________ transformation is used to aggregate data from multiple rows into a single row.
- Aggregate
- Combine
- Concatenate
- Merge
The correct term is "Aggregate" transformation. This transformation is used to combine and summarize data from multiple rows into a single row, often involving functions like sum, average, or count.
What role does version control play in maintaining the history of ETL test cases and scripts?
- Enhances data quality
- Facilitates data loading
- Manages transformations
- Tracks changes and revisions
Version control tracks changes and revisions in ETL test cases and scripts, maintaining a comprehensive history. This helps in traceability, auditing, and understanding the evolution of test artifacts over time.
Which data loading strategy is typically used for small and simple datasets?
- Batch Loading
- Incremental Loading
- Parallel Loading
- Real-time Loading
Batch Loading is typically used for small and simple datasets. In this strategy, data is collected, processed, and loaded in batches, making it suitable for less complex data scenarios.
What tool is commonly used for automated ETL testing?
- Apache JMeter
- Informatica
- Jira
- Selenium
Informatica is a commonly used tool for automated ETL testing. It provides features for automating and managing the ETL processes, ensuring data quality and integrity.
What aspect of the ETL process is typically the focus in initial performance tests?
- Data Extraction
- Data Loading
- Data Transformation
- Overall System Throughput
Initial performance tests in ETL processes typically focus on the Data Loading aspect. This includes evaluating the speed and efficiency of loading transformed data into the target system.
What is the impact of data deduplication on the performance of ETL processes?
- Data deduplication has no impact on ETL performance
- Data deduplication improves ETL performance by reducing storage and processing overhead
- Data deduplication is only relevant for data loading
- Data deduplication slows down ETL processes
Data deduplication positively impacts ETL performance by reducing storage and processing overhead. It eliminates redundant data, leading to more efficient processing and improved overall performance.
What is the primary goal of Test Data Management in ETL testing?
- Ensuring data consistency
- Facilitating data extraction
- Managing test environments
- Providing real-time data
The primary goal of Test Data Management in ETL testing is to manage test environments effectively. It involves creating, maintaining, and refreshing test data to ensure that the testing process is conducted in a controlled and reliable environment.
For advanced data analytics, BI tools integrate with ________ to provide deeper insights.
- Blockchain
- Cloud Storage
- Machine Learning
- Virtualization
For advanced data analytics, BI tools integrate with Machine Learning to provide deeper insights. Machine Learning algorithms enable predictive and prescriptive analytics, uncovering patterns and trends in the data for more informed decision-making.
__________ integrity checks are essential for ensuring consistency and avoiding anomalies in ETL processes.
- Data
- Entity
- Referential
- Structural
Referential integrity checks play a crucial role in ETL processes. They ensure that relationships between tables are maintained, preventing inconsistencies and anomalies in the data.
In data transformation logic, what is the significance of a merge transformation?
- It combines multiple data streams into a single stream
- It divides a single data stream into multiple streams
- It performs data cleansing operations
- It validates data integrity
A merge transformation in data transformation logic is significant as it combines multiple data streams into a single stream. This consolidation of data is useful for integrating information from different sources or stages of processing, enabling further analysis or loading into target systems.