To find the claim data validation checks

Introduction: Identifies claims Validation Checks by analyzing the claim data, ensuring data integrity across various fields with missing fields, Invalid claim amount, Date validation, Duplicate claims, Invalid status.

 

Requirements: Read the ‘purgo_playground.claim_validation_check table’.

 

Conditions:

 

Missing Values Check*: Validates if Claim_ID, Patient_ID, Claim_Status, or Provider_ID are NULL or "NULL". If any of these fields are missing, the result it as 'Missing Values'.

Null Date Validation*: Checks if Service_Date is NULL or "NULL". If either condition is true, then result it as 'Invalid Date'.

Future Date Validation*: ifService_Date is a future date (greater than the current system date) then result it as 'Invalid Date'.

Negative Claim Amount*: Claim_Amount less than 0 result it as 'Invalid Claim Amount'.

Invalid Claim Status*: Verifies if Claim_Status is outside the valid set ('Pending', 'Approved', 'Denied'). If not in this set, then result it as 'Invalid Status'.

Duplicate Claim Check*: if Claim_ID >1 and result it as 'Duplicate Claims'.

Validation Check Passed*: If none of the above conditions are appears, then result it as 'All Validation Check Passed.'

* If Multiple Validation fails and show all the applicable failures only in the Validation Result.

 

Final Output: Show result with existing table with Validation results.

 

Save the results as table 'purgo_playground.claim_validation_check_output'. Both Show and Save the output.

 

Write Pyspark logic without the syntax error.

 

Unity Catalog : purgo_playground.claim_validation_check