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2707 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 areas2707 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 Architecture96 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 Architecture98 Streaming & Real-Time Data93 Data Governance & Semantics91 Frontend & Experience Architecture91 Edge, Mobile & IoT88 Regulatory & Data Protection Architecture90 Assurance, Audit & Model Risk98
Difficulty Any beginner intermediate advanced

6 questions in Warehouse, Lake & Lakehouse.

  1. Warehouse, Lake & Lakehouse beginner Multiple choice

    A 40-person company has 80 GB of analytical data growing about 4 GB a month, six analysts, a nightly load from Postgres and four SaaS sources, and no data engineer. An architect proposes an object-storage lakehouse with an open table format so the company never has to migrate again. What should they build first?

    2 min answer lakehousewarehousepragmatismsizing
  2. Warehouse, Lake & Lakehouse advanced

    A retail client needs BI dashboards for 400 concurrent users and a data science platform over the same data. One lakehouse or a lakehouse plus a serving layer?

    2 min answer lakehousearchitectureconcurrency
  3. Warehouse, Lake & Lakehouse advanced

    Datadog has published the design of Husky, its third-generation event store, which splits writers, readers and compactors into independently scaled services over a shared metadata store and commodity object storage rather than running one storage tier. What problem forces that separation, and where would copying it be a mistake?

    2 min answer datadoghuskycompactioncolumnar
  4. Warehouse, Lake & Lakehouse intermediate

    How should a platform decide between a warehouse, a lake and a lakehouse for a given workload?

    2 min answer warehouselakelakehouseworkload-fit
  5. Warehouse, Lake & Lakehouse advanced

    Leadership wants to consolidate a warehouse, a data lake and three departmental marts into a lakehouse. How do you scope and sequence this?

    2 min answer data-platformmigrationlakehousestrategy
  6. Warehouse, Lake & Lakehouse intermediate

    Notion runs its product on sharded Postgres and originally loaded analytics into a managed warehouse through off-the-shelf connectors. In 2022 it built its own data lake on change data capture into Kafka, Hudi tables and S3 instead. What forced that, and where would copying it be a mistake?

    2 min answer notionhudicdclakehouse