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values | userPrompt stringlengths 259 11.7k | response stringlengths 242 2.23k |
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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_name","sourceTableName":"sakila.actor","sourceColumnDatatype":"varchar"}],"targetColumnName":"last_name","targetColumnDatatype":"varchar"},{"businessRule":"No Transformation","targetTableName"... | [{"testCaseName":"Test Case - Direct Mapping of Columns","testCaseDescription":"Test the direct mapping of columns from the source to target without any transformation.","sourceQuery":"SELECT actor_id, first_name, last_name, last_update FROM sakila.actor","targetQuery":"SELECT actor_id, first_name, last_name, last_upda... |
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":"Apply Aggregation","targetTableName":"sales_summary","sourceTableColumnInformation":[{"sourceColumnName":"sale_date","sourceTableName":"sales","sourceColumnDatatype":"date"}],"targetColumnName":"sale_date","targetColumnDatatype":"date"},{"businessRule":"Sum and Group By","targetTableName":"sales_summa... | [{"testCaseName":"Test Case - Aggregation and Group By","testCaseDescription":"Test the aggregation and grouping of sales data based on sale_date with summation of amount.","sourceQuery":"SELECT sale_date, SUM(amount) AS total_amount FROM sales GROUP BY sale_date","targetQuery":"SELECT sale_date, total_amount FROM sale... |
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":"Apply Date Transformation","targetTableName":"employee_data","sourceTableColumnInformation":[{"sourceColumnName":"hire_date","sourceTableName":"employee","sourceColumnDatatype":"date"}],"targetColumnName":"hire_date_transformed","targetColumnDatatype":"date"}] | [{"testCaseName":"Test Case - Date Transformation","testCaseDescription":"Test the transformation of the hire_date to a new format for the target table.","sourceQuery":"SELECT hire_date FROM employee","targetQuery":"SELECT TO_CHAR(hire_date, 'YYYY-MM-DD') AS hire_date_transformed FROM employee"}] |
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":"Apply Aggregation","targetTableName":"sales_summary","sourceTableColumnInformation":[{"sourceColumnName":"sale_date","sourceTableName":"sales","sourceColumnDatatype":"date"},{"sourceColumnName":"amount","sourceTableName":"sales","sourceColumnDatatype":"decimal"}],"targetColumnName":"sale_date","target... | [{"testCaseName":"Test Case - Aggregation and Group By for Sales Data","testCaseDescription":"Test aggregation and summation of sales data grouped by sale_date.","sourceQuery":"SELECT sale_date, SUM(amount) AS total_sales_amount FROM sales GROUP BY sale_date","targetQuery":"SELECT sale_date, total_sales_amount FROM 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":"Direct Mapping with Transformation","targetTableName":"employee_data","sourceTableColumnInformation":[{"sourceColumnName":"first_name","sourceTableName":"employee","sourceColumnDatatype":"varchar"},{"sourceColumnName":"last_name","sourceTableName":"employee","sourceColumnDatatype":"varchar"}],"targetC... | [{"testCaseName":"Test Case - Full Name and Date Transformation","testCaseDescription":"Test the concatenation of first_name and last_name into full_name and apply date transformation on hire_date.","sourceQuery":"SELECT first_name || ' ' || last_name AS full_name, TO_CHAR(hire_date, 'YYYY-MM-DD') AS hire_date_transfor... |
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":"Apply Filtering and Aggregation","targetTableName":"order_summary","sourceTableColumnInformation":[{"sourceColumnName":"order_date","sourceTableName":"orders","sourceColumnDatatype":"date"},{"sourceColumnName":"amount","sourceTableName":"orders","sourceColumnDatatype":"decimal"}],"targetColumnName":"o... | [{"testCaseName":"Test Case - Filtered Aggregation for Orders","testCaseDescription":"Test filtering and aggregation of orders based on order_date and summing the amounts for each date.","sourceQuery":"SELECT order_date, SUM(amount) AS total_amount FROM orders WHERE order_date >= '2024-01-01' GROUP BY order_date","targ... |
