Meter-to-cash, water quality, main breaks, and asset condition
Industry
Water and wastewater utility
Company size
Large regional water authority with a heavy industrial base, about 63 billion gallons billed annually, roughly $695M to $725M annual operating revenue
Operating scale represented
165,000 customer accounts, 140,000 premises, 165,000 water meters (one per account), 28,000 system assets averaging 25 years in service, 80 communities, 8 pressure zones, 130 specialist field crews, 1.0 million sampled daily meter reads, 3.51 million monthly bills covering every active account in every service month, 1.2 million sampled payment transactions, 130,000 water-quality samples, 14,000 main-break events, 320,000 work orders, and 90,000 asset maintenance records
Planning note
Enterprise-tier BI kit focused on meter-to-cash, consumption, water quality and compliance, main breaks and water loss, asset condition, and field work
Carrowdale Water Authority is a fictional regional municipal water and wastewater utility built for BI teams that want a credible meter, consumption, billing, water-quality, main-break, asset, and field-work dataset without exposing real account holders, communities, infrastructure, or sample results. The authority treats and distributes drinking water, collects and bills for sewer service, samples water quality for compliance, and maintains mains, hydrants, valves, pump stations, tanks, and treatment assets. Everything in the kit is invented so analysts can model meter-to-cash performance, consumption seasonality, compliance, water loss, and asset condition in one coherent utility story.
These are the operating questions this kit is optimized to answer first.
Follow customer-class consumption into monthly water and sewer bills, due dates, payment timing, and arrears state.
Show residential and irrigation summer peaks against steadier commercial and industrial demand using sampled daily reads.
Use water-quality samples to show parameter results, compliance, and exceedance rates by zone and parameter.
Compare main-break frequency, water lost, customers affected, and restoration time by asset type, material, and zone.
Connect asset condition bands and maintenance activity back to break-prone mains and work-order workload.