Property Data Engineering Sprint - Part 4
Multi-page Power BI dashboard with interactive analysis of property, rental, crime, school, and transport data built over a dimensional model.

House Values Dashboard
Project Overview
- Objective: Build an interactive Power BI dashboard over the star schema to explore state-wide housing and public service data by location.
- Tools Used: Power BI, SQL Server (DW connection), DAX, Drillthrough, Custom Groups/Buckets, Map Visualizations
Dashboard Pages
- House Value: Distribution and median trends by suburb, city, and state with grouped value buckets.
- Rental Value: Analysis by property type, region, and grouped rent brackets.
- School Data: Breakdown by type, location, and number of schools with maps and filters.
- Transport: Count of stations by city and suburb, mapped by transport mode.
- Crime Summary: Incidents grouped by category and subcategory with slicers by region and date.
- Summary Page: High-level stats and KPIs with clickable drillthrough to detailed pages.
- Home Page (Optional): Navigation tiles with image buttons linking to individual reports.
Key Features
- Dynamic Bucketing: Created DAX columns to group house and rent values into ranges (e.g. “$400K–$600K”, “Above $600”).
- Drillthrough Enabled: Clickable summary page metrics link directly to filtered report views.
- Custom Tooltips: Hover over charts to see more details like suburb count and average metrics.
- Fully Connected Data Model: Connected fact tables to dimensions through appropriate surrogate keys with proper cardinality and cross-filtering.
Insights Discovered
- House prices above $800K were heavily concentrated in capital city suburbs.
- Rental affordability was lowest in high-transport-density suburbs with good schools.
- Crime reporting showed higher variation by suburb than by state, supporting location-based policy recommendations.
Key Skills Demonstrated
- Interactive report building using Power BI's visual and modeling tools.
- Custom DAX measures and calculated columns for grouping and conditional analysis.
- Map visualizations using latitude/longitude from dimension tables.
- User-friendly dashboard layout with navigation and drillthrough support.