Non-clustered indexes can lead to slower data modification operations due to the need to update both the index and the underlying data.

INNER JOIN is used to combine data from two tables based on a common key. It returns only the rows where there is a match in both tables. In this scenario, it will retrieve data from both "Customers" and "Orders" tables where there is a common key, enabling you to link related information.

Access Control Lists (ACLs) are crucial components of database security that define and enforce access permissions for users or entities attempting to access database objects. ACLs specify which users or groups are granted permissions to perform specific operations (such as read, write, or execute) on particular database objects (such as tables, views, or stored procedures). By effectively configuring ACLs, database administrators can control access to sensitive data, prevent unauthorized modifications, and mitigate the risk of data breaches or unauthorized access attempts.

The primary goal of query optimization during performance testing is to minimize query execution time and resource consumption. By optimizing queries, database administrators aim to improve overall system performance, reduce response times, and enhance the scalability of the database system. This involves techniques such as index optimization, query rewriting, and efficient resource allocation.

In this scenario, the issue represents a Discretionary Access Control (DAC) problem. DAC allows users to have control over their own resources and data, often leading to situations where users can grant access to others unnecessarily, as seen with the junior analyst having access to sensitive data they don't need. Implementing stricter access controls, such as Role-Based Access Control (RBAC) or Attribute-Based Access Control (ABAC), would help mitigate this risk by ensuring that only authorized individuals can access sensitive data based on their roles or attributes.

Test data preparation in database testing refers to the process of generating data that will be used to test various aspects of the database, including its functionality, performance, and scalability. This involves creating realistic data sets that mimic the production environment and cover various scenarios that the database might encounter during actual usage.

Validity is the correct option. ETL testing aims to ensure that the data being processed through the ETL pipeline is valid, meaning it adheres to the defined rules, constraints, and requirements. This includes checking for data accuracy, completeness, and validity to ensure the reliability of the data for downstream use.

The term "Index" refers to a data structure that helps in faster data retrieval from a database table. An index is created on one or more columns of a table to facilitate quick access to rows based on the indexed column values, thereby improving the efficiency of data retrieval operations.

In load testing, the typical approach to evaluate system performance involves gradually increasing the load on the system until it reaches its breaking point or fails to meet performance criteria. This helps identify the system's limitations and potential bottlenecks under different load conditions.

Analyzing the query execution plan is crucial as it provides insights into how the database engine is processing the query. This helps identify potential bottlenecks and areas for optimization, such as missing indexes or inefficient join methods.