Data Transform Tests
Introduction
Data Transform Tests validate the transformation and mapping processes during the integration of data between Slate and Banner. These tests ensure data accuracy, consistency, and compliance with formatting requirements.
Objectives
Confirm that all transformations occur accurately and consistently.
Validate that data formats conform to required standards in both Slate and Banner.
Identify and resolve issues arising from incorrect or incomplete transformations.
Ensure compliance with business rules during data transformation.
Test Cases
1. Citizenship Status Transformation
Test ID | DT-001 |
|---|---|
Description | Validate transformation of citizenship status values from Slate to Banner. |
Input | FN, PR, US. |
Expected Output | FN -> "N", PR -> "E", US -> "Y". |
Steps | 1. Input test values into Slate. 2. Run integration process. 3. Verify output in Banner. |
Status | Pending |
Owner | IT Integration Team |
2. Date Format Standardization
Test ID | DT-002 |
|---|---|
Description | Ensure date fields are transformed to DD-MM-YYYY format. |
Input | MM-DD-YYYY format in Slate. |
Expected Output | DD-MM-YYYY format in Banner. |
Steps | 1. Input test dates in Slate. 2. Run integration process. 3. Confirm output format in Banner. |
Status | Pending |
Owner | IT Integration Team |
3. GPA Transformation
Test ID | DT-003 |
|---|---|
Description | Validate GPA scale conversion during data transformation. |
Input | GPA out of 4.0 in Slate. |
Expected Output | GPA out of 100 in Banner. |
Steps | 1. Input GPA values in Slate. 2. Execute transformation. 3. Verify converted values in Banner. |
Status | Pending |
Owner | QA Team |
4. Checklist Item Transformation
Test ID | DT-004 |
|---|---|
Description | Verify checklist items are accurately mapped and transformed. |
Input | Transcript Received, Test Scores Received. |
Expected Output | Corresponding checklist items in Banner. |
Steps | 1. Update checklist items in Slate. 2. Run integration. 3. Confirm mapping in Banner. |
Status | Pending |
Owner | Admissions Team |
5. Error Handling for Invalid Data
Test ID | DT-005 |
|---|---|
Description | Ensure invalid data is flagged and does not disrupt the transformation process. |
Input | Invalid citizenship values or malformed dates. |
Expected Output | Error logs generated, with no data transfer to Banner. |
Steps | 1. Input invalid data into Slate. 2. Run transformation. 3. Confirm error logging and handling. |
Status | Pending |
Owner | IT Integration Team |
Metrics for Success
Metric | Target |
|---|---|
Transformation Accuracy | 99.9% |
Error Detection Rate | 100% |
Successful Data Transformations | 100% |
Average Transformation Time | < 5 seconds |
Recommendations
Automate Validation Checks:
Implement automated checks to validate data transformations in real time.
Error Logging Improvements:
Enhance error logs to provide clear, actionable insights for invalid data.
Training:
Provide staff with training on transformation processes and issue resolution.
Periodic Audits:
Conduct quarterly reviews of transformation processes to ensure compliance and accuracy.