MigrateIQ.
Give a technical migration a structured review process.
A development project for parsing and reviewing industrial configuration data before producing a migration output.
Software development project01 /The context
What needed
to work better.
Configuration migrations can involve records from several source formats, inconsistent fields, and the need to review mappings before exporting a new structure.
02 /What was built
- A Python pipeline with ICONICS alarm, OPC, and screen-export parsers.
- Normalization, mapping, validation, and SDM output modules.
- A web interface with upload, project review, result, and reviewer screens, plus parser and mapping tests.
03 /The thinking
The pipeline separates ingestion, mapping, validation, and output so each stage has a clearer responsibility. The review interface gives a person a place to inspect the transformation.
04 /The decisions
Validation is a separate stage with its own output
Parsing, mapping, validating and writing are distinct modules. In data migration the expensive failure is a file that loaded successfully and was wrong, so validation earns its own step and its own visible result.
A human reviews before anything is written
The React interface exists so a person can see what the mapping decided. Migration is exactly the kind of work where automation should prepare the decision and not make it.
Tests cover the parsers, because that is where format surprises live
Industrial data arrives in shapes nobody documented. The tests are concentrated where reality differs from the specification.
05 /Where it fits
The same architecture is useful for business data imports, legacy-system transitions, and other tasks that require careful review of a conversion.
Explore the service06 /Questions
Has this been deployed industrially?
No such claim is made here. This is a software development project: parsers, mapping, validation, output and a review interface, with tests.
Why does a migration need a review screen at all?
Because the cost of a silent mapping error only appears months later, in a system everyone has started trusting.
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