Instruction stringclasses 5
values | Input stringlengths 274 6.42k | response stringlengths 366 2.2k |
|---|---|---|
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"SUM(ss.OrderQuantity) by join SRC_Customer sc and SRC_Sales ss on ss.CustomerKey and sc.CustomerKey","targetTableName":"public.tgt_customer","sourceTableColumnInformation":[{"sourceColumnName":"orderquantity","sourceTableName":"public.src_sales","sourceColumnDatatype":"smallint"}],"targetColumnName":"... | ```json
[
{
"testCaseName": "Total Orders Calculation",
"testCaseDescription": "Tests if the SUM of order quantities is calculated correctly by joining SRC_Customer and SRC_Sales on CustomerKey.",
"sourceQuery": "SELECT ss.CustomerKey, SUM(ss.OrderQuantity) AS totalorders FROM public.src_sal... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"SUM(ss.OrderQuantity) by join SRC_Customer sc and SRC_Sales ss on ss.CustomerKey and sc.CustomerKey","targetTableName":"public.tgt_customer","sourceTableColumnInformation":[{"sourceColumnName":"orderquantity","sourceTableName":"public.src_sales","sourceColumnDatatype":"smallint"}],"targetColumnName":"... | ```json
[
{
"testCaseName": "Total Orders Calculation Test",
"testCaseDescription": "Verifies that the total orders are correctly aggregated using SUM on order quantities by joining SRC_Customer with SRC_Sales on CustomerKey.",
"sourceQuery": "SELECT ss.CustomerKey, SUM(ss.OrderQuantity) AS ... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"SUM(ss.OrderQuantity) by join SRC_Customer sc and SRC_Sales ss on ss.CustomerKey and sc.CustomerKey","targetTableName":"public.tgt_customer","sourceTableColumnInformation":[{"sourceColumnName":"orderquantity","sourceTableName":"public.src_sales","sourceColumnDatatype":"smallint"}],"targetColumnName":"... | ```json
[
{
"testCaseName": "Total Orders Calculation Test",
"testCaseDescription": "Verifies that the total orders are aggregated correctly from the SRC_Sales data by joining with SRC_Customer on CustomerKey.",
"sourceQuery": "SELECT ss.CustomerKey, SUM(ss.OrderQuantity) AS totalorders FROM... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"SUM(ss.OrderQuantity) by join SRC_Customer sc and SRC_Sales ss on ss.CustomerKey and sc.CustomerKey","targetTableName":"public.tgt_customer","sourceTableColumnInformation":[{"sourceColumnName":"orderquantity","sourceTableName":"public.src_sales","sourceColumnDatatype":"smallint"}],"targetColumnName":"... | ```json
[
{
"testCaseName": "Total Order Quantity Calculation",
"testCaseDescription": "Verify that the total orders are calculated correctly using SUM aggregation by joining SRC_Customer and SRC_Sales on CustomerKey.",
"sourceQuery": "SELECT ss.CustomerKey, SUM(ss.OrderQuantity) AS totalord... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"sakila.actor","sourceTableColumnInformation":[{"sourceColumnName":"last_update","sourceTableName":"sakila.actor_automation","sourceColumnDatatype":"timestamp"}],"targetColumnName":"last_update","targetColumnDatatype":"date"},{"businessRule":"No Transformation","ta... | ```json
[
{
"testCaseName": "Direct Mapping Test",
"testCaseDescription": "Verify that the columns with no transformation are copied directly from source to target.",
"sourceQuery": "SELECT actor_id, last_name, last_update FROM sakila.actor_automation",
"targetQuery": "SELECT actor_i... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"sakila.actor","sourceTableColumnInformation":[{"sourceColumnName":"last_update","sourceTableName":"sakila.actor_automation","sourceColumnDatatype":"timestamp"}],"targetColumnName":"last_update","targetColumnDatatype":"date"},{"businessRule":"add+2","targetTableNam... | ```json
[
{
"testCaseName": "Direct Mapping Test",
"testCaseDescription": "Verify that the columns with no transformation are copied directly from source to target.",
"sourceQuery": "SELECT last_update, last_name FROM sakila.actor_automation",
