Data Migration | My Site

QK-DATA MIGRATION TESTING

Overall Experience in Data Migration & Finance

Data Migration Experience

Finance Experience

Actuarial Experience

Migration QE Assessment & Planning

To ensure that the migration aligns with business requirements and minimizes risks

• Migration Risk assessment: Understand the existing financial processes supported by SUNGL including GL , Debit, credit balance entries, mapping ,GL Masters

• Data Assessment : Understand Data and identify mapping of

• Integration and Customization Assessment Understand integration and customization

• Regulatory and Compliance Understanding current reporting and changes required for IFRS 17 standard or as per regulatory and compliance

• Risk Assessment: Identify Modules and scenarios to perform.

• Performance assessment :Baseline the current performance of key processes and transactions in SUNGL

FDR, Data Migration & MIS Report Testing

To ensure that data from SUNGL is accurately and completely migrated to Oracle Fusion as per Finance data repository

• Data Validation :

• Data Completeness Testing

• Data Accuracy Testing

• Data Consistency Testing

• Data Transformation Validation

• Data Schema Testing

• Mapping Verification

• Field-Level Testing

• Error Handling

• Data Reconciliation Testing

• Trial Balance Reconciliation

• Subledger Reconciliation

• Historical Data Reconciliation

• MIS Report validation :

• Report structure and layout

• Visualization

• Formatting consistence

Function & Integration Testing of FDR & Oracle Fusion

To ensure that different modules and systems function as expected & work together seamlessly in the Oracle Fusion

• Designing : Detailed test cases designing covering all critical life insurance scenarios, ensuring functionality in the new system.

• Walkthrough and signoff with business users

• Verify configurations, customizations, and interfaces :Automate + manual test execution on identified test scenarios

• Validate the complete and integrated system in an environment that closely resembles production

• Test end-to-end Finance business processes.

• Perform comprehensive testing of all business scenarios

• Validate data flows between SUNGL, Oracle Fusion, and any third- party systems.

Performance & Scalability Testing

To ensure Oracle Fusion system meets the performance requirements in comparison to SUNGL or exceed them

• Performance assurance :

• Plan for performance and load testing in

Oracle Fusion to validate the system’s

ability to handle financial processing loads

• Test system response times, scalability,

and stability.
Identify and resolve performance

bottlenecks.

• Ensure the system can handle large

volumes of data and

concurrent users

Migration Testing Assessment Framework

Framework-based approach to baseline, remediate, and automate the reliability of complex, distributed systems. Assessment will focus on following Key areas of reliability as stated below.

Assessment will be performed on 2 ways

1. Q&A – This will be shared with stakeholders before the meeting to come up with data points and detailed discussion.

2. Validation – Walkthrough of existing Operations (Tools, Process, Configurations, Dashboards, Incident/Ticket Analysis)

Financial Process Analysis

Understand the existing financial processes supported by SUNGL

Chart of Accounts (CoA) Assessment

Evaluate the current Chart of Accounts structure and plan its migration to Oracle Fusion.

Data Assessment

Evaluate the quality, structure, and relevance of financial data in Source Systems

Financial Reporting Assessment

Review existing financial reports and ensure they can be replicated or improved in Oracle Fusion

Integration and Customization Assessment

Evaluate existing integrations with other systems and any customizations within

Regulatory and Compliance Assessment

Ensure the migration meets all financial regulatory and compliance requirements.

Documentation Review

Data Analytics

Align findings from Assessment Study to Planning

Data Accuracy Validation

Functional Compatibility

Error & Issue Log

Reconcilation Reports

Performance Analysis

Compilance Assessment

Structured Interviews

Tools & Artifact Access

Quality Gates & Improvement

Our Domain Coverage across Finance Business Processes

General Ledger (GL) Process

1.Chart of Accounts Setup

2.Journal Entries

3.Subledger Accounting

4.Period Close

5.Financial Reporting

Accounts Payable (AP) Process

6.Supplier Setup:

7.Invoice Entry:

8.Invoice Validation:

9.Payment Processing:

10.Liability Reconciliation

Accounts Receivable (AR) Process

11.Customer Setup:

12.Invoice Generation:.

13.Payment Application:

14.Dunning and Collections:

15.Revenue Recognition: AR Reconciliation:

Fixed Assets (FA) Process

17.Asset Addition:.

18.Asset Categorization:

19.Depreciation Calculation:

20.Asset Transfers:

21.Asset Retirement/Disposal:

22.FA Reconciliation.

Cash Management Process

23.Bank Account Setup

24.Bank Reconciliation:

25.Cash Positioning:

26.Cash Forecasting:

27.Treasury Operations:

Expense Management Process

28.Expense Report Submission:

29.Approval Workflow:.

30.Expense Policy Compliance:

31.Reimbursement Processing:

32.Expense Accounting.

Procure-to-Pay (P2P) Process

33.Requisition Creation

34.Purchase Order (PO) Generation:

35.Goods Receipt:

36.Invoice Matching:.

37.Payment Processing:

Order-to-Cash (O2C) Process

38.Sales Order Entry:

39.Order Fulfilment:

40.Invoicing:

41.Payment Collection

42.Revenue Recognition:

Cash Management Process

23.Bank Account Setup

24.Bank Reconciliation:

25.Cash Positioning:

26.Cash Forecasting:

27.Treasury Operations:

Expense Management Process

28.Expense Report Submission:

29.Approval Workflow:.

30.Expense Policy Compliance:

31.Reimbursement Processing:

32.Expense Accounting.

Procure-to-Pay (P2P) Process

33.Requisition Creation

34.Purchase Order (PO) Generation:

35.Goods Receipt:

36.Invoice Matching:.

37.Payment Processing:

Order-to-Cash (O2C) Process

38.Sales Order Entry:

39.Order Fulfilment:

40.Invoicing:

41.Payment Collection

42.Revenue Recognition:

Test Strategy – Azure Databricks Architecture & Validations

Data Source

Structured

• Relational databases

• CRMs

• ERP

Semi - Structured

• JSON

• XML

• CSV

• HTML

Unstructured

• Videos

• Audio files

• Images

• PDF files

• Sensor data

• Social media data, etc.

Data Ingestion

Data Source

Validation

Data Integrity

Check

Schema

Validations

Data Staging

Data Source

Validation

Data Partitioning

Validation

Data Compression Check

Data Processing Layer

Hadoop Map Reduce

(Batch & Real-time processing)

Data Transformation Validation

Data Quality Assessment

Error Handling and

Logging

Data Storage

Curated Zone

Query Syntax Validation

Data Consistency Check

Query Performance Optimization

Data Consumption

Data Accuracy

Column & Row Counts

Data Formatting

Data Consistency

Parameterized Reports

Sorting and Filtering

Chart Validations

Error Handling

Performance

Availability 99.9% Up Time

Reliability

Accuracy

99.9% transactions without error

Speed

99.9% transactions within a time

Engineering Reliability

• Centralized NFR Management

• Shift-Left & Shift-Right

• Performance Engineering

• Capacity Benchmarking

Enhancing Customer Exp

• Data Driven CXT

• Device Performance Engineering

• Continuous Improvement through Synthetic & RUM feedback

Building Resiliency

• Fault Tolerant architecture

• Chaos Engineering

Automation Driven Agility

• Pipeline Driven PT

• Environment Automation through Service Virtualization

• E2E NFR automation framework

Observability Driven Testing

• Performance Engineering through App insight across layers

• Continuous Testing-(Production influenced)