How a mortgage lender models a file in Oracle: borrowers and co-borrowers with income and liabilities, the subject property and its appraisals, rate locks that expire, underwriting decisions and conditions to clear, a document checklist, closing and disbursement.
How a consumer lender models its data in Oracle: applications and verified income, credit decisions with ranked adverse-action reasons, loans, the amortisation schedule as rows, repayments allocated across fees, interest and principal, delinquency buckets and collections.
How a property portal models its data: properties as durable things versus listings as repeatable campaigns, agents and agencies, ordered media, amenities, price history as rows, viewings, offers and saved searches with alerts.
Landlord operations modelled end to end: buildings and units, leases and renewals, co-tenants and guarantors, rent charges generated per period, payments allocated against them, deposits held and returned, maintenance with vendors, and inspections.
An experimentation platform end to end: experiments and weighted variants, deterministic hash bucketing, exposure events, metric definitions, per-variant aggregates with sufficient statistics, significance results and staged rollout.