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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for null values in NOT NULL columns.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123", "", "Sales"], ["456", "John", "Marketing"]], "excel_metadata": [{"column_name": "Emp_ID", "data_type": "NUMBER(5)", "allow_null": "No"}, {"column_name": "Emp_Name", "data_type": "VARCHAR2(10)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(20)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 has a NULL value in column 'Emp_Name', which is marked NOT NULL. Please correct the data.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate data length against column definitions.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["AliceSmith", "HR"]], "excel_metadata": [{"column_name": "Emp_Name", "data_type": "VARCHAR2(5)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1: 'Emp_Name' exceeds max length of 5 (value: 'AliceSmith'), 'Department' exceeds max length of 2 (value: 'HR').<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for values violating NUMBER precision and scale.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["1234567890.12"], ["123456.7"]], "excel_metadata": [{"column_name": "Salary", "data_type": "NUMBER(10,2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 value '1234567890.12' exceeds precision 10. Row 2 is valid and will be padded to 123456.70.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate invalid characters in column names.<|eot_id|><|start_header_id|>user<|end_header_id|>{"excel_metadata": [{"column_name": "1stName", "data_type": "VARCHAR2(20)", "allow_null": "No"}, {"column_name": "Dept$", "data_type": "VARCHAR2(30)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Invalid column names detected: '1stName' starts with a number, 'Dept$' contains illegal character '$'.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Ensure date format consistency.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["01-02-24"], ["03/02/24"], ["04-02-2024"]], "excel_metadata": [{"column_name": "Join_Date", "data_type": "DATE", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Date format inconsistency detected: '-' and '/' used; year format varies between YY and YYYY. Standardize format before load.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for invalid numeric entries.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123"], ["(567)"], ["abc"], ["-89.6"]], "excel_metadata": [{"column_name": "Bonus", "data_type": "NUMBER(5,1)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Rows 2 and 3 contain non-numeric values ('(567)', 'abc') which violate NUMBER datatype. Others are valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Aggregate revenue by region.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["North", "1200"], ["South", "800"], ["North", "720"]], "column_mapping": ["Region", "Total_Revenue"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The region with the highest total revenue is 'North' with a total of 1920.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check if values fit VARCHAR2(5) column.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123.4"], ["123.45"], ["1234.5"]], "excel_metadata": [{"column_name": "Amount", "data_type": "VARCHAR2(5)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 2 ('123.45') and Row 3 ('1234.5') exceed the VARCHAR2(5) limit. Only '123.4' is valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Identify padded values violating NUMBER(10,8) precision.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["12.34567891"], ["1234.67"], ["12345"]], "excel_metadata": [{"column_name": "Conversion_Rate", "data_type": "NUMBER(10,8)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Only '12.34567891' is valid. '1234.67' and '12345' will exceed precision 10 after padding.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check total units sold.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["120"], ["85"], ["90"], ["75"], ["60"]], "column_mapping": ["Total_Units"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The total units sold is 430.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for null values in NOT NULL columns.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123", "", "Sales"], ["456", "John", "Marketing"]], "excel_metadata": [{"column_name": "Emp_ID", "data_type": "NUMBER(5)", "allow_null": "No"}, {"column_name": "Emp_Name", "data_type": "VARCHAR2(10)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(20)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 has a NULL value in column 'Emp_Name', which is marked NOT NULL. Please correct the data.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate data length against column definitions.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["AliceSmith", "HR"]], "excel_metadata": [{"column_name": "Emp_Name", "data_type": "VARCHAR2(5)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1: 'Emp_Name' exceeds max length of 5 (value: 'AliceSmith'), 'Department' exceeds max length of 2 (value: 'HR').<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for values violating NUMBER precision and scale.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["1234567890.12"], ["123456.7"]], "excel_metadata": [{"column_name": "Salary", "data_type": "NUMBER(10,2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 value '1234567890.12' exceeds precision 10. Row 2 is valid and will be padded to 123456.70.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate invalid characters in column names.<|eot_id|><|start_header_id|>user<|end_header_id|>{"excel_metadata": [{"column_name": "1stName", "data_type": "VARCHAR2(20)", "allow_null": "No"}, {"column_name": "Dept$", "data_type": "VARCHAR2(30)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Invalid column names detected: '1stName' starts with a number, 'Dept$' contains illegal character '$'.