Both ETL testing and database testing involve data validation,
but they are not the same.ETL testing is normally performed on data in a data warehouse system, whereas database testing is commonly performed on transactional systems where the data comes
from different applications into the transactional database.
ETL Testing
ETL testing involves the following operations:
1. Validation of data movement from the source to the target system.
2. Verification of data count in the source and the target system.
3. Verifying data extraction, transformation as per requirement and expectation.
4. Verifying if table relations – joins and keys – are preserved during the
transformation.
Common ETL testing tools include QuerySurge, Informatica, etc.
Database Testing
Database testing stresses more on data accuracy, correctness of data and valid values.
It involves the following operations:
1. Verifying if primary and foreign keys are maintained.
2. Verifying if the columns in a table have valid data values.
3. Verifying data accuracy in columns.
Example: Number of months column shouldn’t have a value greater than 12.
4. Verifying missing data in columns. Check if there are null columns which actually
should have a valid value.
Common database testing tools include Selenium, QTP, etc.
Difference (Database and ETL)
Primary Goal
Data validation and Integration and ETL -Data Extraction, Transform and
Loading for BI Reporting
Applicable System
Transactional system where business flow occurs and ETL-System containing historical
data and not in business flow environment
Common tools
QTP, Selenium, etc. and ETL -QuerySurge, Informatica, etc.
Business Need
It is used to integrate data from multiple applications, Severe impact. and ETL It is used for Analytical Reporting, information and forecasting.
Modeling
ER method and ETL -Multidimensional
Database Type
It is normally used in OLTP systems and ETL It is applied to OLAP systems
Data Type
Normalized data with more joins and ETL -De-normalized data with less joins, more indexes, and aggregations.
but they are not the same.ETL testing is normally performed on data in a data warehouse system, whereas database testing is commonly performed on transactional systems where the data comes
from different applications into the transactional database.
ETL Testing
ETL testing involves the following operations:
1. Validation of data movement from the source to the target system.
2. Verification of data count in the source and the target system.
3. Verifying data extraction, transformation as per requirement and expectation.
4. Verifying if table relations – joins and keys – are preserved during the
transformation.
Common ETL testing tools include QuerySurge, Informatica, etc.
Database Testing
Database testing stresses more on data accuracy, correctness of data and valid values.
It involves the following operations:
1. Verifying if primary and foreign keys are maintained.
2. Verifying if the columns in a table have valid data values.
3. Verifying data accuracy in columns.
Example: Number of months column shouldn’t have a value greater than 12.
4. Verifying missing data in columns. Check if there are null columns which actually
should have a valid value.
Common database testing tools include Selenium, QTP, etc.
Difference (Database and ETL)
Primary Goal
Data validation and Integration and ETL -Data Extraction, Transform and
Loading for BI Reporting
Applicable System
Transactional system where business flow occurs and ETL-System containing historical
data and not in business flow environment
Common tools
QTP, Selenium, etc. and ETL -QuerySurge, Informatica, etc.
Business Need
It is used to integrate data from multiple applications, Severe impact. and ETL It is used for Analytical Reporting, information and forecasting.
Modeling
ER method and ETL -Multidimensional
Database Type
It is normally used in OLTP systems and ETL It is applied to OLAP systems
Data Type
Normalized data with more joins and ETL -De-normalized data with less joins, more indexes, and aggregations.
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