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":"Direct Mapping and Conditional Filter","targetTableName":"customer_data","sourceTableColumnInformation":[{"sourceColumnName":"customer_id","sourceTableName":"customers","sourceColumnDatatype":"int"},{"sourceColumnName":"customer_name","sourceTableName":"customers","sourceColumnDatatype":"varchar"},{"s... | [{"testCaseName":"Test Case - Direct Mapping with Filtering for Customers","testCaseDescription":"Test direct mapping for customer_id and customer_name with filtering on registration_date to only include customers registered after '2023-01-01'.","sourceQuery":"SELECT customer_id, customer_name FROM customers WHERE regi... |
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":"Apply Conditional Transformation","targetTableName":"product_inventory","sourceTableColumnInformation":[{"sourceColumnName":"product_name","sourceTableName":"products","sourceColumnDatatype":"varchar"},{"sourceColumnName":"quantity","sourceTableName":"inventory","sourceColumnDatatype":"int"}],"targetC... | [{"testCaseName":"Test Case - Product Mapping and Stock Check","testCaseDescription":"Test the direct mapping of product_name and apply stock status transformation for quantity values greater than 100.","sourceQuery":"SELECT product_name, CASE WHEN quantity > 100 THEN 'In Stock' ELSE 'Out of Stock' END AS stock_status ... |
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":"Apply Transformation with Join","targetTableName":"order_details","sourceTableColumnInformation":[{"sourceColumnName":"order_id","sourceTableName":"orders","sourceColumnDatatype":"int"},{"sourceColumnName":"product_id","sourceTableName":"order_items","sourceColumnDatatype":"int"}],"targetColumnName":"... | [{"testCaseName":"Test Case - Join and Transform for Order Details","testCaseDescription":"Test the join of orders and order_items tables to transform order information into a single field.","sourceQuery":"SELECT o.order_id || '-' || oi.product_id AS order_info FROM orders o JOIN order_items oi ON o.order_id = oi.order... |
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_name","sourceTableName":"sakila.actor","sourceColumnDatatype":"varchar"}],"targetColumnName":"last_name","targetColumnDatatype":"varchar"},{"businessRule":"No Transformation","targetTableName"... | [{"testCaseName":"Direct Mapping Test Case","testCaseDescription":"Test case for direct mapping of columns with no transformation.","sourceQuery":"SELECT last_name, last_update, first_name, actor_id FROM sakila.actor","targetQuery":"SELECT last_name, last_update, first_name, actor_id FROM sakila.actor"}] |
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":"Aggregate Function","targetTableName":"sakila.film","sourceTableColumnInformation":[{"sourceColumnName":"rental_rate","sourceTableName":"sakila.film","sourceColumnDatatype":"decimal"}],"targetColumnName":"avg_rental_rate","targetColumnDatatype":"decimal"}] | [{"testCaseName":"Aggregate Function Test Case","testCaseDescription":"Test case for aggregate function on rental_rate column.","sourceQuery":"SELECT AVG(rental_rate) FROM sakila.film","targetQuery":"SELECT avg_rental_rate FROM sakila.film"}] |
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":"Transformation","targetTableName":"sakila.customer","sourceTableColumnInformation":[{"sourceColumnName":"first_name","sourceTableName":"sakila.customer","sourceColumnDatatype":"varchar"}],"targetColumnName":"first_name","targetColumnDatatype":"varchar","transformation":"UPPER(first_name)"},{"businessR... | [{"testCaseName":"Transformation Test Case","testCaseDescription":"Test case for transforming first_name and last_name to uppercase.","sourceQuery":"SELECT UPPER(first_name), UPPER(last_name) FROM sakila.customer","targetQuery":"SELECT first_name, last_name FROM sakila.customer"}] |
