This thing had like ten sub-domains crammed into one question.
Start by clarifying the scope and key requirements of the demand-side platform, then propose a normalized relational schema that captures the core entities and their relationships. Emphasize how the model supports scalability, auditability, and efficient querying for delivery and frequency capping.
Pro tip: Highlight the importance of separating transactional and analytical workloads, and discuss how you would handle high-volume delivery tracking with partitioning or time-series databases. Also, mention that auditability often requires immutable logs and versioning of targeting and creative assignments.
Ask questions to understand the scale, key use cases, and constraints (e.g., real-time bidding, reporting needs, compliance). Confirm whether the model should support multiple advertisers and agencies, and how granular delivery tracking must be.
List the main entities: Advertiser, Agency, Line Item, Targeting Criteria, Creative, Delivery Record, Frequency Cap, and Audit Log. Define their relationships, such as an advertiser having multiple line items, and a line item having multiple creatives and targeting rules.
Propose tables with primary and foreign keys, and consider normalization vs. denormalization for performance. For delivery tracking, suggest partitioning by date and using a columnar or time-series store for analytics.
Explain how frequency caps can be enforced using a separate service or a distributed cache, and how audit logs should capture all changes with timestamps and user IDs for compliance.
Talk about trade-offs between consistency and availability, and how the model can evolve to support new targeting types or real-time updates. Mention indexing strategies for common queries.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.