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Ensure date format consistency.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["01-02-24"], ["03/02/24"], ["04-02-2024"]], "excel_metadata": [{"column_name": "Join_Date", "data_type": "DATE", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Date format inconsistency detected: '-' and '/' used; year format varies between YY and YYYY. Standardize format before load.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for invalid numeric entries.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123"], ["(567)"], ["abc"], ["-89.6"]], "excel_metadata": [{"column_name": "Bonus", "data_type": "NUMBER(5,1)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Rows 2 and 3 contain non-numeric values ('(567)', 'abc') which violate NUMBER datatype. Others are valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Aggregate revenue by region.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["North", "1200"], ["South", "800"], ["North", "720"]], "column_mapping": ["Region", "Total_Revenue"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The region with the highest total revenue is 'North' with a total of 1920.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check if values fit VARCHAR2(5) column.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123.4"], ["123.45"], ["1234.5"]], "excel_metadata": [{"column_name": "Amount", "data_type": "VARCHAR2(5)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 2 ('123.45') and Row 3 ('1234.5') exceed the VARCHAR2(5) limit. Only '123.4' is valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Identify padded values violating NUMBER(10,8) precision.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["12.34567891"], ["1234.67"], ["12345"]], "excel_metadata": [{"column_name": "Conversion_Rate", "data_type": "NUMBER(10,8)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Only '12.34567891' is valid. '1234.67' and '12345' will exceed precision 10 after padding.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check total units sold.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["120"], ["85"], ["90"], ["75"], ["60"]], "column_mapping": ["Total_Units"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The total units sold is 430.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for null values in NOT NULL columns.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123", "", "Sales"], ["456", "John", "Marketing"]], "excel_metadata": [{"column_name": "Emp_ID", "data_type": "NUMBER(5)", "allow_null": "No"}, {"column_name": "Emp_Name", "data_type": "VARCHAR2(10)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(20)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 has a NULL value in column 'Emp_Name', which is marked NOT NULL. Please correct the data.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate data length against column definitions.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["AliceSmith", "HR"]], "excel_metadata": [{"column_name": "Emp_Name", "data_type": "VARCHAR2(5)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1: 'Emp_Name' exceeds max length of 5 (value: 'AliceSmith'), 'Department' exceeds max length of 2 (value: 'HR').<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for values violating NUMBER precision and scale.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["1234567890.12"], ["123456.7"]], "excel_metadata": [{"column_name": "Salary", "data_type": "NUMBER(10,2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 value '1234567890.12' exceeds precision 10. Row 2 is valid and will be padded to 123456.70.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate invalid characters in column names.<|eot_id|><|start_header_id|>user<|end_header_id|>{"excel_metadata": [{"column_name": "1stName", "data_type": "VARCHAR2(20)", "allow_null": "No"}, {"column_name": "Dept$", "data_type": "VARCHAR2(30)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Invalid column names detected: '1stName' starts with a number, 'Dept$' contains illegal character '$'.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Ensure date format consistency.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["01-02-24"], ["03/02/24"], ["04-02-2024"]], "excel_metadata": [{"column_name": "Join_Date", "data_type": "DATE", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Date format inconsistency detected: '-' and '/' used; year format varies between YY and YYYY. Standardize format before load.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for invalid numeric entries.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123"], ["(567)"], ["abc"], ["-89.6"]], "excel_metadata": [{"column_name": "Bonus", "data_type": "NUMBER(5,1)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Rows 2 and 3 contain non-numeric values ('(567)', 'abc') which violate NUMBER datatype. Others are valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Aggregate revenue by region.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["North", "1200"], ["South", "800"], ["North", "720"]], "column_mapping": ["Region", "Total_Revenue"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The region with the highest total revenue is 'North' with a total of 1920.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check if values fit VARCHAR2(5) column.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123.4"], ["123.45"], ["1234.5"]], "excel_metadata": [{"column_name": "Amount", "data_type": "VARCHAR2(5)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 2 ('123.45') and Row 3 ('1234.5') exceed the VARCHAR2(5) limit. Only '123.4' is valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Identify padded values violating NUMBER(10,8) precision.