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":"Conditional Transformation","targetTableName":"sakila.payment","sourceTableColumnInformation":[{"sourceColumnName":"amount","sourceTableName":"sakila.payment","sourceColumnDatatype":"decimal"}],"targetColumnName":"amount","targetColumnDatatype":"decimal","transformation":"CASE WHEN amount > 10 THEN am... | [{"testCaseName":"Conditional Transformation Test Case","testCaseDescription":"Test case for conditional transformation on amount column.","sourceQuery":"SELECT CASE WHEN amount > 10 THEN amount * 0.9 ELSE amount END AS amount FROM sakila.payment","targetQuery":"SELECT amount FROM sakila.payment"}] |
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.film","sourceTableColumnInformation":[{"sourceColumnName":"title","sourceTableName":"sakila.film","sourceColumnDatatype":"varchar"}],"targetColumnName":"title","targetColumnDatatype":"varchar"},{"businessRule":"No Transformation","targetTableName":"sakila.f... | [{"testCaseName":"Direct Mapping Test Case","testCaseDescription":"Test case for direct mapping of columns with no transformation.","sourceQuery":"SELECT title, description, release_year FROM sakila.film","targetQuery":"SELECT title, description, release_year FROM sakila.film"}] |
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":"Aggregate Function","targetTableName":"sakila.rental","sourceTableColumnInformation":[{"sourceColumnName":"rental_duration","sourceTableName":"sakila.rental","sourceColumnDatatype":"smallint"}],"targetColumnName":"avg_rental_duration","targetColumnDatatype":"decimal"},{"businessRule":"Aggregate Functi... | [{"testCaseName":"Aggregate Function Test Case","testCaseDescription":"Test case for aggregate functions on rental_duration and rental_rate columns.","sourceQuery":"SELECT AVG(rental_duration), AVG(rental_rate) FROM sakila.rental","targetQuery":"SELECT avg_rental_duration, avg_rental_rate FROM sakila.rental"}] |
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":"Expression-based Transformation","targetTableName":"customer_discount","sourceTableColumnInformation":[{"sourceColumnName":"total_amount","sourceTableName":"orders","sourceColumnDatatype":"decimal"}],"targetColumnName":"discounted_amount","targetColumnDatatype":"decimal"},{"businessRule":"Apply Discou... | [{"testCaseName":"Test Case - Discount Calculation Based on Expression","testCaseDescription":"Test calculation of discounted_amount based on total_amount and apply discount_percentage based on a given business rule.","sourceQuery":"SELECT total_amount, CASE WHEN total_amount > 1000 THEN total_amount * 0.1 ELSE total_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":"Lookup Join","targetTableName":"employee_salary","sourceTableColumnInformation":[{"sourceColumnName":"employee_id","sourceTableName":"employee","sourceColumnDatatype":"int"}],"targetColumnName":"salary","targetColumnDatatype":"decimal"},{"businessRule":"Apply Lookup for Salary","targetTableName":"empl... | [{"testCaseName":"Test Case - Lookup Join for Employee Salary","testCaseDescription":"Test lookup join between employee and salary tables based on employee_id, and apply salary and bonus transformation.","sourceQuery":"SELECT e.employee_id, s.salary, s.salary * 0.1 AS bonus FROM employee e LEFT JOIN salary s ON e.emplo... |
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":"Regular Expression-based Transformation","targetTableName":"user_profile","sourceTableColumnInformation":[{"sourceColumnName":"email","sourceTableName":"users","sourceColumnDatatype":"varchar"}],"targetColumnName":"domain","targetColumnDatatype":"varchar"},{"businessRule":"Regex Extraction","targetTab... | [{"testCaseName":"Test Case - Regex-based Transformation for Email","testCaseDescription":"Test extraction of domain and username using regex from the email address.","sourceQuery":"SELECT email, REGEXP_SUBSTR(email, '@(\S+)$') AS domain, REGEXP_SUBSTR(email, '^(\S+)@') AS username FROM users","targetQuery":"SELECT dom... |
