Course Overview

This intensive and practical training programme is designed to equip participants with the knowledge and skills required to analyse, visualise, and interpret data using Microsoft Power BI and modern data analytics techniques. The course covers the complete analytics lifecycle, from data collection and transformation to dashboard development, data modelling, advanced analytics, and business intelligence reporting. Participants will gain hands-on experience in transforming raw data into meaningful insights that support strategic decision-making and organisational performance.

Course Objectives

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

• Understand the fundamentals of data analytics and business intelligence.
• Connect, import, clean, and transform data from various data sources.
• Develop efficient data models using Power BI.
• Create interactive and professional dashboards and reports.
• Utilise DAX (Data Analysis Expressions) for advanced calculations.
• Apply data visualisation best practices to communicate insights effectively.
• Perform trend analysis, forecasting, and performance monitoring.
• Automate reporting processes and enhance organisational decision-making.
• Implement data governance, security, and reporting standards.
• Leverage Power BI’s AI-powered capabilities for predictive analytics and insight generation.

Target Audience

This course is suitable for:

• Data Analysts
• Business Analysts
• Financial Analysts
• Monitoring and Evaluation Specialists
• Project Managers
• Accountants and Auditors
• Business Intelligence Professionals
• Senior Managers and Executives
• Government Officials
• Researchers and Data Scientists
• Anyone responsible for analysing, reporting, or presenting organisational data

Training Methodology

The programme incorporates:

• Expert-led presentations
• Hands-on Power BI exercises
• Real-world case studies
• Interactive discussions
• Data modelling workshops
• Dashboard development projects
• Group assignments
• Practical reporting scenarios
• Performance assessments
• Capstone analytics project

 

Course Outline

Module 1: Introduction to Data Analytics and Business Intelligence

Topics Covered

• Fundamentals of Data Analytics
• Data-Driven Decision Making
• Business Intelligence Concepts
• Types of Analytics:

• Descriptive Analytics
• Diagnostic Analytics
• Predictive Analytics
• Prescriptive Analytics
  • Data Analytics Lifecycle
  • The Role of Power BI in Modern Organisations
  • Overview of the Microsoft Power Platform

Practical Exercise

• Exploring business intelligence use cases
• Understanding sample datasets

Module 2: Introduction to Power BI Environment

Topics Covered

• Power BI Architecture and Components
• Power BI Desktop Overview
• Power BI Service Overview
• Power BI Mobile Applications
• Navigating the Power BI Interface
• Power BI Licensing Models
• Connecting to Data Sources

Practical Exercise

• Installing and configuring Power BI Desktop
• Connecting to Excel and CSV files

Module 3: Data Acquisition and Integration

Topics Covered

• Data Sources and Data Connectivity
• Importing Data from:

• Excel
• SQL Databases
• SharePoint
• Cloud Services
• Web Sources
  • Understanding Extract, Transform and Load (ETL)
  • Data Integration Strategies
  • Data Quality Management

Practical Exercise

• Importing and combining multiple datasets
• Resolving data inconsistencies

Module 4: Data Cleaning and Transformation Using Power Query

Topics Covered

• Introduction to Power Query Editor
• Data Profiling Techniques
• Cleaning Incomplete Data
• Managing Errors and Duplicates
• Data Transformation Techniques
• Merging and Appending Queries
• Creating Custom Columns
• Data Standardisation

Practical Exercise

• Transforming raw business datasets
• Building reusable data preparation workflows

Module 5: Data Modelling Fundamentals

Topics Covered

• Principles of Data Modelling
• Relationships Between Tables
• Cardinality and Cross Filtering
• Star Schema Design
• Snowflake Schema Concepts
• Fact and Dimension Tables
• Optimising Data Models

Practical Exercise

• Designing a relational data model
• Building star-schema models

Module 6: Data Analysis Expressions (DAX)

Topics Covered

• Introduction to DAX
• DAX Syntax and Functions
• Calculated Columns
• Measures
• Time Intelligence Functions
• Aggregation Techniques
• Financial Calculations
• Conditional Logic
• Advanced DAX Techniques

Practical Exercise

• Creating KPIs and performance metrics
• Developing advanced DAX measures

Module 7: Data Visualisation and Dashboard Design

Topics Covered

• Principles of Effective Data Visualisation
• Choosing Appropriate Charts
• Creating:

• Bar Charts
• Line Charts
• Pie Charts
• Maps
• Tables and Matrices
• KPI Cards
• Gauges
  • Interactive Filters and Slicers
  • Drill-down Functionality
  • Visual Storytelling Techniques

Practical Exercise

• Building executive dashboards
• Designing operational performance reports

Module 8: Advanced Analytics in Power BI

Topics Covered

• Trend Analysis
• Forecasting Techniques
• Statistical Analysis
• Scenario Analysis
• What-If Parameters
• Clustering and Segmentation
• Key Influencers Analysis
• AI Visuals and Insights

Practical Exercise

• Building forecasting models
• Identifying business performance drivers

Module 9: Report Publishing, Sharing and Collaboration

Topics Covered

• Publishing Reports to Power BI Service
• Dashboard Creation in the Cloud
• Sharing Reports with Stakeholders
• Workspaces and Collaboration
• Scheduled Refreshes
• Mobile Reporting
• Embedding Reports in Applications

Practical Exercise

• Publishing and distributing reports
• Configuring automatic refresh schedules

Module 10: Power BI Security and Governance

Topics Covered

• Data Security Principles
• Row-Level Security (RLS)
• User Permissions and Roles
• Data Governance Frameworks
• Compliance Requirements
• Audit Trails and Monitoring
• Data Privacy Considerations

Practical Exercise

• Implementing secure access controls
• Configuring role-based report security

Module 11: AI and Machine Learning Integration

Topics Covered

• Introduction to AI in Business Intelligence
• AI Features in Power BI
• Predictive Analytics Applications
• Natural Language Querying
• Smart Narratives
• Cognitive Services Integration
• Machine Learning Models and Power BI

Practical Exercise

• Creating AI-driven analytical reports
• Generating automated business insights

Module 12: Building Executive Business Intelligence Solutions

Topics Covered

• Designing Enterprise Dashboards
• Executive Reporting Frameworks
• Strategic KPI Development
• Performance Management Dashboards
• Balanced Scorecard Reporting
• Analytics for Decision Support
• Best Practices for BI Implementation

Practical Exercise

• Developing an executive-level dashboard
• Presenting analytical findings to stakeholders

Participants will complete a comprehensive Power BI analytics project involving:

• Data extraction and preparation
• Data modelling
• DAX calculations
• Dashboard design
• KPI reporting
• Forecasting and trend analysis
• Executive presentation of findings

Expected Learning Outcomes

Upon successful completion of this course, participants will be able to:

• Build complete end-to-end Power BI solutions.
• Transform complex datasets into actionable business insights.
• Design professional and interactive dashboards.
• Develop advanced DAX calculations and KPIs.
• Implement secure and governed reporting environments.
• Support strategic and operational decision-making through data analytics.
• Apply AI-powered analytics capabilities within Power BI.
• Deliver impactful business intelligence reports for organisational success.