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Diploma in Business Analytics with Microsoft Power BI

Diploma in Business Analytics with Microsoft Power BI

About This Course

This course provides a comprehensive introduction to business analytics using Microsoft Power BI, guiding learners from foundational concepts to advanced analytical techniques. You’ll gain hands-on experience in data preparation, visualization, and reporting while mastering the Power BI ecosystem. With practical modules and real-world applications, the program equips you with the skills needed to derive meaningful insights and support data-driven decision-making. It is ideal for beginners and professionals looking to enhance their analytics capabilities

By the end of this course, you will be able to:

  • Build interactive dashboards and impactful data visualizations using Power BI.
  • Prepare, clean, and transform data efficiently within Power BI Desktop.
  • Write and apply DAX formulas for advanced calculations and analytics.
  • Transform raw data into clean, reliable datasets that support accurate business reporting.
  • Create professional, interactive dashboards used by organizations to track KPIs and make data-driven decisions.
  • Share and collaborate on reports in Power BI Service, enabling teams to access real-time insights across the business.

Who Can Join

  • Beginners interested in learning
  • Undergraduate Students
  • Professionals in Any Industry
  • Business Analysts / Project Managers
  • Marketing Specialists
  • Administrative Assistants

Career Pathway

  • Professionals in Any Industry
  • Professionals in Business & administration
  • Professionals in Education
  • Professionals in Finance & Marketing
  • Professionals in Customer service
  • Professionals in HR & operations
  • Writers, Creators & Designers
  • Teachers & Educators
  • Entrepreneurs & Business Owners
  • Anyone Who Wants to Be More Productive

Professional Skills

✔ Data Analysis & Critical Thinking
✔ Data Visualization
✔ Understanding Business KPIs
✔ Storytelling With Data
✔ Running Ad-Hoc Analysis Quickly
✔ Stakeholder Management
✔ Data analysis
✔ Data-Driven Judgment

