Data Migration Testing

Data migration
Data quality
Data verification
Currently I am working on a data migration project. I would like to know "What are the aspects that need to be considered during Testing? Also, what are the aspects that need to be addressed in data verification?"

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When you talk about Data migration. First you need to know the type of Data, like DB, CIFS non structured data, etc, what kind of file system you migrate, from what technology to what technology. Is the File systems (FS) are SAN, NAS, directe attached, Virtual Luns,

After you need to know who is accesing the data, thoes the data is sencitive (you will need to know what toes mean sencitivity for your organisation)

You also need to know where is the data is going, Tier 1 disk (mean SCSI, Fiber SCSI High hand Disk) Thier 2 disk, SATA, Fiber Sata (FSATA),

The migration risk to impact the backups, so make sure you have enough backup space.

and you need to consider the tool you will use to do the migration, script, SAN/SAN manufacturer tool, Software manufacturer tool like Quest.

and you will need to plan a Lab to do test, a pilote this is end users that test live data after a migration and at the end what is the migration plan how many user at a time, time frame for the migration.

Their is some of the thing you should consider for your data migration

Michel Monette
Storage Architect
Bombardier Aerospace

P.S. Sory for my english my first language is French.

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  • Mayurkhe
    Data Migration(DM) projects involve a high level of risk due to large volumes of data to be dealt , New functionalites infused with old funcationlaities, variants of O.S , Application upgrades.Data rules for integrity, controls, security, availability and recoverability are often ill- defined . What legacy data is really required by New System . Do Gap Analysis to identifying what are differences in the functionality of the target system and legacy system , this helps to identify data may be left behind or alternatively generating default data for the new system where nothing comparable exists on legacy. DM involves ELT(Extract , Transform , Load) Extract: What will be the tentative number of tables , columns and rows that require to be transformed. It is always good to have DFD diagram based on which you can get a picture of the satellite modules which can be affected in New system after TRANSFORMATION. Ensure if Data Refertial Integrity is maintained to reduce orphan data. There can be some hard coded values in Old system(Source Db) for few columns . Ensure that they matches in New System(Target DB) . Transormation: Voulme of Data Migrated can be Transfored to new system either by deleting or by updating . Depends on what'sagreed with Client. a) Delete : When we tend to not port the rows which are without fkeys in the parent table. Only those which follow referentail integrity will be ported. b) Update: When we tend to simply update the rows . Update will replace FK values with null. Load: If Convsersion Types during transformation are incorrect . Consider if Source DB has a 'Varchar ' type which is being tried to load to Target Db , can give error. In Target DB there can be a Column with "Not Null ' value. So if the Source Column has NULL values , there can be a problem during transformation. 'Default data' used in new application and legacy data do not match. This can affect Calculation /Formula's and Funtcation Logic as incorrect data will be picked . Test to identify Duplicate data. Horizontal/Vertical reconciliation , Translation Table Validation , Eyeballing are important techniques to get Data Migration issues .If there are UAT goals/objectives/requirements established, then one must develop tests to prove them . The Data migration project can be very time consuming and impact on business can be high . During planning state itself we can have a Operational Database Task List and Dependecies during various phases of project. In DM projects Mapping document is of great use . Performance Test to prove any specific requirements can be done. Some important docs from QA perspective are :• Gap Analysis document SRS - Migration Specification document , Data Migration Strategy document , Migration Tools (Design/Test/Usage) documents ,User Acceptance Test Plan (UAT) document ,Test Criteria, Plan & Procedures . Hope this helps. :)
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  • Subhendu Sen
    Upon choosing a robust migration methodology is one of the main thing. Before migrate data, analyze the data models first, like if the database is same then it is easy but if the databases are different then, need to take care data types issues, data base specific issues. There are more, here is a good article and step by step procedure:

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