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":"Column Condition Transformation","targetTableName":"product_summary","sourceTableColumnInformation":[{"sourceColumnName":"quantity","sourceTableName":"inventory","sourceColumnDatatype":"int"}],"targetColumnName":"stock_status","targetColumnDatatype":"varchar"},{"businessRule":"Product Availability Che... | [{"testCaseName":"Test Case - Product Availability and Stock Status Check","testCaseDescription":"Test the application of stock status based on quantity and availability check for products with different quantity values.","sourceQuery":"SELECT quantity, CASE WHEN quantity > 100 THEN 'In Stock' ELSE 'Out of Stock' END 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":"Join with Additional Lookup","targetTableName":"order_report","sourceTableColumnInformation":[{"sourceColumnName":"order_id","sourceTableName":"orders","sourceColumnDatatype":"int"},{"sourceColumnName":"product_id","sourceTableName":"order_items","sourceColumnDatatype":"int"}],"targetColumnName":"orde... | [{"testCaseName":"Test Case - Join and Lookup for Order Report","testCaseDescription":"Test joining orders, order_items, and products to create a detailed order report with product names and order information.","sourceQuery":"SELECT o.order_id || '-' || oi.product_id AS order_details, p.product_name FROM orders o JOIN ... |
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":"Complex Join with Condition","targetTableName":"sales_data","sourceTableColumnInformation":[{"sourceColumnName":"sale_id","sourceTableName":"sales","sourceColumnDatatype":"int"},{"sourceColumnName":"customer_id","sourceTableName":"customers","sourceColumnDatatype":"int"}],"targetColumnName":"sale_deta... | [{"testCaseName":"Test Case - Join and Sale Calculation for Sales Data","testCaseDescription":"Test complex join between sales and customers, then apply a transformation to calculate the final sale amount.","sourceQuery":"SELECT s.sale_id || '-' || c.customer_id AS sale_details, s.amount * 1.2 AS final_amount FROM sale... |
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":"Uppercase Transformation","targetTableName":"customer_profile","sourceTableColumnInformation":[{"sourceColumnName":"first_name","sourceTableName":"customers","sourceColumnDatatype":"varchar"}],"targetColumnName":"first_name","targetColumnDatatype":"varchar"},{"businessRule":"Uppercase Transformation",... | [{"testCaseName":"Test Case - Uppercase Transformation for Customer Names","testCaseDescription":"Test the transformation of first_name and last_name to uppercase.","sourceQuery":"SELECT UPPER(first_name) AS first_name, UPPER(last_name) AS last_name FROM customers","targetQuery":"SELECT first_name, last_name FROM custo... |
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":"Add Constant to Column","targetTableName":"product_sales","sourceTableColumnInformation":[{"sourceColumnName":"quantity_sold","sourceTableName":"sales","sourceColumnDatatype":"int"}],"targetColumnName":"adjusted_quantity_sold","targetColumnDatatype":"int"}] | [{"testCaseName":"Test Case - Add Constant to Quantity Sold","testCaseDescription":"Test adding a constant value of 2 to the quantity_sold.","sourceQuery":"SELECT quantity_sold + 2 AS adjusted_quantity_sold FROM sales","targetQuery":"SELECT adjusted_quantity_sold FROM product_sales"}] |
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":"Regular Expression on Email","targetTableName":"user_profile","sourceTableColumnInformation":[{"sourceColumnName":"email","sourceTableName":"users","sourceColumnDatatype":"varchar"}],"targetColumnName":"domain","targetColumnDatatype":"varchar"},{"businessRule":"Regular Expression on Email","targetTabl... | [{"testCaseName":"Test Case - Extract Domain and Username from Email","testCaseDescription":"Test the extraction of domain and username from email using regular expressions.","sourceQuery":"SELECT REGEXP_SUBSTR(email, '@(\S+)$') AS domain, REGEXP_SUBSTR(email, '^(\S+)@') AS username FROM users","targetQuery":"SELECT do... |
