How does the concept of data warehousing relate to BI tool efficiency?
- Data Compression
- Data Consolidation
- Data Duplication
- Data Fragmentation
Data warehousing is about consolidating data from various sources into a centralized repository. Efficient data warehousing reduces data fragmentation, making it easier for BI tools to retrieve and analyze information. This consolidation enhances BI tool efficiency by providing a unified data source.
To protect sensitive data, ETL processes often implement ________ to restrict data access.
- Compression
- Encryption
- Hashing
- Masking
ETL processes commonly implement data masking to restrict access to sensitive information. Data masking involves replacing original data with fictional or pseudonymous data, safeguarding sensitive content during the process.
Test requirement analysis in ETL testing must consider the ________ of data sources.
- Complexity
- Integrity
- Structure
- Volume
In ETL testing, understanding the volume of data sources is crucial during test requirement analysis. This involves assessing the size and quantity of data to ensure the system can handle it effectively.
What is the primary focus of ETL Security Testing?
- Data Accuracy
- Data Availability
- Data Compression
- Data Confidentiality
The primary focus of ETL Security Testing is ensuring Data Confidentiality. It involves validating that sensitive data is protected from unauthorized access and ensuring that only authorized users can access and manipulate the data.
A company notices a decline in the data quality score after modifying their ETL process. What aspects should they investigate?
- Data Transformation Logic, Data Loading Speed, Source Data Quality, Target Data Structure
- ETL Tools Compatibility, Source System Scalability, Target System Connectivity, Data Extraction Methods
- Hardware Specifications, Network Latency, Data Encryption Methods, Data Governance Policies
- Metadata Management, Data Profiling Techniques, Data Archiving Strategies, Data Validation Techniques
When data quality declines after modifying the ETL process, investigation should focus on aspects like the correctness of data transformation logic, speed of data loading, source data quality, and compatibility with the target data structure. This helps identify and rectify issues affecting data quality.
________ is a key metric that measures the percentage of test cases executed in the ETL process.
- Completion Ratio
- Execution Rate
- Test Coverage
- Validation Percentage
Test Coverage is a key metric in ETL testing that measures the percentage of test cases executed in the ETL process. It provides insights into the extent of testing coverage.
How does risk-based testing impact the Test Execution Lifecycle?
- It accelerates the Test Execution Lifecycle
- It extends the Test Execution Lifecycle
- It has no impact on the Test Execution Lifecycle
- It shortens the Test Execution Lifecycle
Risk-based testing influences the Test Execution Lifecycle by extending it. This approach focuses testing efforts on high-risk areas, ensuring critical functionalities are thoroughly tested, which may result in a longer execution time.
How does synthetic data generation benefit Test Data Management?
- It ensures data security during testing
- It helps in creating realistic test scenarios
- It improves test data quality and availability
- It reduces the dependency on production data
Synthetic data generation benefits Test Data Management by improving test data quality and availability. Synthetic data closely resembles real data, allowing for more comprehensive testing scenarios without the need for sensitive or confidential information.
Advanced ETL testing in the cloud may require ________ for real-time data streaming.
- Data partitioning
- Event-driven architecture
- Load balancing
- Parallel processing
Advanced ETL testing in the cloud may require Event-driven architecture for real-time data streaming. This architecture allows processing based on events, enabling real-time data updates and responsiveness in the ETL process.
How is cloud computing expected to influence the future of ETL testing?
- Enhanced data security
- Faster ETL processing
- Increased scalability and flexibility
- Reduced need for testing
Cloud computing is expected to influence ETL testing by providing increased scalability and flexibility. ETL processes can leverage cloud resources for better performance and efficiency. This allows for handling varying workloads and adapting to changing business needs.