Quiz

2667 questions of the kind that actually get asked — in interviews, in architecture review boards, and by the person who has to run the thing at 3 AM. Every answer states the trade-off rather than the slogan, and says when the obvious choice is the wrong one.

All areas2667 Architecture Fundamentals81 Distributed Systems101 Data Architecture90 Cloud Architecture87 Networking86 API & Integration Architecture78 Reliability & Resilience88 Observability81 Performance & Capacity Engineering90 Security Architecture95 Cost Architecture & FinOps92 Business Architecture93 Architecture Communication91 Enterprise Architecture91 Legacy Modernization92 AI-Era Architecture86 Software Architecture & Engineering84 Architecture Patterns84 Architecture Decision-Making91 The Architect's Meta-Skills92 Delivery & Release Engineering93 Platform Engineering & Developer Experience92 Testing & Quality Architecture90 Data Platform Architecture88 Streaming & Real-Time Data93 Data Governance & Semantics81 Frontend & Experience Architecture91 Edge, Mobile & IoT88 Regulatory & Data Protection Architecture90 Assurance, Audit & Model Risk88

Difficulty Any beginner intermediate advanced

90 questions in Data Architecture.

Quiz

A GDPR erasure request arrives for a customer. Where does their data actually live, and what makes this expensive to retrofit?

A consumer fintech accumulates transaction, behavioural and derived data. How should retention, archival, deletion and regulatory holds be designed so they do not conflict?

A customer exercises their right to erasure. List every place their data plausibly exists in a mature architecture and how each is handled.

A file storage platform must permanently delete a user's data on request, while maintaining backups, replicas, caches and search indexes. What makes this genuinely difficult, and how is it designed?

A finance report double-counts revenue after a new fact table is added. What is the likely modelling error?

A travel platform runs thousands of experiments simultaneously and needs its warehouse to support reliable analysis. What warehouse design decisions prevent cross-experiment contamination and infrastructure artefacts from being read as results?

An analytics platform separates compute from storage. What does that actually buy architecturally, and what problems does it not solve?

Finance and marketing report different revenue for the same month from the same warehouse. Where do you look and what would have prevented it?

A daily pipeline has been producing wrong numbers for three weeks due to a logic bug. What must be true of the architecture for the fix to be a one-day job?

A grocery platform ingests catalogue and inventory feeds from hundreds of retailers, each with different formats, quality and update frequency. Should transformation happen before loading or after, and where should data quality be enforced?

A nightly pipeline failed halfway and the retry produced duplicate rows. Walk me through fixing this properly.

A brokerage proposes event sourcing for its account ledger. What requirements would genuinely justify it, and when is conventional state plus an audit trail the safer choice?