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Data Migration Testing Approach
Entry Criteria for DM testing
Scope
DM Verification By
Sign-off By
•Migration strategy covering source to target details including impact on business validations as part of migration.
•Bank to provide list of qualitative & quantitative reports in scope of testing.
•Bank to share field mapping documents from source to target for all screens in scope of migration.
•Data migration with 90% data accuracy available in SIT and UAT env as entry criteria to start Pre-SIT, SIT & UAT execution.
•Bank to share field mapping documents from Source to target
Bank to share business validations to be checked as part of DM profiling.
Bank to arrange walkthrough of all table/schema structures to QK DM tester
Involvement in Mock Migration Reconciliation:
Verification of DM reports generated by Dev/Bank IT.
•Qualitative Reports
•Quantitative Reports
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Screen To Screen Comparison:
Source to Target screen comparison for 100 transactions covering all products and sub-products
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Testing with migrated data:
Use of migrated customers in Pre-SIT, SIT and UAT Testing
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Source to Target verification at database level
•Verification of Source to Target Tables
•SharePoint to Azure Documents
•Data Take-on Transactions from Source to target
•Migration verification
Level 1 Verification by Bank IT
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Level 2 Verification by QK Team / Bank Business Team
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QK Team
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QK Team
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QK Team
Bank IT
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Bank Business Team
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QK Team /Bank Business Team
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QK Team / Bank Business Team
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QK Team / Bank Business Team
Data Migration Testing Approach
Input Data Massaging
•Pre-Migration and Post Migration files are received in txt/lst formats
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•Flexibility to define primary key on which comparison to be carried out
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•Flexibility to define mapping between Pre and Master Data to validate 1-1 transformation logic
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•Flexibility to define totalling and aggregation columns
Data Format Conversion & Processing
•The txt/lst files are populated to auto created MS SQL data tables
•Data between the Pre and Post tables are compared via prewritten SQL queries
•1-1- Transformation logics compared via SQL queries
•The txt/lst files are converted to Excel.
Reconciliation Report
•Reports call out the matched and unmatched entities
•Summary report for unmatched data on sampling basis
•Summary report detailing number of rows and columns verified, matched, missing data, extra rows
•Summation report and Count Report with totals and aggregations
•Sample records for unmatched cells
Utility Data Migration Verification
Built for End-To-End Testing of Pre and Post Migration Data
Verify comprehensive data files encompassing banking data in few clicks. Parallel Multi execution (Java based) approach depending on volume of data
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Flexible Configuration
Flexibility given to user to define Primary keys sets on which comparison to be made, Mark Columns to be applied summation and define aggregation. No coding required
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Multiple Reports
Various reports depicting the data differences within the 2 files. Summary reports on umber of rows and columns processed, etc.
200 Branches Verification
The utility has been verified to handle the load of data migration verification of 200 banks simultaneously. The turnaround time to complete the verification was a single day.
40 + files per branch
There were ~40 files having segregated data of CASA accounts, Customer data, Locker data, etc. The utility processes all branch wise data files for easy reconciliation
1 + million records verified
The utility has handled parallel Data Migration verification of 1 million + records. 8 GB RAM Machines with i3, i5 processors used.