Which section in Data Explorer is focused on improving your schemas?

The section dedicated to improving schemas in Data Explorer is the one focused on schema anti-patterns. This section specifically identifies and highlights common schema designs that can lead to inefficient data access patterns, poor performance, or data inconsistency. By recognizing these anti-patterns, developers can better understand how to restructure or optimize their schemas for more effective data storage and retrieval practices.

This focus on anti-patterns is crucial because it not only helps in diagnosing potential issues with current database designs but also guides developers toward best practices when designing schemas. Identifying anti-patterns allows for proactive adjustments that can significantly enhance the overall database performance and maintainability.

In contrast, data visualization generally aids in presenting and interpreting data rather than directly improving schema design. Collection stats provide insights into the size, count, and data types within collections, useful for performance but not explicitly focused on schema improvement. Performance metrics offer information on query execution times and resource usage, which, while related, do not specifically address schema issues as directly as schema anti-patterns do.