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Advanced Power BI Certification Course with GenAI
Advanced Power BI Certification Course with GenAI
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Why enroll for Advanced Power BI Certification Course with GenAI?
Advanced Power BI with GenAI Training Benefits
Organizations are prioritizing data-driven decision-making, and BI professionals who can transform data into actionable insights using Power BI are highly sought after. By completing Edureka’s Power BI program, learners gain skills that directly map to these in-demand roles, improving employability and potential earnings in a rapidly expanding analytics market.
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Why Advanced Power BI Certification Course with GenAI from edureka
Live Interactive Learning
- World-Class Instructors
- Expert-Led Mentoring Sessions
- Instant doubt clearing
24x7 Support
- One-On-One Learning Assistance
- Help Desk Support
- Resolve Doubts in Real-time
Hands-On Project Based Learning
- Industry-Relevant Projects
- Course Demo Dataset & Files
- Quizzes & Assignments
Industry Recognised Certification
- Edureka Training Certificate
- Graded Performance Certificate
- Certificate of Completion
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About your Advanced Power BI Certification Course with GenAI
Advanced Power BI Skills Covered
Advanced Power BI Tools Covered
Advanced Power BI Course Curriculum
Curriculum Designed by Experts
Module 1: Introduction to Business Intelligence and Power BI Ecosystem
7 Topics
Topics
- BI Fundamentals
- Modern Analytics Landscape
- Power BI Ecosystem: Desktop, Service, Mobile, Report Server
- Licensing Models, Governance & Architecture
- Integration with Microsoft 365, Teams & SharePoint
- Power BI Data Flow
- Architecture Deep Dive
![skill]( "Hands On Experience")
- Install & configure Power BI Desktop
- Navigate the Desktop interface components
- Build your first report with sample data
![skill]( "skill you will learn")
- Power BI ecosystem navigation
- Understanding BI data flows
- Licensing & governance basics
Module 2: Data Source Connectivity and Data Preparation Fundamentals
9 Topics
Topics
- Connecting to Flat Files: Excel, CSV, JSON, XML, PDF
- Relational Database Connections: SQL Server, MySQL, PostgreSQL, Oracle
- Cloud Data Sources: Azure SQL, Azure Synapse, AWS Redshift
- Online Services: SharePoint, Google Analytics, Salesforce
- Web APIs, REST Endpoints & OData Feeds
- Data Source Parameters & Dynamic Connections
- Import Mode vs DirectQuery vs Live Connection vs Composite
- Configuring On-Premises & Cloud Data Gateways
- Data Source Credentials Management & Security Best Practices
![skill]( "Hands On Experience")
- Connect to multiple heterogeneous data sources
- Build hybrid model with Import + DirectQuery
- Extract data from REST APIs
- Set up parameters for dynamic source connections
![skill]( "skill you will learn")
- Multi-source data connectivity
- Hybrid connectivity modeling
- Gateway configuration management
- Secure credential handling
- Connectivity mode optimization
Module 3: Power Query Editor - Data Transformation Mastery
9 Topics
Topics
- Power Query interface and Applied Steps
- Data Profiling for Quality Assurance
- Data type detection and conversion
- Column operations (split, merge, pivot, unpivot)
- Filtering, sorting, and removing duplicates
- Text transformations and pattern matching
- Date and time operations
- Conditional columns and custom calculations
- Advanced Editor and M Code Fundamentals
![skill]( "Hands On Experience")
- Clean messy sales data with inconsistent formats
- Transform wide-format data to long-format
- Create custom columns using conditional logic
- Extract data from nested JSON structures
- Build reusable data transformation templates
- Handle null values and data quality issues
![skill]( "skill you will learn")
- M code development
- Data profiling techniques
- Query transformation pipelines
- Error handling logic
- Data cleansing workflows
Module 4: Advanced Power Query - Data Shaping and Integration
8 Topics
Topics
- Merging queries (inner, left, right, full outer joins)
- Appending queries and union operations
- Query folding and performance optimization
- Parameters for dynamic filtering
- Custom functions creation
