Data Mapping and Transformation

Correct Answer: Establish joint working sessions with data owners and subject matter experts from both systems

Establishing joint working sessions with data owners and subject matter experts from both systems is the most effective approach because: 1. It enables real-time collaboration and discussion between all relevant parties 2. It allows for quick identification and resolution of discrepancies 3. It promotes shared understanding of data mapping requirements 4. It reduces communication gaps and misinterpretations The other approaches are less effective because: Creating technical documentation for review introduces delays and may lead to misinterpretation of written requirements. Scheduling separate meetings creates silos and may result in conflicting interpretations of requirements that need additional reconciliation. Implementing automated tools as the primary approach lacks the crucial human interpretation and context needed for complex data mapping decisions, and may miss business context or nuanced requirements.

Correct Answer: Create a centralized date conversion logic and apply it uniformly across all systems

Creating a centralized date conversion logic and applying it uniformly across all systems is the best approach for standardization because: - It ensures consistency across the entire organization - Reduces the risk of data inconsistencies and errors - Makes maintenance easier as there's only one source of truth - Simplifies future updates and modifications - Promotes data integrity and reliability The other options are problematic because: Maintaining different date formats per department creates complexity and increases the risk of errors during data exchange between systems. Applying sequential transformation rules based on business units leads to inconsistent data handling and makes system integration more difficult. Creating custom scripts for each source system results in unnecessary complexity, higher maintenance costs, and increased risk of errors across different implementations.

Correct Answer: Definition of common business rules for data standardization

The definition of common business rules for data standardization is the highest priority aspect during the analysis phase of a data transformation project involving multiple source databases. This is critical because: - It establishes consistency across all data sources early in the project - It prevents downstream issues in data integration - It ensures business requirements are properly reflected in the transformation rules - It creates a foundation for all subsequent technical implementations The other options are important but secondary: - Automated validation scripts come after business rules are established - Documentation is important but follows the definition of rules and processes - Technical specifications for data mapping are implementation details that must align with already-established business rules By prioritizing business rules standardization, organizations ensure that data transformation efforts align with business objectives and maintain consistency across all integrated systems.