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Database testing
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Database testing
Database Test Scenarios:
1. Structure Validation
a. Validate the source and target table structure as per given requirements.
b. Verify that data field types and formats are specified
c. Source data type length should not less than the target data type length.
d. Validate the name of columns in target table as per given requirements.
2. Constraint Validation
a. Primary Key Constraint should be enabled on Target Table.
b. Foreign Key Constraint validation if specified in the Target Table.
c. Not Null Constraint Validation on specified Fields as per given requirements.
d. Unique Constraint Validation on specified Fields as per given requirements.
3. Data Completeness Validation
a. Validation of rows count in Source and Target table on Each ETL Run.
b. Validation of any truncated data in any columns in target table.
c. Validation of boundary value analysis For Ex : If we load Data in Target table for Date>=2014-01-01 then No Data prior to this data should
Load in target table.
d. Validation of Source and Target data on basis of any unique key present in Source table.
e. Validation of Data at boundary by comparing first and last row of Source and Target Tables
4. Data Correctness Validation
a. Validation of any misspelled on inaccurate data in target table.
b. Validate null, non-unique or out of range data stored in target table when no constraints arespecified.
c. Validation of Column Data in Tables as they are containing values as per given data types and formats specified
5. Data Quality Validation
a. Numeric Fields Validation whether they are containing values as per given requirements.
b. Date Format validation of Fields that is containing Date Values.
c. Precision check validation of Decimal values.
d. Validation of data as per given requirements means few records does not meet certain criteria should be filtered out
e. Validation of Negative values in Numeric Fields .
6. Duplicate Check Validation
a. Validate Primary key, unique key column for duplicate values.
b. Validation of Duplicate values exists in any column which is extracting from multiple columns in source and combining into one column in source.
1. Structure Validation
a. Validate the source and target table structure as per given requirements.
b. Verify that data field types and formats are specified
c. Source data type length should not less than the target data type length.
d. Validate the name of columns in target table as per given requirements.
2. Constraint Validation
a. Primary Key Constraint should be enabled on Target Table.
b. Foreign Key Constraint validation if specified in the Target Table.
c. Not Null Constraint Validation on specified Fields as per given requirements.
d. Unique Constraint Validation on specified Fields as per given requirements.
3. Data Completeness Validation
a. Validation of rows count in Source and Target table on Each ETL Run.
b. Validation of any truncated data in any columns in target table.
c. Validation of boundary value analysis For Ex : If we load Data in Target table for Date>=2014-01-01 then No Data prior to this data should
Load in target table.
d. Validation of Source and Target data on basis of any unique key present in Source table.
e. Validation of Data at boundary by comparing first and last row of Source and Target Tables
4. Data Correctness Validation
a. Validation of any misspelled on inaccurate data in target table.
b. Validate null, non-unique or out of range data stored in target table when no constraints arespecified.
c. Validation of Column Data in Tables as they are containing values as per given data types and formats specified
5. Data Quality Validation
a. Numeric Fields Validation whether they are containing values as per given requirements.
b. Date Format validation of Fields that is containing Date Values.
c. Precision check validation of Decimal values.
d. Validation of data as per given requirements means few records does not meet certain criteria should be filtered out
e. Validation of Negative values in Numeric Fields .
6. Duplicate Check Validation
a. Validate Primary key, unique key column for duplicate values.
b. Validation of Duplicate values exists in any column which is extracting from multiple columns in source and combining into one column in source.
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