The classic system-design question, modelled properly: short codes from a base62 counter, custom aliases and custom domains, an append-only click log with daily rollups, expiry and click limits, QR codes and blocked-domain safety checks.
How an API platform is modelled: consumers and applications, hashed API keys with scopes and rotation, upstream services and routes, rate limit policies, durable usage counters, rolled-up aggregates, sampled request logs, plans, quotas and overage billing.
How a build system models its data: versioned pipeline definitions, immutable runs triggered by a commit, stages with approval gates, a job DAG stored as edges, runners and capabilities, attempts and retries, artifacts, caches and streamed logs.
How an error monitoring service models its data: projects and releases, raw events with stack frames and breadcrumbs, grouping into issues by fingerprint, resolve and regression detection, alert rules and event sampling.
How a feature management platform stores its data: flags and variations, per-environment settings, ordered targeting rules, reusable segments, percentage rollouts with deterministic bucketing, scheduled changes and a full audit trail.