Visual Explain in DB2 helps developers optimize database application performance by identifying opportunities for index usage optimization. By analyzing the query execution plan generated by Visual Explain, developers can determine whether the queries are utilizing indexes efficiently. Efficient index usage can significantly enhance query performance by reducing the need for full table scans and minimizing disk I/O operations. Therefore, leveraging Visual Explain enables developers to make informed decisions about index creation, modification, or deletion to enhance the overall performance of the database application. 

AES (Advanced Encryption Standard) is commonly used for data encryption in DB2. AES is a symmetric encryption algorithm known for its security, efficiency, and widespread adoption in various applications, including database systems. It provides strong encryption capabilities, ensuring the confidentiality and integrity of sensitive data stored in DB2 databases. 

The primary goal of an IDE like IBM Data Studio is to boost developer productivity. It achieves this by providing a centralized platform with tools and features tailored to streamline various development tasks such as writing and debugging code, managing database schemas, and optimizing performance. By offering an integrated set of tools and a user-friendly interface, developers can work more efficiently, reducing the time and effort required to complete tasks. 

AES (Advanced Encryption Standard) is commonly used to secure data in transit in DB2. It provides strong encryption, ensuring the confidentiality and integrity of data as it travels across networks. 

In DB2, the component that defines the name of the database object within a tag is known as the tag identifier. This identifier uniquely identifies the object associated with the tag and allows users to reference and manipulate it within the database environment. For instance, when creating a tag for a table, the tag identifier would typically specify the name of the table. 

Multi-dimensional clustering (MDC) in DB2 offers advantages such as improved query performance due to reduced I/O, better space utilization, and enhanced data distribution. By organizing data into multiple dimensions, MDC optimizes query processing by grouping similar data together, which leads to reduced I/O and improved performance. Additionally, MDC can help in achieving better space utilization by storing related data together, resulting in more efficient storage allocation. 

The Runstats utility in DB2 is used to update statistical information about the tables, indexes, and columns, which helps the query optimizer to choose the most efficient access paths for retrieving data. This utility does not perform reorganization or index creation. It solely focuses on gathering statistics for better query performance. 

The correct option is option 1: SKIPHEADER. This option instructs the IMPORT utility to skip header rows present in the input file while importing data into DB2 tables. Skipping header rows is essential when the input file contains column headers or other non-data information that should not be imported into the database tables.