Duration 5 Days – 40 hrs.
Overview
The BIRD (Business Intelligence, Reporting & Data Analytics) Training Course is a comprehensive, hands-on program designed to equip professionals with the skills to transform raw data into actionable business insights.
This course focuses on end-to-end data workflows—from data sourcing, cleaning, and transformation to dashboard creation, reporting automation, and decision-making support. It emphasizes real-world enterprise scenarios, enabling participants to build scalable BI solutions aligned with business objectives.
Participants will gain practical experience using modern BI tools, data modeling techniques, and reporting strategies widely used in corporate environments.
Objectives
- Understand the role of Business Intelligence in enterprise decision-making
- Collect, clean, and prepare data from multiple sources
- Design efficient data models for reporting and analytics
- Create interactive dashboards and reports
- Apply basic to intermediate data analysis techniques
- Automate reporting processes and workflows
- Translate data insights into business recommendations
- Implement BI best practices for scalability and governance
Target Audience
- Data Analysts and Business Analysts
- Reporting Specialists and MIS Professionals
- IT and Data Team Members
- Finance, Operations, and Marketing Analysts
- Managers and Decision-Makers using dashboards
- Professionals transitioning into Data/BI roles
Prerequisites
- Basic knowledge of Microsoft Excel or equivalent tools
- Basic understanding of data (tables, rows, columns)
- No programming experience required (optional advantage)
- Familiarity with business processes is helpful
Course Outline
Day 1 – Data Foundations & Preparation
Module 1: Introduction to Business Intelligence
- What is BI and Data Analytics
- BI in enterprise environments
- Data-driven decision-making lifecycle
Module 2: Data Sources & Data Collection
- Types of data (structured, semi-structured)
- Connecting to databases, Excel, APIs
- Data extraction techniques
Module 3: Data Cleaning & Preparation
- Handling missing and inconsistent data
- Data transformation basics
- Data quality and validation
Hands-On Lab
- Importing and cleaning datasets from multiple sources
Day 2 – Data Modeling & Transformation
Module 4: Data Modeling Fundamentals
- Tables, relationships, keys
- Star schema vs snowflake schema
- Fact and dimension tables
Module 5: Data Transformation Techniques
- Filtering, merging, aggregations
- Data shaping and normalization
Module 6: Introduction to Calculations
- Measures vs calculated columns
- Basic formulas and expressions (e.g., DAX concepts)
Hands-On Lab
- Build a data model for a business use case
Day 3 – Visualization & Dashboarding
Module 7: Data Visualization Principles
- Choosing the right chart
- Storytelling with data
- Avoiding common visualization mistakes
Module 8: Dashboard Design
- KPI dashboards
- Drill-down and interactivity
- User-friendly layouts
Module 9: Reporting Tools Overview
- Tools such as Microsoft Power BI, Tableau, and Looker Studio
- Comparing enterprise BI platforms
Hands-On Lab
- Create an interactive dashboard
Day 4 – Advanced Analytics & Automation
Module 10: Data Analysis Techniques
- Trend analysis
- Segmentation and filtering
- Basic forecasting concepts
Module 11: Automation & Scheduling
- Automating reports
- Data refresh and pipelines
- Integration with business workflows
Module 12: Introduction to AI in BI
- AI-powered insights and recommendations
- Using Copilot and smart analytics features
- Preparing AI-ready datasets
Hands-On Lab
- Automate a reporting workflow
Day 5 – Enterprise BI Strategy & Capstone
Module 13: BI Governance & Best Practices
- Data governance and security
- Data privacy and compliance
- Managing enterprise BI environments
Module 14: BI Architecture Overview
- Data warehouses and data lakes
- ETL vs ELT processes
- Cloud BI environments
Module 15: Communicating Insights
- Translating data into business decisions
- Executive reporting techniques
- Storytelling for stakeholders
Module 16: Capstone Project
- Build an end-to-end BI solution:
- Data preparation
- Data modeling
- Dashboard creation
- Insights presentation
- Final presentation and feedback
