Stress testing, a component of scalability testing, aims to determine the system's robustness and its ability to handle extreme conditions beyond its normal operational capacity. By subjecting the system to high loads or excessive stress, it helps identify potential bottlenecks, weak points, or performance limitations. This allows developers to optimize the system's performance and ensure its scalability under stressful conditions.

Data Quality Testing is required in this scenario to ensure that the data transformations are working correctly and that the data being loaded into the warehouse meets the expected quality standards. This involves validating data accuracy, completeness, consistency, and integrity throughout the ETL process. By performing comprehensive data quality tests, you can identify and rectify issues related to incorrect data transformations, ensuring the accuracy and reliability of the data in the data warehouse.

Query optimization plays a crucial role in SQL testing as it aims to enhance the performance of SQL queries by optimizing their execution plans. This involves identifying inefficient query execution paths and reorganizing or rewriting the queries to improve their efficiency. By optimizing SQL queries, it reduces the response time and resource utilization, thereby enhancing the overall performance of the database system.

Data cleansing is a critical step in the ETL process, where data is cleaned, standardized, and validated to ensure accuracy and consistency. This process improves the quality of data analysis and decision-making by providing reliable and trustworthy data. Testing data cleansing functionalities ensures that the ETL process effectively handles data quality issues and produces reliable results.

Partitioned indexing allows for efficient management of large datasets by dividing them into smaller, manageable chunks for faster access.

The data mapping document specifies the relationships between the source and target systems, guiding the data migration process by detailing how data from various sources will be mapped to the corresponding target.

The correct option is "Summary". Test summary reports play a vital role in communicating key information about the testing process to stakeholders. These reports typically include essential metrics, trends, and findings from the testing activities, providing stakeholders with valuable insights into the quality of the product and areas that require attention.

Testing large datasets presents scalability challenges, where the database system's ability to handle increasing amounts of data efficiently is put to the test. Scalability issues involve ensuring that the system maintains its performance and responsiveness as the dataset size grows, avoiding performance bottlenecks that can hinder overall database functionality.

The SQL statement commonly used for testing the integrity of primary keys in a table is "ALTER TABLE ... ADD CONSTRAINT ... PRIMARY KEY". This statement is used to add a primary key constraint to a table, ensuring that the specified column(s) uniquely identify each row and enforcing data integrity. By adding a primary key constraint, it becomes impossible to insert duplicate or null values into the primary key column(s), thus maintaining the integrity of the data.

Common signs of SQL injection vulnerability include the presence of unsanitized user input directly concatenated into SQL queries, error messages that reveal database structure or query information, and the absence of input validation mechanisms. These indicators suggest that the system does not adequately sanitize and validate user input, making it vulnerable to SQL injection attacks.