🔍 Project Overview

The real estate industry is highly competitive and data-driven. Understanding sales trends, pricing behavior, and market performance is essential for maximizing profitability and enhancing stakeholder satisfaction for investors, real estate agents, or buyers/sellers. Leveraging data insights allows business owners and relevant parties to make informed decisions to improve their strategies and operations.

The data presented in this project is based on real estate transaction data and is structured into the following key dashboards:

Overall: Displays price and sales volume trends, key market KPI performance, and property distribution.
Property Type Analysis: Provides in-depth insights into the performance and price trends of each property type.
Location Analysis: Analyzes prices and sales in each town/location to identify high-potential areas.

🧰 Tools Used

Power BI Desktop
Power Query for data cleaning
DAX for calculated measures and KPIs
Data modeling using Star Schema
Custom visuals including: Maps, Pie Charts, Bar/Line Charts, KPIs

🧱 Data Source

Dataset: Real Estate Sales (2001–2022)

The dataset contains detailed property sales records across multiple towns from 2001 to 2022. It includes information such as: