Data Migration Testing: Advanced Approaches and Best Practices

What is Data Migration?

Data migration is transitioning from one system state to another to improve performance, security, or availability. However, this process can lead to unforeseen consequences, such as data loss, application interruptions, or incorrect integration of new components. This is where the testing team will play an important role. Their task is to ensure the application works stably, efficiently, and safely despite all the changes and challenges associated with data migration and check the data integrity. In this article, we will analyze all the features of migration data testing and give you a list of valuable tips. Let's start! 

Different Types Of Data Migration 

Correct data migration is crucial in developing and maintaining applications and databases. In this article, we will look at the main types of data migration. Each of these types of migration has its characteristics and advantages. 

Application Migration 

Application migration is moving an entire application from one environment or platform to another. This type of migration can lead to numerous benefits: 

1. Cost reduction: Migrating to a new platform can reduce application operation and maintenance costs by optimizing resources and reducing infrastructure costs. 
2. Reduction of dependence: Migration reduces the program’s dependence on specific systems or platforms, making it more universal and independent. 
3. Risks and security: Adopting new technologies can eliminate or reduce business risks and increase application security. 
4. Performance improvement: A new environment can improve the performance of the application and its capabilities. 
5. Improved technical support: Migration can simplify the process of technical support and application administration, which reduces maintenance time and costs. 
6. Technological changes: Migration can include transitioning to modern technologies improving the program’s competitiveness.
    

Example: There is a need for cloud database migration testing when transferring an application to a cloud platform or switching from ASP technology to ASP.Net. 

Database Migration 

Database migration is transferring all data from one database to another. This type of migration requires the application to be stable and the data in the database to be correct and valid. Database migration testing is one of the key tasks of testers in this field. 

Database migration can lead to product benefits:

1. Data preservation: Data remains accessible and intact after migration. 
2. Improved efficiency: Migration can improve the efficiency of working with the database. 
3. Data improvement: Migration involves analyzing data to enhance its quality by removing superfluous or invalid entries and correcting any corrupted information.

Example: Moving from a relational database management system (RDBMS) to a non-relational one (such as MongoDB). 

How to Test Database Migration? 

Implementing the testing involves establishing a step-by-step procedure to verify the migration's success. This includes validating schema conversions, data completeness, data integrity, data format retention, and ensuring that stored procedures and triggers function correctly post-migration. 

• Database Migration Test Plan: Begin with a comprehensive test plan tailored specifically for the migration process. This plan should define the objectives, scope, resource allocation, timeline, and deliverables. It must also include risk assessment and contingency plans for potential migration challenges. 
• Database Migration Testing Checklist: A meticulously crafted checklist is vital to ensure no aspect of the migration is overlooked. This checklist should cover pre-migration, during-migration, and post-migration testing phases, encompassing data integrity, data transformation rules, application dependencies, and performance benchmarks. 
• Database Migration Testing Strategy: The testing strategy should encompass the overall approach to testing, including the methodologies to be used (such as white box, black box, or gray box testing), the type of tests to be conducted (like unit, system, and acceptance tests), and the criteria for test pass or fail outcomes.  
• Test Cases for Database Migration: Develop specific test cases that will validate every critical aspect of the database migration. These test cases should cover the validation of data mapping, successful data loading, and the application's functionality after the migration. 

This section should serve as a blueprint for ensuring a seamless and secure transition during database migrations, providing a structured and systematic approach to testing and validating each stage of the migration process. 

Migration to a New Server 

Server migration is a migration in which data is moved from one physical server to another. This process includes not only the data itself but also the server configuration transferred to the new object. This approach achieves several important advantages depending on the new server: 

1. Advanced configurations: A new server enables enhanced outcomes, including cost optimization, improved performance, and the availability of essential features that the old one lacked. 
2. Improved reliability: A new server usually means improved reliability and stability, helping to avoid crashes and downtime.
3. Greater clarity in logs: A new server can provide more detail, making it easier to analyze request responses between system components and identify problems. 
4. Increased performance: The migration process, combined with the adoption of more powerful hardware, leads to a notable increase in system performance.

Example: Moving from a Windows operating system to a mainframe server or from an HP Box to an IBM Box. 

These main types of data migration reflect the important role of information movement processes in supporting the effective functioning and development of information systems and computer environments. 

Why Do You Need Data Migration Testing?

Program migration to a new system can occur for various reasons, such as system consolidation, outdated technology, optimization, or other circumstances. It is indisputable that no matter how professional the developers are, this process is challenging and full of potential problems. Testing of the migration process is critical to ensure the following: 

When to Implement Data Migration Testing? 

Data migration testing should be carried out at the following stages: 

1. Pre-migration testing:Check the status of the old system and prepare it for migration. 
2. Migration testing: Evaluation of the data migration process and its integrity. 
3. Post-migration testing: Check the new system’s operation after the migration.

It is also important to consider these types of testing when testing data migration:

Backward compatibility check: 

• Confidence in the correct data transfer and settings from the old system to the new one. 
• Check the smooth migration of the application of the previous two versions without any problems.

Rollback testing:

• Creation of scenarios simulating possible errors and inconsistencies during data migration. 
• Checking the correctness and effectiveness of the rollback mechanism after the occurrence of errors. 
• Fixing the time required to restore the system to the previous version and marking it in the test results for further analysis. 
• Run automated regression testing to ensure that the migration has not adversely affected the system and that the rollback works successfully.

