amount] * RELATED(Currency[Rate]))
Answer:
REST API allows automation:
Publish PBIX
Manage datasets
Refresh datasets programmatically
Embed reports in apps
Answer:
Dataflows store ETL logic in the cloud, allowing:
Centralized data preparation
Reuse across multiple datasets
Supports incremental refresh
Answer:
Store PBIX in Git or SharePoint
Use deployment pipelines for Dev/Test/Prod
Maintain naming standards and documentation
Answer:
Key Influencers – Identify drivers of a metric
Decomposition Tree – Breaks down values by categories
Smart Narrative – Generates automatic insights
Anomaly Detection – Detects trends and outliers
Answer:
Classify data as Public, Confidential, Highly Confidential
Enforces encryption, access control, and compliance policies
Answer:
Use DirectQuery or Composite Models
Incremental refresh
Aggregation tables
Star schema
Avoid high-cardinality columns
Answer:
Usage metrics track report/dashboard usage
Power BI Admin Portal tracks dataset refresh, user access, performance
Helps identify optimization areas
Answer:
Use star schema with Sales fact + Customer, Product, Date dimensions
Implement dynamic RLS for regional managers
Use slicers for interactive filtering
Include KPIs, charts, drill-down, and tooltips
Optimize performance with measures and incremental refresh
