How We Use AI in Data Migration
- Data profiling – AI scans legacy data to find duplicates, gaps and inconsistencies before mapping starts.
- Mapping – AI suggests source-to-Banner field mappings for our consultants to review and approve.
- Cleansing rules – AI proposes automated cleansing rules, cutting manual correction between runs.
- Unstructured data – AI extracts and structures curriculum, module and programme information from documents and free text.
- Full-volume reconciliation – every record is checked, not a sample, with a dashboard of stats and errors for each run.
Every AI suggestion is reviewed by a consultant before it touches your data.
Our Offerings
Our Ellucian Banner Data Migration Testing services provide the expertise and support needed to ensure a smooth and secure migration. Whether you're just starting or need full migration assurance, we offer tailored packages designed to meet your institution's unique requirements.
Discovery – 4-day workshop
- Deliver 4-day workshop
- Develop a high-level Data Management (DM) strategy
- Draft RACI
- Create high-level schedule.
Discovery Plus – strategy and framework
Everything in Discovery, plus:
- Extraction and transformation tool selection
- Framework design and template creation
- Data cleansing approach
- Data reconciliation approach
- Data mapping template
End-to-End Data Migration Assurance
Extraction:
- Create complete and separate data extract files for defined Banner table.
- Create scripts to extract and transform data into load ready files.
- Undertake unit testing.
- Undertake technical reconciliation.
- Provide run summary/dashboard listing all stats and errors.
Data Cleansing:
- Create scripts to perform data clean up and error reconciliation in legacy systems or corrections made to data extracts before second run and final conversion runs.
- Create scripts to transform data into expected Banner format.
- Include rules for automated data cleansing where possible.
- Use AI to profile data and propose cleansing rules, reviewed by our consultants.
Data Validation:
- Verify and validate the converted data.
- Ensure data is successfully transferred to the designated Banner non-production environment.
- Follow the agreed-upon user acceptance test plan during the verification process.
- Reconcile 100% of migrated records, not a sample, with results reported for every run.
Why It Matters
Errors in migrated student records surface at the worst times: module registration, results release, HESA Data Futures returns and graduation. Testing the migration properly, before go-live, is far cheaper than fixing records once students and staff are using them.
Frequently Asked Questions
Which package should we start with?
Most universities start with Discovery: a 4-day workshop that produces a data management strategy, RACI and schedule. Discovery Plus adds tool selection, frameworks and templates.
How does AI help with Banner data migration?
AI speeds up profiling, mapping and cleansing, and structures unstructured curriculum data. Our consultants review every suggestion before it is applied.
Do you only test the migration, or carry it out too?
Both. We can assure a migration run by your team or partner, or carry out extraction, transformation, cleansing and validation ourselves.
Can you migrate data from systems other than Banner?
Yes. We migrate from legacy student records, curriculum management and finance systems into Banner, and between other platforms.