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["12.34567891"], ["1234.67"], ["12345"]], "excel_metadata": [{"column_name": "Conversion_Rate", "data_type": "NUMBER(10,8)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Only '12.34567891' is valid. '1234.67' and '12345' will exceed precision 10 after padding.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check total units sold.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["120"], ["85"], ["90"], ["75"], ["60"]], "column_mapping": ["Total_Units"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The total units sold is 430.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for null values in NOT NULL columns.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123", "", "Sales"], ["456", "John", "Marketing"]], "excel_metadata": [{"column_name": "Emp_ID", "data_type": "NUMBER(5)", "allow_null": "No"}, {"column_name": "Emp_Name", "data_type": "VARCHAR2(10)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(20)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 has a NULL value in column 'Emp_Name', which is marked NOT NULL. Please correct the data.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate data length against column definitions.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["AliceSmith", "HR"]], "excel_metadata": [{"column_name": "Emp_Name", "data_type": "VARCHAR2(5)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1: 'Emp_Name' exceeds max length of 5 (value: 'AliceSmith'), 'Department' exceeds max length of 2 (value: 'HR').<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for values violating NUMBER precision and scale.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["1234567890.12"], ["123456.7"]], "excel_metadata": [{"column_name": "Salary", "data_type": "NUMBER(10,2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 value '1234567890.12' exceeds precision 10. Row 2 is valid and will be padded to 123456.70.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate invalid characters in column names.<|eot_id|><|start_header_id|>user<|end_header_id|>{"excel_metadata": [{"column_name": "1stName", "data_type": "VARCHAR2(20)", "allow_null": "No"}, {"column_name": "Dept$", "data_type": "VARCHAR2(30)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Invalid column names detected: '1stName' starts with a number, 'Dept$' contains illegal character '$'.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Ensure date format consistency.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["01-02-24"], ["03/02/24"], ["04-02-2024"]], "excel_metadata": [{"column_name": "Join_Date", "data_type": "DATE", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Date format inconsistency detected: '-' and '/' used; year format varies between YY and YYYY. Standardize format before load.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for invalid numeric entries.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123"], ["(567)"], ["abc"], ["-89.6"]], "excel_metadata": [{"column_name": "Bonus", "data_type": "NUMBER(5,1)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Rows 2 and 3 contain non-numeric values ('(567)', 'abc') which violate NUMBER datatype. Others are valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Aggregate revenue by region.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["North", "1200"], ["South", "800"], ["North", "720"]], "column_mapping": ["Region", "Total_Revenue"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The region with the highest total revenue is 'North' with a total of 1920.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check if values fit VARCHAR2(5) column.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123.4"], ["123.45"], ["1234.5"]], "excel_metadata": [{"column_name": "Amount", "data_type": "VARCHAR2(5)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 2 ('123.45') and Row 3 ('1234.5') exceed the VARCHAR2(5) limit. Only '123.4' is valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Identify padded values violating NUMBER(10,8) precision.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["12.34567891"], ["1234.67"], ["12345"]], "excel_metadata": [{"column_name": "Conversion_Rate", "data_type": "NUMBER(10,8)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Only '12.34567891' is valid. '1234.67' and '12345' will exceed precision 10 after padding.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check total units sold.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["120"], ["85"], ["90"], ["75"], ["60"]], "column_mapping": ["Total_Units"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The total units sold is 430.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for null values in NOT NULL columns.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123", "", "Sales"], ["456", "John", "Marketing"]], "excel_metadata": [{"column_name": "Emp_ID", "data_type": "NUMBER(5)", "allow_null": "No"}, {"column_name": "Emp_Name", "data_type": "VARCHAR2(10)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(20)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 has a NULL value in column 'Emp_Name', which is marked NOT NULL. Please correct the data.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate data length against column definitions.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["AliceSmith", "HR"]], "excel_metadata": [{"column_name": "Emp_Name", "data_type": "VARCHAR2(5)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1: 'Emp_Name' exceeds max length of 5 (value: 'AliceSmith'), 'Department' exceeds max length of 2 (value: 'HR').<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for values violating NUMBER precision and scale.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["1234567890.12"], ["123456.7"]], "excel_metadata": [{"column_name": "Salary", "data_type": "NUMBER(10,2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 value '1234567890.12' exceeds precision 10. Row 2 is valid and will be padded to 123456.70.