- Query dependencies management
- Error handling and data validation
- Fuzzy matching and approximate joins
![skill]( "Hands On Experience")
- Combine data from multiple regional files
- Create a date dimension table using M functions
- Build parameterized queries for dynamic reporting
- Implement fuzzy merge for customer matching
- Develop custom functions for reusable logic
- Optimize slow-performing queries
![skill]( "skill you will learn")
- Advanced query merging
- Reusable M functions
- Query folding optimization
- Dynamic parameter modeling
- Fuzzy data reconciliation
Module 5: Data Modeling Fundamentals
8 Topics
Topics
- Star schema vs. snowflake schema
- Fact tables and dimension tables
- Primary and foreign keys
- Relationship types (one-to-many, many-to-many)
- Cardinality and cross-filter direction
- Active vs. inactive relationships
- Role-playing dimensions
- Model Optimization and Performance Tuning
![skill]( "Hands On Experience")
- Design a sales data model with proper relationships
- Create a date dimension with hierarchies
- Build a customer dimension with attributes
- Implement role-playing dimensions (order date, ship date)
- Resolve many-to-many relationships
- Document data model using diagrams
![skill]( "skill you will learn")
- Dimensional model design
- Relationship configuration
- Role-playing implementation
- Model performance tuning
Module 6: DAX Fundamentals
10 Topics
Topics
- DAX Syntax, Operators, and Expressions
- Data Types and Type Conversion
- Working with Tables and Columns
- Calculated columns vs. measures
- Basic aggregation functions (SUM, AVERAGE, COUNT, MIN, MAX)
- Simple Implicit vs. explicit measures
- RELATED and RELATEDTABLE functions
- Logical and Conditional Functions
- Basic date and time functions
- Understanding Auto Date/Time
![skill]( "Hands On Experience")
- Create calculated columns for data categorization
- Build basic KPI measures (Total Sales, Profit Margin)
- Calculate running totals and cumulative values
- Create rank-based calculated columns
- Implement percentage calculations
![skill]( "skill you will learn")
- DAX expression writing
- Row vs filter context
- KPI measure development
- Cross-table calculations
- Aggregation logic implementation
Module 7: Advanced DAX
8 Topics
Topics
- Evaluation Context and Context Transition
- CALCULATE function advanced usage
- ALL, ALLEXCEPT, ALLSELECTED functions
- Time intelligence functions (YTD, QTD, MTD, SAMEPERIODLASTYEAR)
- Period-over-period calculations (YoY, MoM)
- Moving averages and rolling calculations
- FILTER and CALCULATETABLE functions
- VALUES, DISTINCT, and SELECTEDVALUE
![skill]( "Hands On Experience")
- Create YoY, MoM, QoQ comparison measures
- Implement rolling 12-month averages
- Calculate same period last year with fiscal calendar
- Build dynamic period selection using slicers
- Create custom fiscal year calculations
![skill]( "skill you will learn")
- Context transition control
- Advanced CALCULATE patterns
- Time intelligence modeling
- Period comparison analysis
- Virtual table filtering
Module 8: Iterator Functions and Complex Calculations
8 Topics
Topics
- Iterator functions (SUMX, AVERAGEX, COUNTX, RANKX)
- SUMMARIZE and ADDCOLUMNS for virtual tables
- Statistical functions (MEDIAN, STDEV, PERCENTILE)
- EARLIER function for nested row contexts
- ABC/Pareto analysis using DAX
- Complex filtering scenarios
- Dynamic measures with SWITCH
- Variables (VAR) for optimization
![skill]( "Hands On Experience")
- Build ABC analysis for product categorization
- Create customer RFM segmentation
- Calculate weighted averages and complex KPIs
- Implement Pareto analysis (80/20 rule)
- Build dynamic top N analysis
- Create cohort analysis measures
![skill]( "skill you will learn")
- Iterator-based calculations
- Virtual table construction
- ABC/Pareto implementation
- Complex KPI modeling
- DAX performance optimization
Module 9: Data Visualization Fundamentals
9 Topics
Topics
- Visualization selection criteria
- Bar and column charts (clustered, stacked, 100% stacked)
- Line and area charts
- Pie, donut, and treemap charts
- Scatter and bubble charts
- Tables and matrix visuals
- Card and multi-row card visuals
- Conditional formatting rules
- Tooltips and drill-through configuration
![skill]( "Hands On Experience")
- Build executive KPI dashboard with cards