"targetQuery": "SELECT last_update, last... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"SH.CHANNELS","sourceTableColumnInformation":[{"sourceColumnName":"PROD_ID","sourceTableName":"SH.SALES","sourceColumnDatatype":"NUMBER"}],"targetColumnName":"CHANNEL_CLASS_ID","targetColumnDatatype":"NUMBER"},{"businessRule":"No Transformation","targetTableName":"... | ```json
[
{
"testCaseName": "Direct Mapping Without Transformation",
"testCaseDescription": "Test direct mapping from SH.SALES to SH.CHANNELS without any transformation.",
"sourceQuery": "SELECT PROD_ID, QUANTITY_SOLD, CUST_ID, AMOUNT_SOLD, CHANNEL_ID, TIME_ID FROM SH.SALES",
"target... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"public.address_capitalize","sourceTableColumnInformation":[{"sourceColumnName":"COUNTRYNAME","sourceTableName":"public.address_capitalize","sourceColumnDatatype":"text"}],"targetColumnName":"COUNTRYNAME","targetColumnDatatype":"text"},{"businessRule":"No Transform... | ```json
[
{
"testCaseName": "Direct Mapping Validation",
"testCaseDescription": "Verify that all source columns are directly mapped to the target columns without any transformation.",
"sourceQuery": "SELECT COUNTRYNAME, CITY, STATECODE, ZIPCODE, TELEPHONE, STREETADDRESS, STREETNAME, STATENAM... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"SUM(ss.OrderQuantity) by join SRC_Customer sc and SRC_Sales ss on ss.CustomerKey and sc.CustomerKey","targetTableName":"public.tgt_customer","sourceTableColumnInformation":[{"sourceColumnName":"orderquantity","sourceTableName":"public.src_sales","sourceColumnDatatype":"smallint"}],"targetColumnName":"... | ```json
[
{
"testCaseName": "Total Orders Calculation",
"testCaseDescription": "Tests if the SUM of order quantities is calculated correctly by joining SRC_Customer and SRC_Sales on CustomerKey.",
"sourceQuery": "SELECT ss.CustomerKey, SUM(ss.OrderQuantity) AS totalorders FROM public.src_sal... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"SUM(ss.OrderQuantity) by join SRC_Customer sc and SRC_Sales ss on ss.CustomerKey and sc.CustomerKey","targetTableName":"public.tgt_customer","sourceTableColumnInformation":[{"sourceColumnName":"orderquantity","sourceTableName":"public.src_sales","sourceColumnDatatype":"smallint"}],"targetColumnName":"... | ```json
[
{
"testCaseName": "Total Orders Calculation Test",
"testCaseDescription": "Verifies that the total orders are correctly aggregated using SUM on order quantities by joining SRC_Customer with SRC_Sales on CustomerKey.",
"sourceQuery": "SELECT ss.CustomerKey, SUM(ss.OrderQuantity) AS ... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"SUM(ss.OrderQuantity) by join SRC_Customer sc and SRC_Sales ss on ss.CustomerKey and sc.CustomerKey","targetTableName":"public.tgt_customer","sourceTableColumnInformation":[{"sourceColumnName":"orderquantity","sourceTableName":"public.src_sales","sourceColumnDatatype":"smallint"}],"targetColumnName":"... | ```json
[
{
"testCaseName": "Total Orders Calculation Test",
"testCaseDescription": "Verifies that the total orders are aggregated correctly from the SRC_Sales data by joining with SRC_Customer on CustomerKey.",
"sourceQuery": "SELECT ss.CustomerKey, SUM(ss.OrderQuantity) AS totalorders FROM... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"SUM(ss.OrderQuantity) by join SRC_Customer sc and SRC_Sales ss on ss.CustomerKey and sc.CustomerKey","targetTableName":"public.tgt_customer","sourceTableColumnInformation":[{"sourceColumnName":"orderquantity","sourceTableName":"public.src_sales","sourceColumnDatatype":"smallint"}],"targetColumnName":"... | ```json
[
{
"testCaseName": "Total Order Quantity Calculation",
"testCaseDescription": "Verify that the total orders are calculated correctly using SUM aggregation by joining SRC_Customer and SRC_Sales on CustomerKey.",
"sourceQuery": "SELECT ss.CustomerKey, SUM(ss.OrderQuantity) AS totalord... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"sakila.actor","sourceTableColumnInformation":[{"sourceColumnName":"last_update","sourceTableName":"sakila.actor_automation","sourceColumnDatatype":"timestamp"}],"targetColumnName":"last_update","targetColumnDatatype":"date"},{"businessRule":"No Transformation","ta... | ```json