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate invalid characters in column names.<|eot_id|><|start_header_id|>user<|end_header_id|>{"excel_metadata": [{"column_name": "1stName", "data_type": "VARCHAR2(20)", "allow_null": "No"}, {"column_name": "Dept$", "data_type": "VARCHAR2(30)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Invalid column names detected: '1stName' starts with a number, 'Dept$' contains illegal character '$'.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Ensure date format consistency.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["01-02-24"], ["03/02/24"], ["04-02-2024"]], "excel_metadata": [{"column_name": "Join_Date", "data_type": "DATE", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Date format inconsistency detected: '-' and '/' used; year format varies between YY and YYYY. Standardize format before load.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for invalid numeric entries.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123"], ["(567)"], ["abc"], ["-89.6"]], "excel_metadata": [{"column_name": "Bonus", "data_type": "NUMBER(5,1)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Rows 2 and 3 contain non-numeric values ('(567)', 'abc') which violate NUMBER datatype. Others are valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Aggregate revenue by region.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["North", "1200"], ["South", "800"], ["North", "720"]], "column_mapping": ["Region", "Total_Revenue"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The region with the highest total revenue is 'North' with a total of 1920.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check if values fit VARCHAR2(5) column.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123.4"], ["123.45"], ["1234.5"]], "excel_metadata": [{"column_name": "Amount", "data_type": "VARCHAR2(5)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 2 ('123.45') and Row 3 ('1234.5') exceed the VARCHAR2(5) limit. Only '123.4' is valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Identify padded values violating NUMBER(10,8) precision.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["12.34567891"], ["1234.67"], ["12345"]], "excel_metadata": [{"column_name": "Conversion_Rate", "data_type": "NUMBER(10,8)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Only '12.34567891' is valid. '1234.67' and '12345' will exceed precision 10 after padding.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check total units sold.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["120"], ["85"], ["90"], ["75"], ["60"]], "column_mapping": ["Total_Units"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The total units sold is 430.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for null values in NOT NULL columns.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123", "", "Sales"], ["456", "John", "Marketing"]], "excel_metadata": [{"column_name": "Emp_ID", "data_type": "NUMBER(5)", "allow_null": "No"}, {"column_name": "Emp_Name", "data_type": "VARCHAR2(10)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(20)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 has a NULL value in column 'Emp_Name', which is marked NOT NULL. Please correct the data.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate data length against column definitions.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["AliceSmith", "HR"]], "excel_metadata": [{"column_name": "Emp_Name", "data_type": "VARCHAR2(5)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1: 'Emp_Name' exceeds max length of 5 (value: 'AliceSmith'), 'Department' exceeds max length of 2 (value: 'HR').<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for values violating NUMBER precision and scale.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["1234567890.12"], ["123456.7"]], "excel_metadata": [{"column_name": "Salary", "data_type": "NUMBER(10,2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 value '1234567890.12' exceeds precision 10. Row 2 is valid and will be padded to 123456.70.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate invalid characters in column names.<|eot_id|><|start_header_id|>user<|end_header_id|>{"excel_metadata": [{"column_name": "1stName", "data_type": "VARCHAR2(20)", "allow_null": "No"}, {"column_name": "Dept$", "data_type": "VARCHAR2(30)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Invalid column names detected: '1stName' starts with a number, 'Dept$' contains illegal character '$'.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Ensure date format consistency.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["01-02-24"], ["03/02/24"], ["04-02-2024"]], "excel_metadata": [{"column_name": "Join_Date", "data_type": "DATE", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Date format inconsistency detected: '-' and '/' used; year format varies between YY and YYYY. Standardize format before load.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for invalid numeric entries.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123"], ["(567)"], ["abc"], ["-89.6"]], "excel_metadata": [{"column_name": "Bonus", "data_type": "NUMBER(5,1)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Rows 2 and 3 contain non-numeric values ('(567)', 'abc') which violate NUMBER datatype. Others are valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Aggregate revenue by region.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["North", "1200"], ["South", "800"], ["North", "720"]], "column_mapping": ["Region", "Total_Revenue"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The region with the highest total revenue is 'North' with a total of 1920.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check if values fit VARCHAR2(5) column.