Establish clear data standards and mapping protocols across systems. Implement real-time synchronization to maintain consistency and prevent discrepancies. Use automated data validation and transformation rules during integration to catch errors early. Leverage robust data governance policies to define access control, ownership, and auditing. Regularly audit and reconcile data between systems to identify and resolve issues promptly.

Establish Data Governance Policies Define Standards: Create clear data governance policies that outline data standards, definitions, and formats. This ensures that all systems adhere to the same criteria for data entry and management. Assign Data Stewards: Designate individuals or teams responsible for overseeing data quality and integrity. Data stewards can help enforce policies and address any issues that arise. 2. Implement Data Validation Rules Validation at Entry Points: Set up validation rules at every data entry point to check for accuracy, completeness, and consistency. This can include format checks, mandatory fields, and range checks. Automated Checks: Utilize automated tools to perform real-time data validation,