1. Data Migration Process

2. Table of Contents Purpose and Prerequisites Data Migration Data Flow
Data Migration Process Flow
Data Migration Process Description
Roles and Responsibilities
Premium Collection after Data Migration Roll-outs
PLI Data Cleansing
Data Mapping
McCamish Modules

3. Purpose, Inputs and Output for Data Migration Process
The purpose of Data Migration Process is to ensure a smooth, accurate and timely migration of data from existing PLI/RPLI system to McCamish without impacting customer service and productivity of the customer.
Forms part of content for Data Migration training to IP-PLI
Purpose
Sign off on Data Migration Plan
Confirmation from IP-PLI on preparedness of office data to be migrated.
LAN/WAN network readiness confirmation
Command Center should be ready
List of offices identified for Data Migration as per Rollout Plan
Entry Criteria/ Inputs
Data Migration from PLI/RPLI to McCamish
Sign off on Reconciliation Reports
Exit Criteria/ Output

4. Data Migration Data flow

5. Data Migration Process Flow
Sign-off from IP (PLI)
PMU – IP (PLI)
PLI to run scripts and share the discrepancy report with the circles
IP (PLI)
Data is clean or not?
To next phase
Data Mapping (Source System v/s Target System)
DM Team - Infosys
Share scripts of Data Cleansing rules with NIC/PLI
Infosys
Data Cleansing & Enrichment
Sys Admin – IP (PLI)
YES NO
DB – Converted and Cleansed data of all HOs
Sign-off on DM Plan
-Finalise DM Process
-DM Training
-LAN/WAN Readiness

6. Data Migration Process Flow…Contd.
Data Validation & Correction
Circle Officer – Infosys & IP (PLI)
From previous phase
Transfer PLI/RPLI DB from NIC
DM Team - Infosys
Extract Data
Stage 1 Area
Transform Source Data into format as reqd. by Target System
Target Schema Tables (Stage 2 Area)
Reconciliation
Data Upload
Upload Team - Infosys
Pre-staging Area
Data Profiling Report
Reconciliation Report
Sign-off
PMU – IP (PLI)
McCamish Staging Area

7. Data Migration Process Flow…Contd.
From previous phase
Trial Run
DM Team - Infosys
One-time activity for the selected offices
Sign-off
PMU – IP (PLI)
SIT
Report
System Integration Testing
DM Team - Infosys
UAT
Report
Mock Run
DM Team - Infosys
User Acceptance Testing
Zonal PMs – Infosys & End User IP (PLI)
Bug Fixing
YES
Is SIT successful? NO
Bug Fixing
Is UAT successful? NO
Data Uploading - Final
DM Team - Infosys
YES
End
McCamish Tables

8. Data Migration Process Description
Identifying source tables from PLI/RPLI system
Identifying source tables from McCamish system
Perform data mapping exercise
Data Mapping
Data Cleansing
Data will be extracted from the pre staging area. After validation and correction using validation engine the content of DB would be replicated to Stage 1 area for data transformation process
Data Transformation is the process of applying a set of rules to bring PLI/RPLI data to the same format as the McCamish . After transformation the Data will be inserted to the Stage 2 area and thereafter uploading to McCamish Staging Area
Data Extraction, Transformation and Loading
Sharing of PLI/RPLI Data cleansing scripts to NIC by Infosys. NIC will share the discrepancy reports to Circle offices after executing the scripts
Data will be cleansed and enriched with the help of Data Enrichment Cleansing Rules by DoP
The cleansed DB will be transferred to the pre staging area

9. Data Migration Process Description
The reconciliation reports will be generated and validated before the uploading process
In the Upload process data will be loaded to Stage 2 Area
From Stage 2 area, data will be further migrated to production
Trial migration will happen for selected offices
Mock migration will happen across offices
Data Extraction, Transformation and Loading (Cont.)
After trial migration, system integration testing will be performed which will be followed by mock migration .After mock migration, user acceptance testing will be performed.
After UAT, data will be further migrated to production
User Acceptance testing and Final Upload

10. Roles and Responsibilities

11. Premium Collection after Data Migration roll-outs

12. Data Discrepancy Report

13. Data Discrepancy Report

14. Data issues Policy Status not known or is incorrect in system
Pay Mode is Null
Medical is Null or is Invalid
DO Code is Null
Spouse DOB is Null (YS)
Invalid Gender
Invalid Category
Difference between DOB and DOA is more than 45 years (CWLA Policies) .
Policies with loan amount less than 1000.

15. Data Cleansing
Infosys provided data cleansing scripts to DoP to generate policy wise data discrepancy report for Pilot offices
DoP to get those scripts run and share discrepancy report with respective offices
To run these scripts, appropriate access to database is required
Cleansing is to be done manually mostly by referring to case files and/or related ledger / table
Refer to data cleansing rules for more details in share point

16. Thank You