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123.4"], ["123.45"], ["1234.5"]], "excel_metadata": [{"column_name": "Amount", "data_type": "VARCHAR2(5)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 2 ('123.45') and Row 3 ('1234.5') exceed the VARCHAR2(5) limit. Only '123.4' is valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Identify padded values violating NUMBER(10,8) precision.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["12.34567891"], ["1234.67"], ["12345"]], "excel_metadata": [{"column_name": "Conversion_Rate", "data_type": "NUMBER(10,8)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Only '12.34567891' is valid. '1234.67' and '12345' will exceed precision 10 after padding.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check total units sold.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["120"], ["85"], ["90"], ["75"], ["60"]], "column_mapping": ["Total_Units"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The total units sold is 430.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for null values in NOT NULL columns.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123", "", "Sales"], ["456", "John", "Marketing"]], "excel_metadata": [{"column_name": "Emp_ID", "data_type": "NUMBER(5)", "allow_null": "No"}, {"column_name": "Emp_Name", "data_type": "VARCHAR2(10)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(20)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 has a NULL value in column 'Emp_Name', which is marked NOT NULL. Please correct the data.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate data length against column definitions.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["AliceSmith", "HR"]], "excel_metadata": [{"column_name": "Emp_Name", "data_type": "VARCHAR2(5)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1: 'Emp_Name' exceeds max length of 5 (value: 'AliceSmith'), 'Department' exceeds max length of 2 (value: 'HR').<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for values violating NUMBER precision and scale.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["1234567890.12"], ["123456.7"]], "excel_metadata": [{"column_name": "Salary", "data_type": "NUMBER(10,2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 value '1234567890.12' exceeds precision 10. Row 2 is valid and will be padded to 123456.70.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate invalid characters in column names.<|eot_id|><|start_header_id|>user<|end_header_id|>{"excel_metadata": [{"column_name": "1stName", "data_type": "VARCHAR2(20)", "allow_null": "No"}, {"column_name": "Dept$", "data_type": "VARCHAR2(30)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Invalid column names detected: '1stName' starts with a number, 'Dept$' contains illegal character '$'.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Ensure date format consistency.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["01-02-24"], ["03/02/24"], ["04-02-2024"]], "excel_metadata": [{"column_name": "Join_Date", "data_type": "DATE", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Date format inconsistency detected: '-' and '/' used; year format varies between YY and YYYY. Standardize format before load.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for invalid numeric entries.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123"], ["(567)"], ["abc"], ["-89.6"]], "excel_metadata": [{"column_name": "Bonus", "data_type": "NUMBER(5,1)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Rows 2 and 3 contain non-numeric values ('(567)', 'abc') which violate NUMBER datatype. Others are valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Aggregate revenue by region.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["North", "1200"], ["South", "800"], ["North", "720"]], "column_mapping": ["Region", "Total_Revenue"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The region with the highest total revenue is 'North' with a total of 1920.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check if values fit VARCHAR2(5) column.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123.4"], ["123.45"], ["1234.5"]], "excel_metadata": [{"column_name": "Amount", "data_type": "VARCHAR2(5)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 2 ('123.45') and Row 3 ('1234.5') exceed the VARCHAR2(5) limit. Only '123.4' is valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Identify padded values violating NUMBER(10,8) precision.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["12.34567891"], ["1234.67"], ["12345"]], "excel_metadata": [{"column_name": "Conversion_Rate", "data_type": "NUMBER(10,8)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Only '12.34567891' is valid. '1234.67' and '12345' will exceed precision 10 after padding.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check total units sold.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["120"], ["85"], ["90"], ["75"], ["60"]], "column_mapping": ["Total_Units"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The total units sold is 430.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for null values in NOT NULL columns.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123", "", "Sales"], ["456", "John", "Marketing"]], "excel_metadata": [{"column_name": "Emp_ID", "data_type": "NUMBER(5)", "allow_null": "No"}, {"column_name": "Emp_Name", "data_type": "VARCHAR2(10)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(20)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 has a NULL value in column 'Emp_Name', which is marked NOT NULL. Please correct the data.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate data length against column definitions.