Getting Started : Business Analytics with Microsoft Power BI

Module 01 :    Getting Started with Power BI ▼
  • 1. Introduction to Business Intelligence
  • 2. Understanding Data and Its Importance
  • 3. Why do we need a Business Intelligence Tool?
  • 4. Self-Service Business Intelligence (SSBI)
  • 5. Introduction to Power BI
  • 6. Features of Power BI
  • 7. Traditional BI vs. Power BI
  • 8. Architecture of Power BI
  • 9. How Power BI Works - The Workflow
  • 10.Core Components of Power BI
  • 11.Power BI Version Comparison
  • 12.Real-World Use Cases of Power B
Module 02 :    Data Preparation and Transformation with Power BI Desktop ▼
  • 1. Connecting to Various Data Sources
  • 2. Import vs. DirectQuery Modes
  • 3. Data Loading and Source Settings
  • 4. Normali
  • 5. Views in Power BI Desktop
  • 6. Introduction to Power Query Editor
  • 7. Data Profiling in Query Editor
  • 8. Transforming, Cleaning, and Shaping Data
  • 9. Data Modeling Fundamentals
  • 10.Introduction to Semantic Model
  • 11.Star vs. Snowflake Schema Design
  • 12.Exploring Data Relationships
  • 13.Cardinality and cross-filter Direction
  • 14.Creating and Using Parameters
  • 15.Model Optimization
Module 03 :    Data Analysis Expression (DAX) ▼
  • 1. Introduction to Data Analysis Expression
  • 2. Role of DAX in Power BI and Data Modeling
  • 3. Understanding DAX Syntax and Structure
  • 4. Data Types in DAX
  • 5. Calculation Types in DAX: Calculated Columns, Measures, and Tables
  • 6. Introduction to Measures
  • 7. DAX Functions
  • 8. Understanding and Using DAX Operators
  • 9. Working with DAX Tables and Applying Filters
  • 10.DAX Performance Optimization
  • 11.Best Practices for DAX Performance Optimization
Module 04 :    Designing Impactful Data Visualizations ▼
  • 1. Introduction to Visuals in Power BI
  • 2. Types of Visualizations
  • 3. Using Shapes, Text Boxes, and Images
  • 4. Conditional Formatting in Visuals
  • 5. Z-order, Layering, Grouping, and Binning
  • 6. Bookmarks, tooltips, and drillthrough
  • 7. Page Layout and Formatting
  • 8. Field Parameters for Dynamic Visuals
  • 9. Custom Visuals from Appsource
Module 05 :    Leveraging Power BI Service for Scalable Insights ▼
  • 1. Introduction to Power BI Service
  • 2. Power BI Service vs Power BI Desktop
  • 3. Exploring Power BI Service Interface
  • 4. Introduction to Workspaces
  • 5. Publishing Reports to Power BI Service
  • 6. Creating a Dashboard
  • 7. Quick Insights and Analyze Features in Power BI
  • 8. Working with Power BI Q&A Feature
  • 9. Monitoring Usage Metrics and Report Performance
  • 10. Deployment Pipelines
  • 11. Power BI Lineage
  • 12. Protecting Data using Sensitivity Labels
  • 13. Introduction to Metrics Hub and Scorecards
  • 14. Power BI Embedded
  • 15. Power BI Mobile App Features and Development
Module 06 :    Data Connectivity Modes in Power BI ▼
  • 1. Exploring Data Connections
  • 2. Connecting to Cloud Databases
  • 3. SQL Server Analysis Services / MySQL
  • 4. Connecting Power BI with Microsoft Dataverse
  • 5. Understanding Security Roles and Permissions in Dataverse
  • 6. Working with Dataflows in Power BI Service
  • 7. Integrating Cognitive Services with Power BI
  • 8. Importing Power View and Power Pivot
  • 9. Introduction to Data Gateways
  • 10.Data Gateways Workflow
  • 11.Introduction to OneLake and the Fabric Ecosystem
  • 12.Discovering and Reusing Datasets from OneLake Data Catalog
  • 13.Governance and Lineage in OneLake
Module 07 :    Integrating R and Python in Power BI ▼
  • 1. Overview of R and Python Languages in BI
  • 2. Setting Up R/Python Environments
  • 3. Data Ingestion with R and Python Scripts
  • 4. Using scripts for Data Transformation
  • 5. Custom Visualizations with R and Python
  • 6. Predictive Analytics with R/Python
  • 7. Azure ML Integration via Python
  • 8. Use cases and Best Practices for Integration
Module 08 :    Power BI Report Server ▼
  • 1. What is Power BI Report Server?
  • 2. Key Features of Report Server
  • 3. Report Server Architecture
  • 4. Power BI Report Server vs. Power BI Service
  • 5. Acquiring and Installing Power BI Report Server
  • 6. What is a Web Portal?
  • 7. Working with Paginated Reports
  • 8. Scheduled Data Refresh via Gateway
  • 9. Implementing and Managing Row-Level Security (RLS)
  • 10.Limitations of Report Server
  • 11.Use Cases for Power BI Report Server in Enterprise Environments
Module 09 :    Developing Sales Dashboard ▼
  • 1. Data Loading from External Sources
  • 2. Data Transformation using Power Query Editor
  • 3. Data Modeling and Relationships
  • 4. Data Analysis with DAX
  • 5. Designing AI-Powered Visuals
  • 6. Workspace Management
  • 7. Row-Level Security (RLS) Implementation
  • 8. Publishing Reports on Power BI Service
Module 10 :    PL 300 Certification Preparation ▼
  • 1. Overview of PL-300 Exam Outline
  • 2. Key Objectives Breakdown
  • 3. Real-World Case Studies
  • 4. Sample Question Discussion
  • 5. Time Management Tips
  • 6. Common Pitfalls to Avoid in the Exam
PDF DOWNLOAD FULL SYLLABUS
✓ Hands-on
  • • Sales Data Analysis – Generic Super Market Sales
  • • HR Analytics Dashboard – Attrition Analysis
  • • IMDB Movie Dataset Dashboard – Movie Comparison
  • • Personal Finance Management Dashboard – Financial Insights

Tools

Power BI Tools

Program Fees & Enrollment

Business Analytics with Power BI

  • ✔ Mentorship & Project Work
  • ✔ Lifetime Recording Full Access
  • ✔ Certificate & Placement Support
  • ✔ Lifetime Community Membership

Rs.20,000

Including all taxes & course materials

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  • Lessons 50 Lessons
  • Duration 3 Month
  • Classroom Online
  • Language Tamil
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