- Create sales trend analysis with line charts
- Design product performance comparison with bar charts
- Implement conditional formatting for variance analysis
- Create matrix with drill-down hierarchies
- Build interactive scatter plot for correlation analysis
![skill]( "skill you will learn")
- Visualization selection strategy
- KPI dashboard design
- Interactive drill-down setup
- Conditional formatting logic
- Analytical chart configuration
Module 10: Advanced Visualizations and Custom Visuals
8 Topics
Topics
- Gauge, KPI, and waterfall charts
- Funnel and ribbon charts
- Decomposition tree for root cause analysis
- Key influencers visual
- Q&A visual and natural language queries
- Custom visuals from AppSource
- Python and R visuals integration
- Exploring Spatial Insights with Geospatial Analytics
![skill]( "Hands On Experience")
- Build sales funnel with conversion metrics
- Create waterfall chart for P&L analysis
- Implement decomposition tree for drill-through analysis
- Build key influencers for customer churn analysis
- Import and configure custom visuals (Gantt, Sankey)
- Create geographic analysis with shape maps
![skill]( "skill you will learn")
- Visual storytelling
- AI visual implementation
- Custom visual integration
- Geospatial analytics modeling
- Statistical visualization integration
Module 11: Report Design - UX/UI Best Practices
9 Topics
Topics
- Report design principles and best practices
- Color theory and accessible color palettes
- Custom themes and JSON theme files
- Buttons, bookmarks, and navigation
- Mastering Layout: Z-order, Grouping, and Binning
- Page navigation and drill-through pages
- Mobile layout optimization
- Report performance optimization
- Accessibility features (alt text, tab order)
![skill]( "Hands On Experience")
- Design a corporate-branded report template
- Create custom theme JSON file
- Implement bookmark navigation for story-telling
- Build drill-through pages for detailed analysis
- Optimize mobile layout for tablets and phones
- Apply accessibility standards (WCAG compliance)
![skill]( "skill you will learn")
- UX/UI report design
- Custom theme development
- Mobile layout optimization
- Accessibility compliance implementation
Module 12: Interactive Reports
8 Topics
Topics
- Report, page, and visual-level filters
- Slicer types and configurations
- Sync slicers across multiple pages
- Drill-down, drill-through, and drill-up
- Cross-highlighting and cross-filtering
- Edit interactions configuration
- Field parameters for dynamic measures
- Relative date filtering
![skill]( "Hands On Experience")
- Build multi-page interactive sales dashboard
- Implement cross-report drill-through
- Create field parameters for user-selected measures
- Configure complex slicer interactions
- Build dynamic what-if scenarios
- Implement hierarchical navigation structure
![skill]( "skill you will learn")
- Slicer synchronization setup
- Dynamic field parameters
- Cross-report navigation design
- Interactive dashboard development
Module 13: Power BI Service
8 Topics
Topics
- Power BI Service workspace architecture
- Publishing from Desktop to Service
- Workspace roles (Admin, Member, Contributor, Viewer)
- Apps creation and distribution
- Sharing reports and dashboards
- Subscriptions and data alerts
- Comments and collaboration features
- Tracing Data Lineage and Impact Analysis
![skill]( "Hands On Experience")
- Create and configure workspaces
- Publish reports and create apps
- Set up role-based access control
- Configure email subscriptions
- Create data-driven alerts
- Implement content distribution strategy
![skill]( "skill you will learn")
- Power BI Service publishing
- Workspace security management
- App distribution strategy
- Role-based access configuration
- Deployment pipeline governance
Module 14: Dashboards and Power BI Mobile
8 Topics
Topics
- Dashboard vs. report differences
- Pinning visuals to dashboards
- Dashboard tiles configuration
- Real-time dashboards with streaming datasets
- Dashboard themes
- Mobile app features and capabilities
- Phone layout design
- Q&A on dashboards
![skill]( "Hands On Experience")
- Build executive dashboard with pinned tiles
- Create real-time streaming dashboard
- Design mobile-optimized phone layout
- Configure natural language Q&A
