Forget rigid relational schemas; MongoDB offers flexibility. That power demands careful schema design. Poor choices lead to performance bottlenecks and data integrity issues, especially with the rise of real-time applications needing lightning-fast data access. For example, embedding excessively large arrays can cripple read performance, while neglecting proper indexing on frequently queried fields leaves your queries crawling. We'll explore practical examples: how to structure product catalogs for e-commerce platforms needing faceted search, or how to model user activity streams in social media applications for efficient aggregation. Learn to leverage techniques like denormalization strategically and choose the right data types to maximize efficiency and ensure your MongoDB database scales gracefully under pressure.