The global energy sector is becoming increasingly data-driven, requiring professionals to analyze, interpret, and present insights that support decision-making in a rapidly changing environment.
This course equips participants with the technical skills to use MS Access, MS Excel, and Power BI for data management and analysis, while also providing a foundational understanding of the energy sector, its value chain, and operations.
By the end of the program, learners will be able to handle energy-related datasets, create dashboards, and generate actionable insights to drive efficiency and strategic decisions.

Module 1: Introduction to the Energy Sector

• Overview of global and regional energy markets.
• Energy sources: Oil, Gas, Coal, Renewables, and Electricity.
• Energy value chain: Production, Transmission, Distribution, and Consumption.
• Key stakeholders: Utilities, regulators, consumers.
• Role of data analytics in modern energy systems.

Module 2: Fundamentals of Data Analytics

• What are data analytics and why it matters.
• Data types and sources in the energy sector.
• Basics of data quality, integrity, and security.
• Introduction to KPIs for the energy industry (efficiency, demand, losses, costs).

Module 3: Data Management with MS Access

• Creating and managing databases for energy datasets.
• Importing and cleaning raw data.
• Designing tables, queries, and relationships.
• Using forms and reports to structure data.
• Case Study: Building a simple energy consumption database.

Module 4: Data Analysis with MS Excel

• Advanced formulas and functions for energy data.
• Pivot tables and pivot charts for trend analysis.
• Data cleaning and transformation techniques.
• Scenario modeling and sensitivity analysis (e.g., price volatility).
• Forecasting demand using regression and trend analysis.
• Case Study: Analyzing electricity consumption and cost optimization.

Module 5: Data Visualization & Business Intelligence with Power BI

• Introduction to Power BI environment.
• Connecting Power BI with Access and Excel.
• Creating data models and relationships.
• Building interactive dashboards and reports.
• Sharing and publishing insights across teams.
• Case Study: Energy price trend and renewable penetration dashboard.

Module 6: Applied Energy Analytics Projects

• Project 1: Electricity demand forecasting using Excel & Power BI.
• Project 2: Oil and gas production trends dashboard.
• Project 3: Energy efficiency analysis for a utility company.
• Group presentations of projects & peer feedback.