- Implement mobile-specific features
- Build location-aware mobile report
![skill]( "skill you will learn")
- Dashboard design configuration
- Streaming data integration
- Mobile layout optimization
- Natural language Q&A setup
- Executive dashboard storytelling
Module 15: Data Refresh, Gateway, and Dataset Management
9 Topics
Topics
- On-Premises Data Gateway Configuration
- Personal vs Enterprise Gateway
- Dataset Refresh Types (Scheduled and On-Demand)
- Gateway Installation and Configuration
- Incremental Refresh Setup and Policies
- Refresh Failure Troubleshooting
- Dataset Storage Modes (Import, DirectQuery, Composite)
- Query Caching and Performance Optimization
- Dataset Endorsement and Certification
![skill]( "Hands On Experience")
- Install and configure enterprise gateway
- Set up scheduled refresh with multiple data sources
- Implement incremental refresh for large datasets
- Troubleshoot common refresh failures
- Configure hybrid connectivity scenarios
- Optimize dataset for query performance
![skill]( "skill you will learn")
- Enterprise refresh configuration
- Gateway lifecycle management
- Incremental refresh modeling
- Refresh issue diagnostics
- Dataset performance optimization
Module 16: Securing Data and Tracking Metrics
9 Topics
Topics
- Security Layers in Power BI
- Row-Level Security (RLS) Implementation
- Static Roles vs Dynamic Security
- USERNAME() and USERPRINCIPALNAME() Functions
- Role-Based Data Access
- Object-Level Security
- Testing RLS with “View As”
- Sensitivity Analysis and Compliance
- Security Best Practices
![skill]( "Hands On Experience")
- Implement RLS for regional sales managers
- Create dynamic security using user mapping table
- Build multi-level security hierarchy
- Test RLS with different user personas
- Configure object-level security for sensitive data
- Document security model and role assignments
![skill]( "skill you will learn")
- Row-level security design
- Dynamic role configuration
- Object-level security setup
- Access validation testing
- Data governance implementation
Module 17: Advanced Analytics – What-If Parameters and Forecasting
9 Topics
Topics
- What-If Parameters Creation
- Scenario Analysis and Modeling
- Built-in Forecasting and Trend Lines
- Clustering and Outlier Detection
- Statistical Analysis Functions
- Calculated Tables for Scenario Modeling
- Building Data-Driven Scorecards
- Streamlining Deployment Pipelines
- Power BI Embedded Analytics
![skill]( "Hands On Experience")
- Create sales forecasting with confidence intervals
- Implement customer clustering analysis
- Build inventory optimization model
- Create Monte Carlo simulation
- Develop cohort retention analysis
![skill]( "skill you will learn")
- Scenario modeling techniques
- Forecasting model development
- Clustering analysis implementation
- Predictive simulation modeling
- Advanced analytics dashboards
Module 18: AI-Powered Analytics
10 Topics
Topics
- Key Influencers Visual for Pattern Analysis
- Smart Narratives for Automated Storytelling
- Decomposition Tree for Root Cause Analysis
- Quick Insights and Pattern Discovery
- Creating and Managing Dataflows
- Azure Cognitive Services Integration
- Text Analytics and Sentiment Analysis
- Anomaly Detection
- Natural Language Q&A Optimization
- Python Visuals and Predictive Modeling
![skill]( "Hands On Experience")
- Implement sentiment analysis on customer feedback
- Create automated insights dashboard
- Apply anomaly detection to sales data
- Build image classification for product categorization
- Optimize Q&A with synonyms and featured questions
![skill]( "skill you will learn")
- AI visual analytics
- Sentiment analysis modeling
- Anomaly detection techniques
- Cognitive services integration
- Python predictive analytics
Module 19: Copilot for Power BI and Generative AI Integration
8 Topics
Topics
- Microsoft Copilot in Power BI Overview
- Copilot: Preparing Data for AI
- AI-Assisted Report Page Creation
- Copilot for DAX Formula Generation
- Natural Language Narrative Summaries
- AI-Powered Data Transformation Suggestions
- Fabric Copilot Integration
- Power BI Model Context Protocol (MCP) Servers
![skill]( "Hands On Experience")
- Create report pages using Copilot suggestions
- Generate complex DAX measures with AI assistance
- Build AI-powered executive summaries
