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2.2.4 Migration Test
References:
2) How to create / run Daily Batch Job
3) Data Quality Service for Data Integrity
4) How to utilize Data Warehouse
For this test, we implemented SSIS (SQL Server Integration Service) package, and to monitor data integrity, we implemented Data migration monitoring App using Angular for front-end and node.js for back-end.
See More:
Implementing SSIS (SQL Server Integration Service)
Migration Monitoring App with Angular for front-end
Migration Monitoring App with Node.js for back-end
Test Case ID: GS_MIG_002
Test Scenario: Migrate Dynamic Data
Test Case: 02. Migrate SQL server's live data
(import_product, import_product_version...)
to MongoDB (without Temp DB)
Pre-Condition:
- Start SQL Server
- Confirm the service status (SQL Server and SQL Server Browser must be started)
- Set up tables on SQL Server
- Create tables: import_product, import_product_version
- Make 100 source data to migrate
- Set up a MongoDB
- Create collection: import_product_ms
- Write SSIS package
- Implement Migration data Monitoring App
Test Step:
- Open Migration data Monitoring App
- Open SSIS package with Visual Studio
- Execute ETL tool to migrate data (with SSIS)
- Confirm the complete of SSIS in normal
- Confirm the data on target database (MongoDB)
Expected Result:
- Target DB's document count is the same to the source DB's row count.
- There is no different data between source and target DB.
Actual Result:
- Using Data Monitoring App, confirm that the data count is the same and there is no data difference
- As a result of the test, Actual Result is the same to Expected Result.
Status(Pass/Fail): Pass
Test Case ID: GS_MIG_002
Test Scenario: Migrate Dynamic Data
Test Case: 03. Migrate SQL server's live data
(import_product, import_product_version...)
to MongoDB (without Temp DB), generating unmatched data
Pre-Condition:
This is the same to GS_MIG_002_02 Test Case.
Test Step:
- Open Migration data Monitoring App
- Open SSIS package with Visual Studio
-
Set up the break-point
-
Execute ETL tool to migrate data (with SSIS)
- Confirm the complete of SSIS in normal
- Confirm that execution is suspended in break-point
- Confirm the data on target database (MongoDB)
- Change MongoDB data to test data difference check: pid, gtin, gln, productName_en, productName_fr
- Resume SSIS package
- Confirm tests collection has document on MongoDB.
Expected Result:
- There is different data between source and target DB.
Actual Result:
- Using Data Monitoring App, confirm that there is different data.
- As a result of the test, Actual Result is the same to Expected Result.
Status(Pass/Fail): Pass
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