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["AliceSmith", "HR"]], "excel_metadata": [{"column_name": "Emp_Name", "data_type": "VARCHAR2(5)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1: 'Emp_Name' exceeds max length of 5 (value: 'AliceSmith'), 'Department' exceeds max length of 2 (value: 'HR').<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for values violating NUMBER precision and scale.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["1234567890.12"], ["123456.7"]], "excel_metadata": [{"column_name": "Salary", "data_type": "NUMBER(10,2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 value '1234567890.12' exceeds precision 10. Row 2 is valid and will be padded to 123456.70.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate invalid characters in column names.<|eot_id|><|start_header_id|>user<|end_header_id|>{"excel_metadata": [{"column_name": "1stName", "data_type": "VARCHAR2(20)", "allow_null": "No"}, {"column_name": "Dept$", "data_type": "VARCHAR2(30)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Invalid column names detected: '1stName' starts with a number, 'Dept$' contains illegal character '$'.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Ensure date format consistency.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["01-02-24"], ["03/02/24"], ["04-02-2024"]], "excel_metadata": [{"column_name": "Join_Date", "data_type": "DATE", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Date format inconsistency detected: '-' and '/' used; year format varies between YY and YYYY. Standardize format before load.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for invalid numeric entries.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123"], ["(567)"], ["abc"], ["-89.6"]], "excel_metadata": [{"column_name": "Bonus", "data_type": "NUMBER(5,1)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Rows 2 and 3 contain non-numeric values ('(567)', 'abc') which violate NUMBER datatype. Others are valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Aggregate revenue by region.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["North", "1200"], ["South", "800"], ["North", "720"]], "column_mapping": ["Region", "Total_Revenue"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The region with the highest total revenue is 'North' with a total of 1920.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check if values fit VARCHAR2(5) column.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123.4"], ["123.45"], ["1234.5"]], "excel_metadata": [{"column_name": "Amount", "data_type": "VARCHAR2(5)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 2 ('123.45') and Row 3 ('1234.5') exceed the VARCHAR2(5) limit. Only '123.4' is valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Identify padded values violating NUMBER(10,8) precision.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["12.34567891"], ["1234.67"], ["12345"]], "excel_metadata": [{"column_name": "Conversion_Rate", "data_type": "NUMBER(10,8)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Only '12.34567891' is valid. '1234.67' and '12345' will exceed precision 10 after padding.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check total units sold.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["120"], ["85"], ["90"], ["75"], ["60"]], "column_mapping": ["Total_Units"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The total units sold is 430.<|eot_id|>
|
<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for null values in NOT NULL columns.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123", "", "Sales"], ["456", "John", "Marketing"]], "excel_metadata": [{"column_name": "Emp_ID", "data_type": "NUMBER(5)", "allow_null": "No"}, {"column_name": "Emp_Name", "data_type": "VARCHAR2(10)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(20)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 has a NULL value in column 'Emp_Name', which is marked NOT NULL. Please correct the data.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate data length against column definitions.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["AliceSmith", "HR"]], "excel_metadata": [{"column_name": "Emp_Name", "data_type": "VARCHAR2(5)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1: 'Emp_Name' exceeds max length of 5 (value: 'AliceSmith'), 'Department' exceeds max length of 2 (value: 'HR').<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for values violating NUMBER precision and scale.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["1234567890.12"], ["123456.7"]], "excel_metadata": [{"column_name": "Salary", "data_type": "NUMBER(10,2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 value '1234567890.12' exceeds precision 10. Row 2 is valid and will be padded to 123456.70.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate invalid characters in column names.<|eot_id|><|start_header_id|>user<|end_header_id|>{"excel_metadata": [{"column_name": "1stName", "data_type": "VARCHAR2(20)", "allow_null": "No"}, {"column_name": "Dept$", "data_type": "VARCHAR2(30)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Invalid column names detected: '1stName' starts with a number, 'Dept$' contains illegal character '$'.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Ensure date format consistency.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["01-02-24"], ["03/02/24"], ["04-02-2024"]], "excel_metadata": [{"column_name": "Join_Date", "data_type": "DATE", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Date format inconsistency detected: '-' and '/' used; year format varies between YY and YYYY. Standardize format before load.<|eot_id|>
|