- Implement smart narrative for dynamic insights
- Create conversational analytics with Q&A
- Develop AI-augmented dashboards
![skill]( "skill you will learn")
- Copilot report generation
- AI-assisted DAX development
- AI-driven data preparation
- Conversational analytics design
- Generative BI integration
Module 20: End-to-End Enterprise Analytics Solution
8 Topics
Topics
- Requirements Gathering and Analysis
- Data Architecture Design
- Data Modeling and Transformation
- Advanced DAX Implementation
- Report and Dashboard Design
- Security and Governance Implementation
- Deployment and Maintenance Strategy
- Documentation and Knowledge Transfer
![skill]( "Hands On Experience")
- Build end-to-end sales and operations analytics solution
- Connect to SQL, Excel, and API data sources
- Design star schema with 10+ tables
- Create complex DAX measures
- Build 5 interactive reports with advanced visuals
- Implement RLS and security model
- Deploy to Power BI Service with scheduled refresh
![skill]( "skill you will learn")
- Enterprise analytics architecture
- Advanced DAX modeling
- Governance framework implementation
- Production BI deployment
- Solution design presentation
Module 21: Getting Started with Microsoft Fabric (Self-Paced)
7 Topics
Topics
- Why Fabric After Power BI
- Fabric Architectural Fundamentals
- OneLake Unified Storage Concept
- Fabric Workloads Overview
- Semantic Models Hosted on Fabric Data
- Fabric Capacities and Workload Isolation
- Power BI’s Role in Fabric Analytics Lifecycle
![skill]( "Hands On Experience")
- Enable Fabric in Power BI tenant
- Explore Fabric workspace and workloads
- Create a Lakehouse and review structure
- Inspect OneLake storage layout
- Connect Power BI to Fabric-backed data
![skill]( "skill you will learn")
- Fabric architecture fundamentals
- Unified analytics framework
- OneLake storage management
- Fabric–Power BI integration
- Capacity governance basics
Module 22: Fabric Data Engineering with Power Query, Apache Spark & Delta (Self-Paced)
7 Topics
Topics
- Cloud-Based Data Engineering in Fabric
- Fabric Power Query Editor (Cloud Execution)
- Visual Query Editor using Dataflows Gen2
- Delta Tables and Transactional Storage
- Apache Spark Notebooks in Fabric
- When to Use Power Query vs Spark
- Data Engineering Patterns for Power BI Consumption
![skill]( "Hands On Experience")
- Build Dataflows Gen2 using Visual Query Editor
- Apply transformations using Fabric Power Query
- Create Delta tables in Lakehouse
- Use Spark notebooks for large-scale transformations
- Validate Power BI consumption from engineered data
![skill]( "skill you will learn")
- Cloud transformation workflows
- Spark data processing
- Delta Lake implementation
- Data pipeline design
- BI-ready data engineering
Module 23: Real-Time Intelligence & Streaming Analytics (Self-Paced)
6 Topics
Topics
- Real-Time Intelligence Workload Overview
- Eventstream Concepts and Data Ingestion
- Streaming Data into OneLake
- KQL Databases and Query Concepts
- Power BI Integration with Real-Time Datasets
- Use Cases for Operational Dashboards
![skill]( "Hands On Experience")
- Create an Eventstream in Microsoft Fabric
- Ingest streaming data into a KQL database
- Query streaming data using KQL
- Build a real-time Power BI dashboard
- Monitor latency and data freshness
![skill]( "skill you will learn")
- Real-time architecture design
- Event-driven ingestion
- KQL query development
- Streaming dashboard creation
- Latency monitoring techniques
Module 24: Performance, AI & Operations in Fabric Analytics (Self-Paced)
6 Topics
Topics
- Direct Lake Execution Model (Fabric-Specific)
- Cross-Workspace Semantic Model Reuse
- Fabric Capacity Management and Throttling
- Monitoring Fabric Workload Performance
- Copilot in Fabric for Analytics Assistance
- Cost Optimization and Operational Best Practices
![skill]( "Hands On Experience")
- Build a Direct Lake–backed semantic model
- Reuse semantic models across workspaces
- Monitor Fabric capacity utilization
- Deploy an optimized Fabric-to-Power BI solution
![skill]( "skill you will learn")
- Direct Lake optimization
- Capacity management strategy
- Semantic model reuse
- Performance monitoring
- AI-assisted analytics
Advanced Power BI with GenAI Course Description
What is Advanced Power BI Certification Training with GenAI by Edureka?