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":"Phone Number Validation","targetTableName":"contact_info","sourceTableColumnInformation":[{"sourceColumnName":"phone_number","sourceTableName":"customers","sourceColumnDatatype":"varchar"}],"targetColumnName":"valid_phone_number","targetColumnDatatype":"varchar"}] | [{"testCaseName":"Test Case - Phone Number Validation","testCaseDescription":"Test the validation of phone numbers (only 10 digits allowed).","sourceQuery":"SELECT phone_number, CASE WHEN LENGTH(phone_number) = 10 THEN 'Valid' ELSE 'Invalid' END AS valid_phone_number FROM customers","targetQuery":"SELECT valid_phone_nu... |
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":"Lookup Join for Product Information","targetTableName":"product_sales_summary","sourceTableColumnInformation":[{"sourceColumnName":"product_id","sourceTableName":"sales","sourceColumnDatatype":"int"}],"targetColumnName":"product_name","targetColumnDatatype":"varchar"},{"businessRule":"Lookup Join for ... | [{"testCaseName":"Test Case - Lookup Join for Product Information","testCaseDescription":"Test the join between sales and products tables to get product_name and category_name.","sourceQuery":"SELECT s.product_id, p.product_name, p.category_name FROM sales s LEFT JOIN products p ON s.product_id = p.product_id","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":"Check for NULL Values","targetTableName":"user_info","sourceTableColumnInformation":[{"sourceColumnName":"email","sourceTableName":"users","sourceColumnDatatype":"varchar"}],"targetColumnName":"email_valid","targetColumnDatatype":"varchar"}] | [{"testCaseName":"Test Case - Check for NULL Values in Email","testCaseDescription":"Test for NULL values in email column, replace NULL with 'Invalid Email'.","sourceQuery":"SELECT email, COALESCE(email, 'Invalid Email') AS email_valid FROM users","targetQuery":"SELECT email_valid FROM user_info"}] |
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":"concatenate 'first_name' and 'last_name' with a space between them from table 'customer_details' and store as 'full_name' in 'customer_summary' table.","targetTableName":"customer.customer_summary","sourceTableColumnInformation":[{"sourceColumnName":"first_name","sourceTableName":"customer.customer_de... | [{"testCaseName":"String Concatenation - Full Name Creation","testCaseDescription":"Verify that the target 'full_name' in 'customer.customer_summary' table concatenates 'first_name' and 'last_name' columns from 'customer.customer_details' table with a space between them.","sourceQuery":"SELECT first_name, last_name FRO... |
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":"Join 'order_details' and 'product_info' on 'product_id' and calculate the total amount as 'quantity * unit_price' in 'sales_summary' table.","targetTableName":"sales.sales_summary","sourceTableColumnInformation":[{"sourceColumnName":"product_id","sourceTableName":"sales.order_details","sourceColumnDat... | [{"testCaseName":"Join and Calculation - Total Amount","testCaseDescription":"Verify that the 'total_amount' in 'sales.sales_summary' table calculates 'quantity * unit_price' after joining 'sales.order_details' and 'sales.product_info' tables on 'product_id'.","sourceQuery":"SELECT od.product_id, od.quantity, pi.unit_p... |
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":"Extract year from 'transaction_date' in 'transaction_log' table and store as 'transaction_year' in 'annual_summary' table.","targetTableName":"finance.annual_summary","sourceTableColumnInformation":[{"sourceColumnName":"transaction_date","sourceTableName":"finance.transaction_log","sourceColumnDatatyp... | [{"testCaseName":"Date Transformation - Extract Year","testCaseDescription":"Verify that the target 'transaction_year' in 'finance.annual_summary' table extracts the year from 'transaction_date' column in 'finance.transaction_log' table.","sourceQuery":"SELECT transaction_date FROM finance.transaction_log;","targetQuer... |
