Data Migration Best Practice

Technical Reconciliation:

• Statistics
• Record Count
• Not-Null Values
• Checksum for Numeric Column
• Hash Total
• Distinct String Values
• Number of rows extracted from the table
• Number of non-null values in each column of the extract
• Sum of each numeric column in the table, except primary key and foreign key columns.
• Counts of distinct strings values (or substrings) in text fields
• Control Totals
• Stock total
• Data Conversion — should measure conversion-specific metrics for each data object being converted (e.g., time to convert, fallout/error percentages, etc.).

Financial Reconciliation:

• Portfolio Market Values
• Portfolio Market Value with Accrued Income
• Portfolio Market Value without Accrued Income
• Portfolio Performance ROR - MWR (Money Weighted Return)
• Portfolio Performance ROR - TWR (Time Weighted Return)
• Portfolio Performance - since inception RoR (MWR, TWR)
• Position Quantity and Cost
• Position Book Cost
• Position Native Cost
• Initial Holding
• Number of Clients and their accounts (Active, Closed, etc.)
• For each account, number of position and their values.
• For each account, number of transactions on a specific business date.
• Transaction status validation between source and target.

Reconciliation Plan: Technology Team

Objective: Ensure accurate and complete transmission and receipt of data files between source systems, client, and the third-party SaaS system.

Tasks:
1. Establish data transmission protocols and file formats: Determine the protocols (e.g., FTP, SFTP) and file formats (e.g., CSV, XML) for data transmission between systems. Document the specifications and share them with relevant stakeholders.

2. Develop data extraction and transformation scripts: Create scripts or programs to extract data from source systems, transform it based on defined rules, and generate data files in the required format. Test the scripts thoroughly to ensure accurate data extraction and transformation.

3. Implement data encryption and security measures: Set up encryption mechanisms and security protocols to protect the data during transmission. Apply appropriate access controls, authentication methods, and encryption algorithms to maintain data confidentiality and integrity.

4. Establish data transfer schedules and monitoring: Define a schedule for data transfers between systems, considering the frequency and timing requirements of each data component. Monitor the data transfers to ensure they occur as scheduled and address any transmission failures promptly.

5. Implement error handling and logging mechanisms: Develop error handling procedures to identify and address data transmission errors. Log all errors encountered during data transmission for analysis and resolution.

6. Conduct connectivity and compatibility tests: Perform connectivity tests to verify the communication channels between systems. Test compatibility between file formats, versions, and data structures to ensure smooth data transmission and receipt.

7. Document data transmission processes: Create comprehensive documentation outlining the data transmission processes, including step-by-step instructions, error handling procedures, and contact information for support in case of issues.

Accountability and Responsibility:
- Technology Team Lead: Overall accountability for ensuring smooth data transmission.
- Network Administrators: Responsible for configuring and maintaining secure data transmission channels.
- System Administrators: Responsible for setting up and managing the data extraction and transformation scripts.
- Data Security Specialist: Accountable for implementing encryption and security measures.
- Technology Team Members: Responsible for monitoring data transfers, error handling, and documentation.

Reconciliation Plan: Data Transformation Team

Objective: Ensure accurate data transformation based on defined rules and produce valid data extracts for further processing.

Tasks:
1. Understand data transformation rules: Review and understand the data transformation rules provided by the client or business team. Clarify any ambiguities or gaps in the rules through effective communication channels.

2. Develop data transformation logic: Create transformation logic and algorithms based on the defined rules. Implement the logic using appropriate programming languages or tools. Ensure the transformation process considers all data components and maintains data integrity.

3. Test data transformation scripts: Conduct rigorous testing of the data transformation scripts using sample data. Verify the accuracy of the transformed data against expected results. Revise and debug the scripts as necessary.

4. Validate transformed data: Perform field-level validation of the transformed data to ensure it adheres to data quality standards. Validate data formats, data ranges, and data relationships as required by the business rules.

5. Generate data extracts: Produce data extracts in the required format (e.g., CSV, XML) according to the specifications provided. Verify the extract files for completeness and accuracy.

6. Document data transformation processes: Document the data transformation processes, including the transformation rules, scripts, testing procedures, and any assumptions made during the process. Update the documentation as needed.

Accountability and Responsibility:
- Data Transformation Team Lead: Overall accountability for accurate data transformation.
- Data Analysts/Developers: Responsible for developing and testing data transformation logic and scripts.
- Quality Assurance Team: Responsible for validating the transformed data against field-level data quality standards.
- Data Transformation Team Members: Responsible for generating data extracts and documenting the transformation processes.

Reconciliation Plan: Quality Assurance Team

Objective: Ensure the accuracy, completeness, and quality of data through rigorous testing and validation.

Tasks:
1. Develop test scenarios and test cases: Identify and document test scenarios based on business rules, reconciliation requirements, and expected data outcomes. Develop test cases to validate each scenario.

2. Perform data validation tests: Execute test cases to validate data at the field level, ensuring data accuracy, completeness, and adherence to predefined rules. Verify data ranges, data types, and relationships between different data components.

3. Validate data transformation rules: Cross-check the transformed data against the provided transformation rules. Ensure that the data has been transformed correctly and consistently.

4. Verify exception handling: Test the system's ability to handle exceptions or errors in the data processing flow. Validate error messages, error logging, and error recovery mechanisms.

5. Conduct regression testing: Perform regression tests to ensure that changes made to the data transformation process or system configurations have not introduced new issues or errors.

6. Document test results and defects: Record the results of each test case, including any discrepancies or defects found. Report and track defects using a suitable defect tracking system or tool.