Edureka's Advanced Power BI Certification Training with GenAI is a 60-hour, instructor-led live program designed to take learners from data fundamentals to enterprise-grade analytics powered by AI and Microsoft Copilot.
The course spans 20 core modules covering Power Query, data modeling, DAX, advanced visualizations, enterprise security, and AI-powered reporting — plus 4 self-paced Microsoft Fabric modules. It is fully aligned with the Microsoft PL-300 Power BI Data Analyst certification competencies, making it ideal for professionals looking to build job-ready Power BI skills integrated with Generative AI capabilities.
Who should enroll in Advanced Power BI Training with GenAI?
This course is designed for a wide range of professionals:
- Data Analysts and BI Developers aiming to master advanced Power BI concepts and enterprise-level reporting
- Business Analysts, MIS Executives, and Reporting Leads seeking to automate insights and build self-service dashboards
- Finance, Operations, and Marketing professionals who require data-driven decision-making capabilities
- IT professionals transitioning into data analytics and business intelligence roles
- Software Developers expanding their expertise into BI and AI-powered analytics solutions
- Beginners with basic spreadsheet knowledge looking for a structured, hands-on pathway to Power BI certification
What are the prerequisites for Edureka's Advanced Power BI Training?
What are the prerequisites for Edureka's Advanced Power BI Training?
- Required: Basic data literacy (comfort reading tables and spreadsheets), familiarity with Excel or Google Sheets, and an understanding of basic business metrics such as revenue, margin and KPIs.
- Recommended but not mandatory: Basic SQL knowledge for data querying, prior exposure to any BI reporting tool, and familiarity with relational database concepts. No programming background is needed to start — Python and R are introduced only in advanced visualization modules.
What topics are covered in the Advanced Power BI Certification Training with GenAI course?
The course covers the complete Power BI learning journey:
- Comprehensive overview of the Power BI ecosystem and architecture
- Data connectivity with 15+ data source types, including cloud and on-prem systems
- Dimensional modeling with star schema design best practices
- DAX from fundamentals to advanced concepts, including time intelligence and iterator functions
- Development of core and advanced data visualizations
- Professional UX/UI report design principles for impactful dashboards
- Implementation of interactive filtering, drill-through, and drill-down actions
- Publishing, sharing, and collaboration using Power BI Service
- Enterprise-grade security with Row-Level Security (RLS) and Object-Level Security (OLS)
- Data refresh strategies and gateway configuration for production environments
- Advanced analytics using what-if parameters and forecasting models
- AI-powered analytics integration with Azure Cognitive Services
- Dedicated modules on Microsoft Copilot and Generative AI integration in Power BI
- Self-paced modules covering Microsoft Fabric fundamentals and capabilities
Does the Advanced Power BI course include Microsoft Fabric content?
Yes. In addition to the 20 core Power BI live modules, your enrollment includes 4 free self-paced Microsoft Fabric modules. These modules future-proof your skills on Microsoft's unified analytics platform.
How will I execute the practicals in this Advanced Power BI Certification Training with GenAI?
A step-by-step guide for setting up environments, configuring DevOps tools, and integrating GenAI assistants will be provided in the Learning Management System (LMS). Participants will have access to cloud-based lab environments for practicing Docker, Kubernetes, Terraform, CI/CD pipelines, and GenAI tools without complex local setups.
Edureka's Support Team will be available 24/7 to assist learners in case they have any questions or face any technical issues during the practicals.
What are the system requirements for this Advanced Power BICertification Training with GenAI?
You will need: a Windows PC or laptop running Windows 10 or Windows 11 (Power BI Desktop is not officially supported on macOS — Mac users can use a Windows virtual machine or Boot Camp); a minimum of 4 GB RAM (8 GB recommended); a stable internet connection (minimum 5 Mbps); and a free Microsoft account for Power BI Service access. The free version of Power BI Desktop is sufficient for most modules.
A Power BI Pro license (free trial available) is required for Module 13 onward covering Power BI Service collaboration and sharing features.
