Nodes in Visual Explain diagrams represent different operations involved in query execution. These operations can include things like table scans, index scans, sorts, and joins. Understanding these operations helps in analyzing and optimizing query performance. 

Views in DB2 can be used to simplify data access. They provide a virtual representation of the data stored in one or more tables, allowing users to retrieve and manipulate data without directly accessing the underlying tables. Views can filter data, join multiple tables, and present a subset of columns, making it easier for users to work with the data according to their requirements. 

The compression dictionary in DB2 helps in reducing storage space by storing frequently used values in a separate dictionary. This dictionary stores repetitive values, allowing for more efficient data compression. 

DB2 ensures data security through encryption at rest, which encrypts the data while it is stored on disk, making it unreadable without the appropriate decryption key. This helps protect sensitive information from unauthorized access even if the physical storage is compromised. 

Option 3, tuning database configuration parameters, involves adjusting settings such as buffer pool size, lock timeout, and memory allocation to optimize database performance. This step can help address issues such as inefficient resource utilization or contention, which may be causing the performance bottleneck during peak hours. Monitoring system resources (option 2) and optimizing indexing strategy (option 4) are important steps but may not directly address configuration issues leading to performance degradation. Analyzing query execution plans (option 1) is helpful for identifying specific queries causing performance issues but may not resolve underlying configuration problems. 

Clustering keys in DB2 determine the physical order of rows within a table. They're used to organize similar data together on disk, enhancing performance by reducing the need for random disk accesses during queries. 

The FETCH statement in DB2 cursor operations is used to retrieve the next row from the result set of the cursor. Each time FETCH is executed, it advances the cursor to the next row in the result set, allowing the application to process the rows sequentially. FETCH returns the data from the current row and moves the cursor to the subsequent row for subsequent fetch operations. 

The Reorg utility reorganizes data pages and indexes, which improves database performance by optimizing the physical storage layout, reducing fragmentation, and reclaiming unused space. 

Denormalization involves increasing redundancy by storing redundant data to improve query performance. However, this can lead to potential data inconsistency issues if the redundant data is not properly maintained. While denormalization can enhance query performance by reducing the need for joins, it comes at the cost of increased storage space and the risk of data anomalies. Thus, the trade-offs of denormalization include balancing data redundancy for improved query performance. 

Monitoring in DB2 serves the purpose of identifying performance issues such as slow queries or bottlenecks, enabling administrators to optimize database performance. It involves tracking resource usage, query execution times, and system health indicators.