How Does Your Approach Compare to TRUcompare?

Migrations are a complex undertaking, and traditional testing approaches often fall short of today’s business and compliance requirements. The ensuing risk can easily result in costly errors. How sound are your current testing and sampling approaches?

Does your approach verify 100% of the migrated data? In validation? For the production run?
Does your testing process avoid iterations of migration testing in an unpredictable manner?
How does your approach avoid identifying data quality issues late in the process?
If you are using an automated approach to testing / validation, is it independent of the migration software and process?
Is your migration project predictable in cost and schedule?
Will your users be familiar with the data in their new system prior to production use?

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CATEGORY

ITEM/ERROR DESCRIPTION

TRUcompare

YOUR APPROACH

Testing Scope

100% testing of migrated data and content

Migration Tool Errors

Incorrect field mapping from source-to-target system, resulting in migration errors

Partial value migrated to multi-valued fields in the target system (e.g. only first value is migrated)

Data transformation errors

Data truncation errors

Inadvertent data or record omissions during migration

Duplication of records in the target system

Document migrated to incorrect folder

Document incorrectly classified in target system

Errors in generating correct version trees

Errors in generating virtual documents

Errors in generating relations between documents or records

Errors in migrating renditions

Errors in migrating audit trail data

Content Errors

Content Corruption (not frequent, but in one instance due to incorrect setting during FTP transfer)

Incorrect location of the content

Missing content (primary content or renditions)

Data-level Errors

Mappings that result in null value mapped to mandatory fields in the target system

Unexpected content exclusions and inclusions during migration

Invalid values in source system resulting in invalid lookup transformation in target system

Source data values that do not conform to expected formats

Source values that do not have a corresponding lookup value in the target system

Special characters (tabs, crlf, etc…) that cause formatting issues in the target application

Data type mismatches

Incorrect data encoding

Migration errors due to unsupported characters

Mapping/ Specification Errors

Mappings defined for fields in the target system that does not exist in the target system. In some cases, the fields were in queue to be added and in others the fields were invalid

Mappings defined for fields in the target system that does not exist in the source system. (usually due to incorrectly specified source document type or table)

Incorrect type mappings

Mappings to external sources that did not contain any relevant data

Missing data elements in supplemental data sources used for data enrichment

Missing data translations (Source data did not match valid target values, and a new data translation mapping had to be created)

Multi-valued source fields inadvertently mapped to single-valued target fields

Incorrect system configuration mappings (e.g. incorrect lifecycle for documents type, incorrect permission for status, etc.)

Process Errors

Manual steps that were inadvertently excluded or executed incorrectly resulting in data migration errors

Migration Tool changes/customizations that were not completely tested

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TRUcompare Challenge

How Does Your Approach Compare to TRUcompare?

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