Advanced Power BI Training Projects
Enterprise Sales & Operations Analytics Dashboard
Develop a unified sales performance dashboard integrating SQL, Excel, and API data into a star schema model. Implement RLS-based regional access, advanced DAX KPIs, and Copilot-g....Financial P&L & Variance Analysis Report
Design a board-ready P&L reporting suite with YoY variance analysis, waterfall charts, and drill-through to transaction-level data. Implement dynamic fiscal calendar support and ....Customer Segmentation & Churn Analysis
Build a behavioral analytics solution using RFM scoring, clustering, and predictive churn indicators. Leverage iterator DAX, Python visuals, and AI-powered Key Influencers to red....Real-Time Operations Intelligence Dashboard
Create a real-time dashboard powered by streaming IoT datasets to monitor production KPIs and machine performance. Implement anomaly detection, alerting mechanisms, and mobile-op....AI-Powered Executive Insights Suite
Develop an AI-augmented reporting suite with Copilot-generated summaries and Smart Narratives. Integrate Cognitive Services, MCP servers, and AutoML for automated insights and da....Advanced Power BI Certification
Edureka provides the Advanced Power BI with GenAI certification upon successful course completion. The certification is valid for lifetime with no renewal required.
Complete all 20 live modules, pass quizzes, finish hands-on Power BI assignments and complete the capstone project.
Upon successfully completing the course curriculum, all module assessments and the capstone project, you will receive the Edureka Advanced Power BI Certification Training with GenAI course completion certificate.
This credential demonstrates your proficiency in Power BI, DAX, AI-powered analytics, Microsoft Copilot and enterprise BI governance. The certificate is recognized by hiring managers at leading organizations across technology, finance, healthcare and consulting sectors.
Yes. The entire curriculum is closely aligned with all four domains of the Microsoft PL-300: Power BI Data Analyst Associate exam:
- Domain 1: Prepare the Data (covered in Modules 2-4: data connectivity, Power Query and advanced data shaping)
- Domain 2: Model the Data (covered in Modules 5-8: star schema design, DAX fundamentals, advanced and expert-level DAX)
- Domain 3: Visualize and Analyze the Data (covered in Modules 9-12 and 17-18: core visuals, advanced visuals, report design, interactive filtering and AI analytics)
- Domain 4: Deploy and Maintain Assets (covered in Modules 13-16: Power BI Service, dashboards, refresh, gateway and RLS security).
The course maps every module to PL-300 exam competencies. You will practice all skills tested on the exam: connecting and transforming data using Power Query; building optimized data models with relationships, hierarchies and calculated tables; writing DAX measures including time intelligence, iterator functions and context manipulation; designing interactive reports with slicers, filters, drill-through and bookmarks; deploying to Power BI Service with workspaces, apps and scheduled refresh; and implementing Row-Level Security.
The capstone project reinforces all domains in an integrated scenario. Learners are encouraged to use Microsoft's official PL-300 study guide alongside the course.
Yes. The course includes module-level quizzes after each of the 20 modules to reinforce learning and identify gaps. There is an end course assessment covering data modeling and DAX proficiency respectively.
The capstone project serves as the primary graded deliverable and must be completed to receive the Edureka completion certificate.
The Edureka Advanced Power BI Certification is a course completion credential issued by Edureka that validates your training, hands-on lab experience and project delivery. It demonstrates structured learning and practical application.
The Microsoft PL-300: Power BI Data Analyst Associate is a vendor certification issued directly by Microsoft after passing a proctored exam. It is a globally recognized, role-based credential with high market value.
The two certificates are complementary: Edureka's training prepares you thoroughly for the PL-300 exam, and holding both credentials provides the strongest possible signal of competence to employers.
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The unique combination of Online Classes with 24*7 On-Demand Support and class recordings/ppt/docs etc in Learning Management System (LMS) on the site made me fall in love with edureka! There could not be a better Android Training Avenue to quench my thirst for learning Android Development.
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I really had overwhelming experience with edureka. I was looking for class room training for AWS course. But the edureka representative explained me the advantageous of the online program that they are providing. Best part about it is, they provided all the class room recordings and in future you can attend the online classes of the same course again WITHOUT any additional cost. This is awesome. I really recommend edureka training programs for career growth. I am sure you will fell the same, if you are part of edureka.