Before starting data migration testing, it is important to study the system changes and migration strategy in detail and how to write test cases for data migration effectively. 

Different Phases of Migration Testing 

Migration testing is a critical element of successful data migration and includes three main phases: 

Pre-Migration Testing 

At this stage, the initial state of the old system and its preparation for migration are studied. The main tasks include: 

• Checking data for errors and inaccuracies. 
• Checking the availability of necessary backup copies and recovery tools. 
• Development of data migration test cases.

Migration Testing 

This phase evaluates the quality and correctness of the data transfer process. Important aspects include: 

• Tracking the migration process and identifying possible problems. 
• Data integrity checks after migration. 
• Testing the functionality of the new system for defects.

Post-Migration Testing 

At the final stage, the stability and performance of the new system are checked after the migration is completed. This includes the following tasks: 

• Checking whether the new system works correctly in real production conditions. 
• Identification and correction of possible defects that may occur after migration. 
• Tracking the performance and speed of the new system.

Migration testing aims to ensure smooth and successful data migration, reducing risks and minimizing possible negative business consequences. 

Data Migration Test Strategy 

Creating an effective testing strategy for data migration is a critical task aimed at minimizing risks and ensuring a successful migration. Here are the critical steps of this strategy: 

Challenges in Data Migration Testing 

Problems in data migration testing require special attention and an effective solution. Below are some of the main issues that arise during this process:

Data quality 

One of the main problems is poor data quality, which can result from improper collection, processing, and storage of information. This can include incorrect records, duplication, archaic data formats, and sometimes even loss of data integrity during transmission or storage. To solve this problem, you must use data validation and cleaning methods before migration and develop strategies to improve data quality in the new system. 

Data inconsistency 

During the migration, data from the old system may not be appropriate for the new system. This may be due to changes in the database structure, data types, or information processing scheme. To overcome this problem, conducting a detailed data structure analysis and developing a transformation map must ensure that the data meets the new requirements. 

Data loss 

The risk of data loss during migration is always present, especially for mandatory fields. In case of loss of this data, there may be a significant problem as it cannot be recovered. To prevent this, it is important to ensure data is backed up before migration and carefully monitor the process to avoid loss. 

Data volume 

The large amount of data that needs to be migrated can lead to significant challenges. For example, there may be hundreds of thousands of subscribers in the telecommunications industry, each with a large amount of data. You can use specialized tools and develop migration optimization strategies to automate this process. 

Simulation of the environment in real-time 

Simulating a real environment during testing is critical. Given actual data and a real system, testers can spot problems that might go unnoticed in an isolated lab environment. This requires access to data from real sources, replicating the environment, and identifying the volume of data to migrate. 

Modeling the amount of data 

Thorough analysis and modeling of the volume of data is a crucial stage in migration planning. Given the specificity of the data, teams must develop a strategy for processing and moving the volume of information, which can be significant. Automation and extrapolation are helpful tools for managing large volumes of data during migration. 

The ultimate goal of data migration testing is to ensure that no data is lost during the migration and that the product runs smoothly, which requires detailed planning, analysis, and testing. 

Tips for Minimizing Risks During Data Migration

Data migration is a technically demanding process, and the success of this task can significantly affect the functionality of the new system. These tips are helpful not only for testers involved in this process but, most importantly, for developers. Here are detailed tips to help you improve the testing process:  

Data standardization before migration 

• Before migrating, determine the data formats and their structure in legacy systems. 
• Make sure the data meets the modern standards used in the new system.

Example: If you have a database with dates in different formats (e.g., MM/DD/YYYY and DD-MM-YYYY), convert them to a single standard to avoid migration conflicts. 

Improving data quality 

• Use data cleansing and validation tools to detect and correct errors. 
• Develop a policy for handling duplicates and resolving data conflicts. 
• Perform a database audit and remove redundant or unnecessary data. 
• Plan the transfer of data to the new system in such a way as to avoid contamination of the new database with redundant records.

Example: If you are migrating a customer database, check if inactive subscribers can be deleted, merge all duplicates and fix all corrupted data. 

Rechecking restrictions and procedures

• Verify that all database constraints (e.g., keys, uniqueness constraints) meet the new system's requirements. 
• Validate complex queries and create test scripts to validate them in a new environment. 

Example: If your old system uses uniqueness constraints to identify users, ensure uniqueness is preserved during the migration.

Choosing the right data migration testing tools 

Consider test automation tools that can help you perform data validation on your new system.

Example: Using automated test scripts allow to speed up testing and free ap tester’s time. 

Data quality is a critical factor in completing data migration testing. So, following these tips, you will achieve the desired result. 

Conclusions 

In this article, we have delved into the core essence of data migration, described the types of this process, and emphasized the importance of testing at all stages of migration. We also discussed when data migration becomes necessary and highlighted the key steps involved in the process. You have received a list of difficulties that may arise during data migration and tips for further solving and avoiding them. May this newfound knowledge contribute to the seamless execution of data migration tasks in your projects! You can also read about our fintech testing services to gain insights into how we ensure the quality, security, and compliance of financial technology applications and systems. Reach out to us today to discuss your project requirements and let our expert team ensure the quality and security of your software products.