What is the purpose of identifying schema anti-patterns in MongoDB?

Identifying schema anti-patterns in MongoDB primarily serves to improve schema design and efficiency, making option B the most appropriate choice. In the context of database management, schema anti-patterns refer to common mistakes or bad practices in schema design that can lead to inefficient data modeling and performance issues.

By recognizing these anti-patterns, developers can redesign their schema to better align with MongoDB’s document-oriented nature, enhancing the overall effectiveness of data storage and retrieval operations. This can involve revisiting data structures, optimizing relationships, and ensuring that the design aligns with how applications will access and interact with the data.

Improving schema design ultimately leads to better data throughput and reduced latency during queries, even though those specific benefits might not be the primary purpose of identifying anti-patterns. Strengthening schema efficiency can also simplify data management and improve maintainability, ensuring that the database scales effectively with use.

The other options, while they touch upon important aspects of database management, do not capture the core goal of identifying schema anti-patterns as effectively. For example, increasing storage capacity and simplifying backups are secondary benefits that may arise from improved schema design but are not the main focus. Enhancing data retrieval speed might be an end result of addressing schema anti-patterns