________ testing is employed in data lakes to verify the accuracy and consistency of analytical queries.
- Integration
- Performance
- Query
- Regression
"Query" testing is employed in data lakes to verify the accuracy and consistency of analytical queries. This ensures that the queries provide reliable results, supporting the data lake's analytical capabilities.
What is the primary purpose of a data lake in a data management ecosystem?
- Storing data summaries
- Storing only metadata
- Storing structured data
- Storing unstructured data
The primary purpose of a data lake is to store unstructured data in its raw format. This allows organizations to collect and analyze vast amounts of data without the need for pre-processing or schema definition, providing flexibility in data exploration and analysis.
What is the primary purpose of a test case in software testing?
- To design the software
- To document requirements
- To execute code
- To find defects
The primary purpose of a test case in software testing is to find defects. It involves systematically verifying whether the application behaves as expected and identifying any deviations or issues.
In ETL, ________ is a technique used to compare source and target data for validating data integrity.
- Data Deduplication
- Data Matching
- Data Merging
- Data Reconciliation
In ETL, Data Reconciliation is a technique used to compare source and target data for validating data integrity. It ensures that the data loaded into the target system matches the expected results after the transformation process.
In complex ETL testing scenarios, ________ is used to replicate real-world data conditions accurately.
- Data Masking
- Data Profiling
- Data Subsetting
- Synthetic Data Generation
In complex ETL testing scenarios, Synthetic Data Generation is used to replicate real-world data conditions accurately. It involves creating artificial but realistic data for testing purposes.
In ETL testing, how is data reconciliation used to ensure data accuracy and consistency?
- It involves comparing source and target data counts only
- It is not used in ETL testing
- It reconciles data at each ETL stage to identify discrepancies
- It validates data using statistical methods
Data reconciliation in ETL testing involves comparing data at each stage of the ETL process to identify discrepancies. This ensures data accuracy and consistency throughout the transformation and loading phases.
What is the primary purpose of data transformation in the ETL process?
- Clean and validate data
- Extract data from sources
- Move data from source to target
- Store data in a data warehouse
The primary purpose of data transformation in the ETL process is to clean and validate data. This step ensures that the data meets quality standards and conforms to the requirements of the target system.
________ in ETL involves ensuring that data is consistent and correct across the system.
- Cleansing
- Standardization
- Transformation
- Validation
The Validation step in ETL is responsible for ensuring that data is consistent and correct throughout the system. It involves checks and validation rules to maintain data quality.
Manual testing is often preferred when ________ is a key requirement.
- Complexity
- Precision
- Repeatability
- Speed
Manual testing is often preferred when Repeatability is a key requirement. In certain situations where test cases need to be executed with various data sets or under changing conditions, manual testing provides flexibility and adaptability.
In ETL, ________ is used to extract data from different sources.
- Extraction
- Integration
- Loading
- Transform
In ETL, the process of Extraction is used to gather data from various sources. It is the initial step where data is collected for further processing in the ETL pipeline.