What is the difference between soft delete and hard delete in SQL, Informatica power center and Informatica cloud?

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Understanding Deletion in SQL:

1. Soft Delete in SQL:

   • Definition: Soft delete refers to the practice of marking a record as deleted without actually removing it from the database.
   • Implementation: In SQL, this is often achieved by adding a column like "IsDeleted" to the table and updating its value to indicate the deleted status.
   • Advantages:
     • Data can be recovered easily.
     • Historical records are preserved.

2. Hard Delete in SQL:

   • Definition: Hard delete involves the permanent removal of a record from the database.
   • Implementation: Typically accomplished using the SQL DELETE statement.
   • Advantages:
     • Frees up storage space.
     • Improves query performance.

Deletion in Informatica PowerCenter:

1. Soft Delete in Informatica PowerCenter:

   • Usage: Implemented through the use of mapping logic.
   • Example: Utilizing a filter transformation to exclude records marked for deletion.
   • Advantages:
     • Retains data integrity.
     • Allows for auditing and tracking changes.

2. Hard Delete in Informatica PowerCenter:

   • Usage: Employing the DELETE command in SQL within a mapping.
   • Example: Using a SQL transformation to execute the DELETE statement.
   • Advantages:
     • Efficient for large-scale data purges.
     • Reduces storage overhead.

Deletion in Informatica Cloud:

1. Soft Delete in Informatica Cloud:

   • Implementation: Similar to Informatica PowerCenter, achieved through mapping logic.
   • Example: Applying filter transformations to exclude soft-deleted records during data integration.
   • Advantages:
     • Enables data governance.
     • Supports compliance requirements.

2. Hard Delete in Informatica Cloud:

   • Implementation: Utilizing SQL transformations or stored procedures.
   • Example: Integrating a SQL transformation that executes a DELETE statement.
   • Advantages:
     • Useful for scenarios requiring immediate data removal.
     • Enhances data cleansing processes.
       
       

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