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":"Format 'birth_date' as 'YYYY-MM' in 'employee_details' table and store in 'birth_month' in 'employee_summary' table.","targetTableName":"hr.employee_summary","sourceTableColumnInformation":[{"sourceColumnName":"birth_date","sourceTableName":"hr.employee_details","sourceColumnDatatype":"date"}],"target... | [{"testCaseName":"Date Formatting - Birth Month Extraction","testCaseDescription":"Verify that the 'birth_month' in 'hr.employee_summary' table formats 'birth_date' column from 'hr.employee_details' table to 'YYYY-MM'.","sourceQuery":"SELECT birth_date FROM hr.employee_details;","targetQuery":"SELECT birth_month FROM h... |
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":"Calculate age based on 'birth_date' from 'person_info' table and store as 'age' in 'demographics' table.","targetTableName":"health.demographics","sourceTableColumnInformation":[{"sourceColumnName":"birth_date","sourceTableName":"health.person_info","sourceColumnDatatype":"date"}],"targetColumnName":"... | [{"testCaseName":"Age Calculation Based on Birth Date","testCaseDescription":"Verify that the 'age' column in 'health.demographics' table calculates age from the 'birth_date' column in 'health.person_info' table.","sourceQuery":"SELECT birth_date FROM health.person_info;","targetQuery":"SELECT age FROM health.demograph... |
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 ... | [{"businessRuleType":"Direct Mapping","businessRules":[{"businessRule":"Map 'customer_id' from 'customer_info' to 'customer_summary'.","sourceTableColumnInformation":[{"sourceColumnName":"customer_id","sourceTableName":"sales.customer_info","sourceColumnDatatype":"int"}],"targetTableName":"sales.customer_summary","targ... | [{"testCaseName":"Direct Mapping - Customer ID","testCaseDescription":"Verify that 'customer_id' is mapped directly from 'sales.customer_info' to 'sales.customer_summary'.","sourceQuery":"SELECT customer_id FROM sales.customer_info;","targetQuery":"SELECT customer_id FROM sales.customer_summary;"},{"testCaseName":"Dire... |
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 ... | [{"businessRuleType":"Expression","businessRules":[{"businessRule":"Calculate 'total_price' as 'quantity * unit_price' from 'order_items'.","sourceTableColumnInformation":[{"sourceColumnName":"quantity","sourceTableName":"sales.order_items","sourceColumnDatatype":"int"},{"sourceColumnName":"unit_price","sourceTableName... | [{"testCaseName":"Expression - Calculate Total Price","testCaseDescription":"Verify that 'total_price' in 'sales.order_summary' is calculated as 'quantity * unit_price' from 'sales.order_items'.","sourceQuery":"SELECT quantity, unit_price FROM sales.order_items;","targetQuery":"SELECT total_price FROM sales.order_summa... |
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 ... | [{"businessRuleType":"Lookup","businessRules":[{"businessRule":"Lookup 'country_name' from 'country_codes' table based on 'country_code' in 'customer_info'.","sourceTableColumnInformation":[{"sourceColumnName":"country_code","sourceTableName":"sales.customer_info","sourceColumnDatatype":"string"}],"lookupTableColumnInf... | [{"testCaseName":"Lookup - Country Name","testCaseDescription":"Verify that 'country_name' in 'sales.customer_summary' is populated based on a lookup from 'geography.country_codes' where 'country_code' matches with 'country_code' in 'sales.customer_info'.","sourceQuery":"SELECT country_code FROM sales.customer_info;","... |
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 ... | [{"businessRuleType":"No Transformation","businessRules":[{"businessRule":"Directly map 'account_number' from 'accounts' to 'account_summary'.","sourceTableColumnInformation":[{"sourceColumnName":"account_number","sourceTableName":"banking.accounts","sourceColumnDatatype":"string"}],"targetTableName":"banking.account_s... | [{"testCaseName":"No Transformation - Account Number","testCaseDescription":"Verify that 'account_number' is mapped directly from 'banking.accounts' to 'banking.account_summary'.","sourceQuery":"SELECT account_number FROM banking.accounts;","targetQuery":"SELECT account_number FROM banking.account_summary;"},{"testCase... |
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... |
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