December 09, 2017
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Edureka has redefined the e-learning service with the help of technology. They have excellent faculty and support team that has given a real class room learning experience. Anybody can upgrade their skills at their convenience! Edureka has expertise in Big Data Analytics and they are providing opportunity to acquire these skills in a short time!
December 09, 2017
Clean, simple and a fantastic learning resource. The courses are a great resource for personal development and continual learning. They are well structured and provided both ease of access and depth while allowing you to go at your own pace.Support team people is also really very cooperative and helps out at there best.
December 09, 2017
Edureka has very good instructors and technical support team, I have completed the course BIG DATA & AWS through web training, and it was very good training, helped me to learn very swiftly. When I stuck up in installation and in writing map reduce programming technical support resolved very quickly and I was very happy with their response in time. As well as they providing life time access for our completed course videos so it will be useful in real time projects. I feel very happy to recommend Edureka for my friends on big data course.
December 09, 2017
Tejinder SinghPGDCA, MSc(IT), MCA, M-tech(IT), Phd(CS)*, Lecturer, Baba Farid College, Punjab
There is a plethora of online training material available for Android; the reason I chose Edureka is the rare combination of great instructors, comprehensive course material . The course has a clear direction, which is perfect for efficiency-oriented professionals like us! What differentiates Edureka training from numerous other Android trainers is that they bring a lot of corporate experience on the table, and that is evident in their teaching techniques.
December 09, 2017
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Advanced Power BI FAQs
Will I get access to recorded sessions if I miss a live class?
Yes. All live sessions are recorded in high definition and uploaded to your Edureka Learning Management System (LMS) account within 24 hours of the session. You can watch sessions at your own pace, rewind and replay specific segments, and access all lab datasets, reference materials and supplementary resources alongside the recordings.
Is Power BI relevant if my organization uses Tableau or other BI tools?
Yes. Power BI knowledge is highly transferable and complementary to other BI tools. Core skills in data modeling, DAX measures, visualization best practices and data storytelling learned in Power BI apply directly when working with any BI platform.
Many organizations use multiple BI tools simultaneously — Power BI for Microsoft 365-integrated reporting and operational dashboards, alongside Tableau or Qlik for specialized analytics.
Power BI's deep integration with Azure, Microsoft Fabric and the Microsoft 365 ecosystem also makes it the preferred choice for organizations already on the Microsoft stack, which represents the majority of enterprise IT environments globally.
How is Power BI different from Excel for data analysis?
While Excel remains powerful for individual-level data manipulation and ad hoc analysis, Power BI is purpose-built for enterprise-scale analytics, interactive dashboards and organizational data sharing. Power BI handles datasets in the hundreds of millions of rows using columnar compression, while Excel struggles beyond a few hundred thousand rows; Power BI's DAX language enables complex calculations across related tables that are difficult or impossible in Excel formulas. Power BI Service enables governed, role-based sharing and collaboration across an entire organization; Power BI includes built-in AI features such as Copilot, Key Influencers and Anomaly Detection unavailable in standard Excel; and Power BI connects natively to cloud data sources, real-time streaming data and the full Microsoft Fabric platform.
Is Advanced Power BI a strong career choice in 2026?
Absolutely. Organizations across industries are investing heavily in data-driven decision-making and AI-augmented analytics. Professionals skilled in advanced DAX, data modeling, RLS, and GenAI-powered insights are in high demand for roles such as BI Developer, Analytics Consultant, and Data Visualization Specialist.
How is Generative AI transforming Power BI?
GenAI enhances Power BI through Copilot-powered DAX generation, automated narrative insights, smart summaries, and AI-assisted data modeling. It accelerates report development, improves analytical depth, and enables business users to derive insights through natural language interactions.
What industries hire Advanced Power BI professionals with AI skills?
Retail and FMCG, Banking and Financial Services (BFSI), Healthcare, E-commerce, Manufacturing, Telecommunications, EdTech, Consulting, and Government sectors actively hire BI professionals who can deliver AI-powered executive dashboards and enterprise reporting solutions.
What is the difference between Advanced Power BI and traditional BI tools?
Traditional BI tools focus primarily on visualization and static reporting. Advanced Power BI with GenAI integrates data modeling, enterprise governance (RLS), AI-powered analytics, automation, and intelligent narratives, enabling scalable, insight-driven decision-making across organizations.
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