[
{
"testCaseName": "Direct Mapping Test",
"testCaseDescription": "Verify that the columns with no transformation are copied directly from source to target.",
"sourceQuery": "SELECT actor_id, last_name, last_update FROM sakila.actor_automation",
"targetQuery": "SELECT actor_i... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"sakila.actor","sourceTableColumnInformation":[{"sourceColumnName":"last_update","sourceTableName":"sakila.actor_automation","sourceColumnDatatype":"timestamp"}],"targetColumnName":"last_update","targetColumnDatatype":"date"},{"businessRule":"add+2","targetTableNam... | ```json
[
{
"testCaseName": "Direct Mapping Test",
"testCaseDescription": "Verify that the columns with no transformation are copied directly from source to target.",
"sourceQuery": "SELECT last_update, last_name FROM sakila.actor_automation",
"targetQuery": "SELECT last_update, last... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"SH.CHANNELS","sourceTableColumnInformation":[{"sourceColumnName":"PROD_ID","sourceTableName":"SH.SALES","sourceColumnDatatype":"NUMBER"}],"targetColumnName":"CHANNEL_CLASS_ID","targetColumnDatatype":"NUMBER"},{"businessRule":"No Transformation","targetTableName":"... | ```json
[
{
"testCaseName": "Direct Mapping Without Transformation",
"testCaseDescription": "Test direct mapping from SH.SALES to SH.CHANNELS without any transformation.",
"sourceQuery": "SELECT PROD_ID, QUANTITY_SOLD, CUST_ID, AMOUNT_SOLD, CHANNEL_ID, TIME_ID FROM SH.SALES",
"target... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"public.address_capitalize","sourceTableColumnInformation":[{"sourceColumnName":"COUNTRYNAME","sourceTableName":"public.address_capitalize","sourceColumnDatatype":"text"}],"targetColumnName":"COUNTRYNAME","targetColumnDatatype":"text"},{"businessRule":"No Transform... | ```json
[
{
"testCaseName": "Direct Mapping Validation",
"testCaseDescription": "Verify that all source columns are directly mapped to the target columns without any transformation.",
"sourceQuery": "SELECT COUNTRYNAME, CITY, STATECODE, ZIPCODE, TELEPHONE, STREETADDRESS, STREETNAME, STATENAM... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"public.address_capitalize","sourceTableColumnInformation":[{"sourceColumnName":"COUNTRYNAME","sourceTableName":"public.address_capitalize","sourceColumnDatatype":"text"}],"targetColumnName":"COUNTRYNAME","targetColumnDatatype":"text"},{"businessRule":"No Transform... | ```json
[
{
"testCaseName": "Direct_Mapping_Validation_596504_Corrected",
"testCaseDescription": "Ensure that select queries for both source and target tables are correctly written to validate direct mapping without transformations.",
"sourceQuery": "SELECT COUNTRYNAME AS SOURCE_COUNTRYNAME,... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"SH.CUSTOMERS","sourceTableColumnInformation":[{"sourceColumnName":"CUST_EFF_FROM","sourceTableName":"SH.CUSTOMERS","sourceColumnDatatype":"DATE"}],"targetColumnName":"CUST_EFF_FROM","targetColumnDatatype":"DATE"},{"businessRule":"No Transformation","targetTableNam... | ```json
[
{
"testCaseName": "Direct Mapping",
"testCaseDescription": "Verify direct mapping of columns without any transformation.",
"sourceQuery": "SELECT CUST_ID, CUST_FIRST_NAME, CUST_LAST_NAME, CUST_EMAIL, CUST_MAIN_PHONE_NUMBER, CUST_STREET_ADDRESS, CUST_CITY, CUST_STATE_PROVINCE, CUST_... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"SH.CHANNELS","sourceTableColumnInformation":[{"sourceColumnName":"CHANNEL_DESC","sourceTableName":"SH.CHANNELS","sourceColumnDatatype":"VARCHAR2"}],"targetColumnName":"CHANNEL_DESC","targetColumnDatatype":"VARCHAR2"},{"businessRule":"No Transformation","targetTabl... | ```json
[
{
"testCaseName": "Direct Mapping With No Transformation",
"testCaseDescription": "Verify that columns are correctly mapped from source to target without any transformations.",
