Data quality tools assist in GDPR compliance by ensuring data anonymity. They can anonymize sensitive information, protecting privacy and meeting regulatory requirements without compromising data quality.

Change Data Capture (CDC) in a Data Warehouse is the process that helps in maintaining the history of data changes over time. It captures and tracks modifications to the data, providing a historical perspective for analysis.

The process of normalizing a database involves dividing it into Tables. Normalization is a technique that helps organize data efficiently and reduces redundancy by dividing tables into smaller, related tables.

Partitioning in BI tools is crucial for handling large volumes of data efficiently. It involves dividing data into smaller, manageable segments, improving query performance and data retrieval speed.

When dealing with streaming data integration into a data lake, testing strategies should include Batch and Real-time Processing Testing. This ensures that both the traditional batch processing and real-time streaming components are validated for accuracy and performance.

Manual testing is more efficient for repetitive test cases in ETL. It allows testers to apply human intelligence to identify patterns and variations that may not be easily captured in automated scripts.

SQL Server Integration Services (SSIS) is a Microsoft ETL tool that seamlessly integrates with SQL Server. It allows for efficient data extraction, transformation, and loading within the Microsoft ecosystem.

Star schema is commonly used in BI tools to optimize query performance. It consists of a central fact table linked to multiple dimension tables, allowing for efficient data retrieval and analysis.

Batch Loading is the most appropriate technique in this scenario. It involves processing data in predefined batches, ensuring consistency by handling large volumes of data efficiently. Although it may not provide real-time updates, it ensures data integrity and consistency, which is crucial in scenarios where data consistency is paramount.

The recommended approach for dealing with defects that cannot be resolved immediately in ETL testing is Deferred Resolution. This involves documenting the defect and planning its resolution in a subsequent release or update, allowing for a more thorough and non-disruptive resolution process.