7. Provide feedback and collaborate with other teams: Share feedback and collaborate with the technology, data transformation, operations, and business teams to resolve any identified issues and improve data quality.

Accountability and Responsibility:
- Quality Assurance Team Lead: Overall accountability for data validation and quality assurance.
- QA Analysts: Responsible for designing and executing test scenarios, validating data, and documenting test results.
- Data Transformation Team: Collaborate with the QA team to resolve data-related issues and improve data quality.
- Technology Team: Coordinate with the technology team to address any technical issues affecting data quality.

Reconciliation Plan: Operations Team

Objective: Conduct substantive testing and validation of processed data by the vendor application.

Tasks:
1. Develop validation test scenarios: Identify and document test scenarios based on the business requirements, reconciliation objectives, and the vendor application's capabilities. Consider various data components and their interdependencies.

2. Execute validation tests: Perform comprehensive testing of the vendor application using test scenarios and test cases. Validate data outputs, system behavior, and adherence to business rules.

3. Verify system configurations: Ensure that the vendor application is correctly configured based on the business requirements. Validate system settings, user permissions, and integration with other systems.

4. Conduct system reconciliation: Compare the processed data from the vendor application with the corresponding source data and verify that they align correctly. Investigate and resolve any discrepancies or variances.

5. Test exception handling and error recovery: Validate the vendor application's ability to handle exceptional cases, error scenarios, and system failures. Verify the effectiveness of error recovery mechanisms.

6. Collaborate with other teams: Engage with the quality assurance, business, and technology teams to address issues, clarify requirements, and improve the reconciliation process.

7. Document test results and defects: Record the results of each validation test, highlighting any issues or defects encountered. Document any workarounds or resolutions implemented.

Accountability and Responsibility:
- Operations Team Lead: Overall accountability for substantive testing and validation of the vendor application's processed data.
- Operations Analysts: Responsible for executing validation tests, verifying system configurations, and documenting test results and defects.
- Quality Assurance Team: Collaborate with the QA team to address any data-related issues and ensure data accuracy.
- Business Team: Engage with the business team to clarify requirements, validate results, and improve reconciliation processes.

Reconciliation Plan: Business Team

Objective: Perform summarized level testing and validation of processed data by the vendor application, focusing on business-specific metrics and exceptions.

Tasks:
1. Define testing objectives and acceptance criteria: Determine the key metrics, reports, and exceptions that need to be validated by the business team. Define the acceptance criteria for each metric or report.

2. Develop testing strategies: Design testing strategies based on the defined objectives, considering data components

, asset classifications, CUSIP numbers, branches, investment advisors, and other relevant factors. Create test scenarios and test cases accordingly.

3. Execute testing and validation: Perform testing based on the defined strategies, using test scenarios and test cases. Validate summarized data, reports, control totals, assets by asset type, holdings by asset, and other business-specific metrics.

4. Verify exception reports and data anomalies: Review exception reports generated by the vendor application and investigate any data anomalies or discrepancies. Ensure that exception handling procedures are followed correctly.

5. Analyze and interpret test results: Analyze test results and identify any patterns, trends, or outliers. Collaborate with the operations team, technology team, and vendor support to address any issues or concerns.

6. Provide feedback and recommendations: Communicate findings, observations, and recommendations to relevant stakeholders, including the technology team, operations team, and vendor support. Propose improvements to the reconciliation process or data quality.

7. Collaborate with other teams: Engage with the operations, quality assurance, and technology teams to share insights, clarify requirements, and improve the reconciliation process.

Accountability and Responsibility:
- Business Team Lead: Overall accountability for testing and validation of business-specific metrics and exceptions.
- Business Analysts: Responsible for developing test strategies, executing testing, analyzing test results, and providing feedback and recommendations.
- Operations Team: Collaborate with the operations team to investigate data anomalies and address any issues identified during testing.
- Technology Team: Engage with the technology team to resolve technical issues and improve the reconciliation process.

Reconciliation Plan: Custody Systems Specialist Team

Objective: Perform testing and validation within the custody system and reconcile data with the processed data from the vendor application.

Tasks:
1. Understand custody system functionalities: Familiarize yourself with the features, capabilities, and data structures of the custody system. Gain a comprehensive understanding of how it processes and stores data.

2. Develop custody system testing scenarios: Identify and document test scenarios specific to the custody system, considering data components, transaction processing, asset management, and reporting requirements.

3. Execute custody system tests: Perform testing within the custody system using the defined test scenarios and test cases. Validate data inputs, transaction processing, system outputs, and reconciliation capabilities.

4. Reconcile custody system data with vendor application data: Compare the data within the custody system with the processed data from the vendor application. Verify the consistency and accuracy of data between the two systems. Investigate and resolve any discrepancies or variances.

5. Validate custody system reports: Verify the accuracy and completeness of reports generated by the custody system. Ensure that the reports align with the business requirements and reconcile with the processed data.

6. Collaborate with other teams: Engage with the operations team, technology team, and vendor support to address any issues, reconcile data discrepancies, and improve the reconciliation process.

7. Document test results and recommendations: Record the results of each custody system test, including any issues or anomalies encountered. Document recommendations for system improvements or enhancements.

Accountability and Responsibility:
- Custody Systems Specialist Team Lead: Overall accountability for testing and validation within the custody system.
- Custody Systems Specialists: Responsible for executing custody system tests, reconciling data with the vendor application, validating reports, and documenting test results and recommendations.
- Operations Team: Collaborate with the operations team to investigate data discrepancies and address any issues identified during testing.
- Technology Team: Engage with the technology team to resolve technical issues and improve the reconciliation process.