Scalable Data Architecture and Modeling Questions

Design data architectures and data models that support high performance analytics and dashboards at scale. Topics include schema design patterns such as star and snowflake schemas, normalization versus denormalization trade offs, indexing and partitioning strategies, materialized views and aggregation layers, appropriate use of real time versus scheduled batch updates, storage and file format considerations, query pattern driven modeling, handling large volumes and high concurrency, refresh and latency trade offs, monitoring and performance tuning, cost versus performance trade offs, and data governance and lineage to ensure correctness and maintainability. Interview candidates should be able to reason about architecture decisions in the context of query performance, update cadence, concurrency, and operational constraints.