Effective MongoDB schema design is crucial for building scalable applications. Unlike relational databases, MongoDB uses documents and collections, offering flexibility in data modeling. Key patterns include embedding documents for one-to-few relationships, referencing for one-to-many relationships, and denormalization for read-heavy workloads. Proper indexing dramatically improves query performance—create indexes on frequently queried fields and use compound indexes for complex queries. Consider data access patterns when designing schemas, and use aggregation pipelines for complex data transformations.