"sourceQuery": "SELECT CHANNEL_DESC, CHANNEL_ID, CHANNEL_TOTAL_ID, CHANNEL_CLASS, CHANNEL_TOTAL, CHANNEL_... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"upper(CHANNEL_DESC) as CHANNEL_DESC\n","targetTableName":"SH.CHANNELS","sourceTableColumnInformation":[{"sourceColumnName":"CHANNEL_DESC","sourceTableName":"SH.CHANNELS","sourceColumnDatatype":"VARCHAR2"}],"targetColumnName":"CHANNEL_DESC","targetColumnDatatype":"VARCHAR2"},{"businessRule":"No Transfo... | ```json
[
{
"testCaseName": "Transformation for CHANNEL_DESC to Upper Case",
"testCaseDescription": "Ensure CHANNEL_DESC in source is converted to upper case before mapping to target.",
"sourceQuery": "SELECT upper(CHANNEL_DESC) AS CHANNEL_DESC, CHANNEL_ID, CHANNEL_TOTAL_ID, CHANNEL_CLASS, C... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"upper(CHANNEL_DESC) as CHANNEL_DESC\n","targetTableName":"SH.CHANNELS","sourceTableColumnInformation":[{"sourceColumnName":"CHANNEL_DESC","sourceTableName":"SH.CHANNELS","sourceColumnDatatype":"VARCHAR2"}],"targetColumnName":"CHANNEL_DESC","targetColumnDatatype":"VARCHAR2"},{"businessRule":"No Transfo... | ```json
[
{
"testCaseName": "Transformation for CHANNEL_DESC to Upper Case with Filter",
"testCaseDescription": "Ensure CHANNEL_DESC in source is converted to upper case and mapped correctly to target, apply where condition to filter specific channels.",
"sourceQuery": "SELECT upper(CHANNEL_... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"upper(USER_NAME)","targetTableName":"SH.ACCOUNTS","sourceTableColumnInformation":[{"sourceColumnName":"CUSTOMER_NAME","sourceTableName":"SH.CUSTOMER","sourceColumnDatatype":"VARCHAR2"}],"targetColumnName":"USER_NAME","targetColumnDatatype":"NUMBER"},{"businessRule":"No Transformation","targetTableName... | ```json
[
{
"testCaseName": "Direct Mapping No Transformation",
"testCaseDescription": "Validate direct mapping of CUSTOMER_ID to USER_ID without any transformation.",
"sourceQuery": "SELECT CUSTOMER_ID FROM SH.CUSTOMER",
"targetQuery": "SELECT USER_ID FROM SH.ACCOUNTS"
},
{
... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"upper(USER_NAME)","targetTableName":"SH.ACCOUNTS","sourceTableColumnInformation":[{"sourceColumnName":"CUSTOMER_NAME","sourceTableName":"SH.CUSTOMER","sourceColumnDatatype":"VARCHAR2"}],"targetColumnName":"USER_NAME","targetColumnDatatype":"NUMBER"},{"businessRule":"No Transformation","targetTableName... | ```json
[
{
"testCaseName": "Direct Mapping No Transformation",
"testCaseDescription": "Validate direct mapping of CUSTOMER_ID to USER_ID without any transformation.",
"sourceQuery": "SELECT CUSTOMER_ID FROM SH.CUSTOMER",
"targetQuery": "SELECT USER_ID FROM SH.ACCOUNTS"
},
{
... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"SH.ALL_DATATYPES_ORACLE","sourceTableColumnInformation":[{"sourceColumnName":"FIRST_NAME","sourceTableName":"SH.ALL_DATATYPES_SQLSERVER","sourceColumnDatatype":"NVARCHAR2"}],"targetColumnName":"FIRST_NAME","targetColumnDatatype":"VARCHAR2"},{"businessRule":"No Tra... | ```json
[
{
"testCaseName": "Direct Mapping Test",
"testCaseDescription": "Test cases for columns with direct mapping and no transformation.",
"sourceQuery": "SELECT FIRST_NAME, CHAR_COL, DATE_COL, NCHAR_COL, LAST_NAME FROM SH.ALL_DATATYPES_SQLSERVER",
"targetQuery": "SELECT FIRST_NA... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"SH.ALL_DATATYPES_ORACLE","sourceTableColumnInformation":[{"sourceColumnName":"FIRST_NAME","sourceTableName":"SH.ALL_DATATYPES_SQLSERVER","sourceColumnDatatype":"NVARCHAR2"}],"targetColumnName":"FIRST_NAME","targetColumnDatatype":"VARCHAR2"},{"businessRule":"No Tra... | ```json
[
{
"testCaseName": "Direct Mapping Test",
"testCaseDescription": "Test cases for columns with direct mapping and no transformation.",
"sourceQuery": "SELECT FIRST_NAME, CHAR_COL, NCHAR_COL, LAST_NAME FROM SH.ALL_DATATYPES_SQLSERVER",
