snowflake_stored_procedure_real_world_scenario

/*
Use Case: Data Cleansing and Deduplication

Suppose you're working for a healthcare organization that manages patient data in a Snowflake database. 
Over time, the database accumulates duplicate patient records due to various data entry errors or system glitches. 
To ensure data accuracy and integrity, you aim to create a stored procedure that cleanses and deduplicates the patient records.

1. Objective: Develop a stored procedure named `CleansePatientData` to identify and merge duplicate patient records while maintaining data consistency.

2. Stored Procedure Creation:
   - Create a stored procedure `CleansePatientData` that identifies and merges duplicate patient records based on matching criteria like name, date of birth, and address.

3. Procedure Logic:
   - Upon invoking the `CleansePatientData` procedure, it begins the deduplication process.
   - It identifies potential duplicate records by comparing patient details (e.g., name, date of birth, address) in the `Patients` table.
   - Algorithmically determine similarity thresholds for merging records (e.g., fuzzy matching on names, exact matching on date of birth).

4. Actions:
   - Merge identified duplicate patient records, updating references in related tables (e.g., medical history, appointments) to maintain data consistency.
   - Log the merged records and any potential data conflicts or issues encountered during the deduplication process for review.

5. Sample Stored Procedure Code (Note: This code is conceptual and may require adjustments based on specific business logic and data structure):
*/

   CREATE OR REPLACE PROCEDURE CleansePatientData()
   RETURNS STRING
   LANGUAGE SQL
   AS
   $$
   DECLARE
     merged_records INT;
   BEGIN
     merged_records := 0;
     
     -- Identify potential duplicate patient records
     FOR patient_rec IN (
       SELECT p1.patient_id AS patient_id_1, p2.patient_id AS patient_id_2
       FROM Patients p1
       JOIN Patients p2 ON p1.name = p2.name
                         AND p1.date_of_birth = p2.date_of_birth
                         AND p1.address = p2.address
                         AND p1.patient_id <> p2.patient_id
     ) DO
       -- Merge duplicate records and update related tables
       UPDATE MedicalHistory
       SET patient_id = patient_rec.patient_id_1
       WHERE patient_id = patient_rec.patient_id_2;
       
       -- Perform similar updates for other related tables if applicable
       
       -- Delete duplicate patient record
       DELETE FROM Patients WHERE patient_id = patient_rec.patient_id_2;
       
       merged_records := merged_records + 1;
     END FOR;
     
     RETURN 'Deduplication process completed. Merged ' || merged_records || ' duplicate records.';
   EXCEPTION
     WHEN OTHERS THEN
       RETURN 'Error encountered during data deduplication: ' || ERROR_MESSAGE();
   END;
   $$;

/*
6. Execution:
   - To initiate the data cleansing and deduplication process, call the stored procedure `CleansePatientData`.
   - Example: `CALL CleansePatientData();`

7. Benefits:
   - Data Integrity: 
       Ensures accurate patient records by removing duplicates.
   - Efficiency:
       Automates the deduplication process, saving time and effort.
   - Error Handling:
      Provides logs for potential conflicts or issues encountered during deduplication.
*/