Associate Data Modeler

As a MongoDB Associate Data Modeler, I possess a comprehensive understanding of the entire data modeling lifecycle. I am skilled in gathering application requirements, identifying crucial application operations that necessitate performance-optimized document designs, and pinpointing all prerequisite information needed for effective data modeling. I can accurately identify and group persisted data entities within their respective domains, recognizing domain ownership and potential needs for data duplication or synchronization. Furthermore, I can map the relationships between these entities, understand their cardinality, and distinguish between strong and weak entities based on application object analysis.

My capabilities extend to analyzing workload and usage patterns, including identifying entities required by CRUD operations and determining which operations are most impactful for data persistence or retrieval, while also considering retention requirements and retrieval times for active and historical data. Based on these analyses, I can design optimal data models by defining usage patterns, determining when to apply schema design patterns such as computed, versioning, and subset, and deciding between embedding versus referencing, always documenting the tradeoffs involved. I am proficient in implementing these designs using MongoDB patterns, including schema validation to meet business requirements and technical specifications like performance for data creation, modification, and retrieval.

Finally, I am adept at developing effective indexing strategies by analyzing query and analytics patterns, ensuring appropriate key fields are indexed using various types like wildcard or TTL indexes, and applying methods like the ESR (Equality, Sort, Range) rule. I can also analyze the performance of these indexes and storage strategies to select the optimal approach for both common and uncommon queries, including interpreting explain plans. My skills also cover monitoring implemented data models, tracking business and technical changes, and determining when to iterate or make schema modifications to support evolving application needs and business goals.