This project focuses on analyzing energy consumption data using Microsoft Power BI to derive actionable insights for better decision-making. It involves importing datasets, performing data cleaning and transformation, building interactive dashboards, and identifying trends in energy usage.
- Visualize energy consumption patterns across various parameters (time, location, source, etc.).
- Identify peak usage hours and seasonal trends.
- Compare renewable vs non-renewable energy sources.
- Generate insights to support sustainability goals and energy efficiency.
- Power BI Desktop
- Microsoft Excel / CSV Data
- DAX (Data Analysis Expressions)
- Power Query Editor
The dataset used in this project includes:
- Timestamps of energy usage
- Energy consumption values (kWh)
- Location/region
- Type of energy source (Renewable/Non-renewable)
- Interactive Dashboards: Slice and filter energy data by year, region, and source type.
- Trend Analysis: Visual line charts showing energy consumption trends over time.
- Pie Charts & Bar Graphs: Breakdown of renewable vs non-renewable energy usage.
- KPIs: Total consumption, average daily usage, and % change over months.
- Handled missing or null values.
- Converted timestamp formats to proper date/time values.
- Created calculated columns and measures using DAX.
- Grouped data by time intervals (monthly/yearly) for better analysis.
- Hands-on experience with Power BI for real-world business analysis.
- Creating clean, informative, and dynamic reports.
- Applying data transformation and DAX techniques effectively.
- Open Power BI Desktop.
- Import the
.pbixfile or the raw CSV dataset. - Use the Power Query Editor to clean and prepare the data.
- Explore the dashboards and reports.