Analyzing Query Patterns

To build an efficient data model, you need to understand the kinds of queries it will handle most often (common query patterns).

Types of query patterns

1. Transactional queries: Fast, simple queries on recent data
2. Analytical queries: Complex queries on large datasets, often historical
3. Real-time aggregations: Continuous calculations on streaming data
4. Periodic reporting: Scheduled, batch-oriented data processing

Example query patterns across domains

Considerations for query patterns

Consider these aspects:

1. Frequency of queries (real-time vs. batch)
2. Complexity of joins required
3. Level of aggregation needed
4. Time range of data typically queried

Questions to ask about query patterns

• "What are the most frequent queries this data model needs to support?"
• "Are there any particularly complex queries that need optimization?"
• "How does the query pattern change for historical vs. recent data?"