Dashboard
- District-wide KPI cards
- Water-use trend
- GIS / system map
- Recent alerts
- Conservation status
- Quick actions
Flagship Demonstration Project
Water Agency
Water Agency
Data Platform
What if your utility's data actually worked together?
A unified platform that brings together customer, meter, property, consumption, GIS, conservation, alerts, and reporting — so a water agency can see its whole operation in one place and act on it.
The Idea
From Disconnected Data
From Disconnected Data
to a Useful System.
Water agencies run on data that usually lives in separate places — billing, meters, GIS, spreadsheets, and field notes that rarely talk to each other. This project demonstrates what happens when that data is connected: staff can look up a property, see its meter and usage history, spot a possible leak, view it on the map, and open a work order — all in one flow.
It's built to look and behave like a realistic utility application, using a fictional agency — Clearview Water District — and entirely synthetic data. No employer, customer, or production data is used.
What It Brings Together
- Customer & account data
- Meter & consumption
- Parcels & property
- GIS & infrastructure
- Conservation targets
- Alerts & leak detection
- Work orders
- Reports & analytics
The Connected Workflow
The core demonstration follows one complete path — the everyday job of answering "what's going on with this account?"
DashboardDistrict at a glance
→
LookupAddress · APN · Meter ID
→
Property / MeterFull detail
→
ConsumptionUsage & trends
→
MapSpatial context
→
Alerte.g. possible leak
→
Work OrderTake action
Example built into the demo data: a meter whose normal use is ~450 gallons/day suddenly reading ~1,900 gallons/day — automatically flagged as a possible continuous leak, ready for a work order.
Key Modules
Property & Meter Detail
- Property, APN & service connection
- Meter & account information
- Current, historical & expected usage
- Leak indicators
- Map location
- Alerts, work orders & notes
Alerts & GIS Map
- High water use
- Possible leak
- No read
- Layers: parcels, meters, infrastructure
- Service areas & alerts
- Map connects to property detail
Under the Hood
Practical, Connected Architecture.
The same kind of integration Mad Man Data builds for clients: validated data, a Python ETL pipeline into PostgreSQL and PostGIS, with analytics and GIS feeding a single API that powers the dashboard, maps, and reports.
Python ETLPostgreSQLPostGISAPIAnalyticsGIS
Synthetic / source data
↓
Data validation
↓
Python ETL
↓
PostgreSQL + PostGIS
↓
Analytics + GIS → API
↓
App: Dashboard · Maps · Reports