"targetQuery": "SELECT FIRST_NAME, CHAR_C... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"SH.ALL_DATATYPES_ORACLE","sourceTableColumnInformation":[{"sourceColumnName":"FIRST_NAME","sourceTableName":"SH.ALL_DATATYPES_SQLSERVER","sourceColumnDatatype":"NVARCHAR2"}],"targetColumnName":"FIRST_NAME","targetColumnDatatype":"VARCHAR2"},{"businessRule":"No Tra... | ```json
[
{
"testCaseName": "Direct Mapping Test",
"testCaseDescription": "Test cases for columns with direct mapping and no transformation.",
"sourceQuery": "SELECT FIRST_NAME, CHAR_COL, NCHAR_COL, LAST_NAME FROM SH.ALL_DATATYPES_SQLSERVER",
"targetQuery": "SELECT FIRST_NAME, CHAR_C... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"public.actordelta","sourceTableColumnInformation":[{"sourceColumnName":"last_update","sourceTableName":"sakila.actor","sourceColumnDatatype":"date"}],"targetColumnName":"last_update","targetColumnDatatype":"date"},{"businessRule":"No Transformation","targetTableNa... | ```json
[
{
"testCaseName": "Direct Mapping No Transformation",
"testCaseDescription": "This test case verifies that all columns from the source table are directly mapped to the target table without any transformation.",
"sourceQuery": "SELECT last_update, first_name, last_name FROM sakila.a... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"public.actordelta","sourceTableColumnInformation":[{"sourceColumnName":"actor_id","sourceTableName":"public.src_actor","sourceColumnDatatype":"numeric"}],"targetColumnName":"actor_id","targetColumnDatatype":"numeric"}] | ```json
[
{
"testCaseName": "Direct Mapping of Actor ID",
"testCaseDescription": "This test case checks that the actor_id is directly mapped from the source to the target table without any transformation.",
"sourceQuery": "SELECT actor_id FROM public.src_actor",
"targetQuery": "SELEC... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"date lesser than 2023","targetTableName":"public.actordelta","sourceTableColumnInformation":[{"sourceColumnName":"last_update","sourceTableName":"sakila.actor","sourceColumnDatatype":"date"}],"targetColumnName":"last_update","targetColumnDatatype":"date"},{"businessRule":"first name contains R","targe... | ```json
[
{
"testCaseName": "Date Filter and Name Condition",
"testCaseDescription": "This test case applies a date filter ensuring the last_update is before 2023 and checks if first_name contains 'R', with no transformation for last_name.",
"sourceQuery": "SELECT last_update, first_name, la... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"public.actordelta","sourceTableColumnInformation":[{"sourceColumnName":"actor_id","sourceTableName":"public.src_actor","sourceColumnDatatype":"numeric"}],"targetColumnName":"actor_id","targetColumnDatatype":"numeric"}] | ```json
[
{
"testCaseName": "Direct Mapping of Actor ID",
"testCaseDescription": "This test case verifies that the actor_id is transferred directly from the source table to the target table without any transformation.",
"sourceQuery": "SELECT actor_id FROM public.src_actor",
"targetQ... |
Generate test cases for the given ETL Mapping JSON based on business rules and provide me output as json string without any explanation sample output json format : [{"testCaseName":"","testCaseDescription":"","sourceQuery":"","targetQuery":""}] Note: Please generate only 'select' queries for both target and source but ... | [{"businessRule":"No Transformation","targetTableName":"SH.SRCCUSTOMERS","sourceTableColumnInformation":[{"sourceColumnName":"YEARLYINCOME","sourceTableName":"PUBLIC.DIMCUSTOMER","sourceColumnDatatype":"FLOAT"}],"targetColumnName":"CUST_SRC_ID","targetColumnDatatype":"NUMBER"},{"businessRule":"No Transformation","targe... | ```json
[
{
"testCaseName": "No Transformation Mapping",
"testCaseDescription": "Validate that the columns from PUBLIC.DIMCUSTOMER are directly mapped to SH.SRCCUSTOMERS without any transformation.",
"sourceQuery": "SELECT YEARLYINCOME, ADDRESSLINE1, FIRSTNAME, ADDRESSLINE2, BIRTHDATE, EMAIL... |
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