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Data Migration Testing
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Data Migration Testing
It is a quite common phenomenon that technology teams within an organization are engaged to upgrade the internal systems while migrating to adopt a different technology or platform to meet the ever-changing demands and challenges of business. Whether the need originates as a result of transforming or adopting to a new data architecture or migrating to an entirely new platform, Data Testing plays a vital role in the success criteria of the transformation or upgrade efforts.
In order to succeed, proper Data Testing procedures and processes need to be established and adhered to during any of these operations -
- Database migration from one technology to a different technology on-premise (e.g. Oracle to SQL Server)
- Database migration from one technology On-Premise to the same or different technology on the Cloud on-premise (e.g. on- premise SAP HANA DB to Azure SQL MI)
- Database Upgrade (e.g. Oracle 11x to Oracle 12x)
Need to Automate Your Migration Testing
Data migrations can present organizations of all sizes an opportunity to organize and integrate systems into a more agile and effective manner as the business grows and their demands change. In some cases such shifts may require the data structure to change due to the nature of the target platform.
During the transfer, critical data needs to stay secure and valid so that it can remain trustworthy and can be quickly put to use post migration to the new platform. Data migration testing is the process of checking the integrity and consistency of data between the source and target platforms. Though data migration tools can help develop the pipelines to enable the actual data transfers however automated testing processes help proactively identify issues early so that they can be resolved just-in-time.
Common Database Migration Testing Pain Points to Bear in Mind
The migration testing process can face some challenges, including:
- Quality of Data: Data migration validation tools may show the data quality degraded after migration to the target platform. Data quality issues can be resolved by enhancing the existing data quality rules to meet the changed business's standards.
- Data loss: Data loss means some of the data was lost in non-mandatory and mandatory fields during migration. For currencies the source system could have had a higher precision value compared to target platform resulting in rounding issues.
- Misaligned data: A data mismatch issue is when the validation process shows that the data between the source and target platform do not match. Data type or storage format changes can cause misaligned data.
How RDt Supports Your Database Migration Testing
RightData's RDt is a self-service Data Migration testing tool designed to help business and technology teams with the automation of data quality assurance and data quality control processes. RDt's intuitive interface allows users to validate and reconcile data between datasets regardless of the differences in the data model or the data source type. It is designed to work efficiently for data platforms with high complexity and huge volumes.
RDt supports your data migration testing through:
- Comprehensive dataset validation: Our data validation process is thorough to ensure your data is accurate in the target platform. High-quality data will help you achieve accurate results and make informed decisions for your business. Our migration testing process is automated to save time and check data quality quickly.
- Dataset comparison: Our data migration testing allows you to compare your data values and structure between the source and target platforms. This comparison ensures that the transfer did not affect the data and the information still meets your quality parameters.
- Early issue identification: Identify issues early on with our automated testing migration. By catching issues early in the data migration process life cycle, you can correct them sooner. Fixing problems at this early stage is cost effective and improves the trust in your dataset.
- Reporting: Our reporting capabilities will alert you to invalid data or other workflow issues. You can use the report to identify a way to fix the data and reconfigure your workflow. You can be confident your data has no inconsistencies, errors, missing values or compliance issues.
Our Data Migration Validation Tools
RightData offers a complete set of tools to support Data Testing initiatives to improve Data Quality during these efforts. Technical Data Reconciliation (TDR) and Functional Data Reconciliation (FDR) aspects of the tool can help both the business and technology teams including quality assurance (QA) test the data by taking the snapshots before and after the migration/upgrade takes place.
Functional Data Reconciliation
FDR gives the flexibility to build the scenarios within RDt to test the data based on the functionality of the application. For example, On-Hand inventory details, Open Orders, GL Balances by fiscal periods, etc., can be tested thoroughly by doing a cell-to-cell comparison for each and every record between the systems.
Technical Data Reconciliation
TDR helps in comparing bulk datasets during migration and database upgrades. The hash algorithm is implemented to do the sanity checks on the key attributes of the data sets in bulk mode, like the number of the tables, record count from each table, metadata comparison, etc. These test cases/processes can be automated, scheduled to run repeatedly based on the requirement and saved for future migration efforts.
Choose RightData for Database Migration Testing
RightData is a software product development company that provides self-service options for businesses that need data analytics services. Our solutions have the features and turnaround time you need to effectively meet your data analytics goals.
Our RDt product can help with the data migration validations your organization requires to ensure data quality.
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