Analytics & Data

Event streams, transactions and application records become useful only when something turns them into answers. Analytics & Data tools do that work across product and web measurement, warehouse-native reporting, natural language query layers translating a question into SQL, anomaly detection, cohort and funnel analysis, attribution modeling, and written summaries explaining what moved. Some also own collection: event schemas, identity resolution and consent-aware tracking.

Analysts, product managers checking a release, growth teams measuring campaigns, and operators who want a weekly number without opening a query editor all use them. Concrete work: finding where people abandon an onboarding flow, explaining a dip in conversion, reconciling two systems reporting different totals, and giving non-technical staff self-serve access without letting definitions drift. Differences that count: warehouse and source connectors, governed metric definitions, row-level and role-based permissions, sampling behavior at scale, data residency, and whether generated SQL is shown before it runs.

Validate a natural language layer against questions whose answers are already known, since a confident wrong number does more damage than none. Confirm how metrics are defined and who may change them, then test permissions with a genuine non-admin account. Recurring problems: identity stitching that splits or inflates user counts, attribution models compared as if interchangeable, and warehouse bills driven by refresh frequency. Pricing shapes include capped free tiers, per-seat or viewer plans, volume tiers and consumption billing.