<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for invalid numeric entries.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123"], ["(567)"], ["abc"], ["-89.6"]], "excel_metadata": [{"column_name": "Bonus", "data_type": "NUMBER(5,1)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Rows 2 and 3 contain non-numeric values ('(567)', 'abc') which violate NUMBER datatype. Others are valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Aggregate revenue by region.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["North", "1200"], ["South", "800"], ["North", "720"]], "column_mapping": ["Region", "Total_Revenue"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The region with the highest total revenue is 'North' with a total of 1920.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check if values fit VARCHAR2(5) column.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123.4"], ["123.45"], ["1234.5"]], "excel_metadata": [{"column_name": "Amount", "data_type": "VARCHAR2(5)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 2 ('123.45') and Row 3 ('1234.5') exceed the VARCHAR2(5) limit. Only '123.4' is valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Identify padded values violating NUMBER(10,8) precision.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["12.34567891"], ["1234.67"], ["12345"]], "excel_metadata": [{"column_name": "Conversion_Rate", "data_type": "NUMBER(10,8)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Only '12.34567891' is valid. '1234.67' and '12345' will exceed precision 10 after padding.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check total units sold.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["120"], ["85"], ["90"], ["75"], ["60"]], "column_mapping": ["Total_Units"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The total units sold is 430.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for null values in NOT NULL columns.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123", "", "Sales"], ["456", "John", "Marketing"]], "excel_metadata": [{"column_name": "Emp_ID", "data_type": "NUMBER(5)", "allow_null": "No"}, {"column_name": "Emp_Name", "data_type": "VARCHAR2(10)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(20)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 has a NULL value in column 'Emp_Name', which is marked NOT NULL. Please correct the data.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate data length against column definitions.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["AliceSmith", "HR"]], "excel_metadata": [{"column_name": "Emp_Name", "data_type": "VARCHAR2(5)", "allow_null": "No"}, {"column_name": "Department", "data_type": "VARCHAR2(2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1: 'Emp_Name' exceeds max length of 5 (value: 'AliceSmith'), 'Department' exceeds max length of 2 (value: 'HR').<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for values violating NUMBER precision and scale.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["1234567890.12"], ["123456.7"]], "excel_metadata": [{"column_name": "Salary", "data_type": "NUMBER(10,2)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 1 value '1234567890.12' exceeds precision 10. Row 2 is valid and will be padded to 123456.70.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Validate invalid characters in column names.<|eot_id|><|start_header_id|>user<|end_header_id|>{"excel_metadata": [{"column_name": "1stName", "data_type": "VARCHAR2(20)", "allow_null": "No"}, {"column_name": "Dept$", "data_type": "VARCHAR2(30)", "allow_null": "Yes"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Invalid column names detected: '1stName' starts with a number, 'Dept$' contains illegal character '$'.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Ensure date format consistency.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["01-02-24"], ["03/02/24"], ["04-02-2024"]], "excel_metadata": [{"column_name": "Join_Date", "data_type": "DATE", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Date format inconsistency detected: '-' and '/' used; year format varies between YY and YYYY. Standardize format before load.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check for invalid numeric entries.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123"], ["(567)"], ["abc"], ["-89.6"]], "excel_metadata": [{"column_name": "Bonus", "data_type": "NUMBER(5,1)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Rows 2 and 3 contain non-numeric values ('(567)', 'abc') which violate NUMBER datatype. Others are valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Aggregate revenue by region.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["North", "1200"], ["South", "800"], ["North", "720"]], "column_mapping": ["Region", "Total_Revenue"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The region with the highest total revenue is 'North' with a total of 1920.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check if values fit VARCHAR2(5) column.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["123.4"], ["123.45"], ["1234.5"]], "excel_metadata": [{"column_name": "Amount", "data_type": "VARCHAR2(5)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Row 2 ('123.45') and Row 3 ('1234.5') exceed the VARCHAR2(5) limit. Only '123.4' is valid.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Identify padded values violating NUMBER(10,8) precision.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["12.34567891"], ["1234.67"], ["12345"]], "excel_metadata": [{"column_name": "Conversion_Rate", "data_type": "NUMBER(10,8)", "allow_null": "No"}]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>Only '12.34567891' is valid. '1234.67' and '12345' will exceed precision 10 after padding.<|eot_id|>
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>Check total units sold.<|eot_id|><|start_header_id|>user<|end_header_id|>{"csv_data": [["120"], ["85"], ["90"], ["75"], ["60"]], "column_mapping": ["Total_Units"]}<|eot_id|><|start_header_id|>assistant<|end_header_id|>The total units sold is 430.<|eot_id|>
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