Data Migration Part 3 of 4

Test Scenarios, in general, would be as below:

I)​ If the migration is to the same type of Database, then,

  • Verify if the queries executed in the new database yield same results as in the older one
  • Verify if the number of records in the old database and new database is the same. Here use appropriate automation tool
  • Verify that there are no redundancies and new database works exactly as the older one
  • Verify if the schema, relationships, table structures are unaltered or set back to match the old database image
  • Verify whether the changes made in application updates new database with correct values and type
  • Verify if after the new database connection is provided to all the components of the application. Application, server, interfaces, firewall, network connectivity etc.
  • Verify the query performance (time-taken to execute complex queries) of the new database is not more than earlier performance

Challenges faced in this testing are mainly with data. Below are few in the list:

#1) Data Quality:

We may find that the data used in the legacy application is of poor quality in the new/upgraded application. In such cases, data quality has to be improved to meet business standards.

Factors like assumptions, data conversions after migrations, data entered in the legacy application itself are invalid, poor data analysis etc. leads to poor data quality. This results in high operational costs, increased data integration risks, and deviation from the purpose of business.

#2) Data Mismatch:

Data migrated from the legacy to the new/upgraded application may be found mismatching in the new one. This may be due to the change in data type, format of data storage, the purpose for which the data is being used may be redefined.

This result in huge effort to modify the necessary changes to either correct the mismatched data or accept it and tweak to that purpose.

#3) Data Loss:

Data might be lost while migrating from the legacy to the new/upgraded application. This may be with mandatory fields or non-mandatory fields. If the data lost is for non-mandatory fields, then the record for it will still be valid and can be updated again.

But if the mandatory field’s data is lost, then the record itself becomes void and it cannot be retracted. This will result in huge data loss and should have to be retrieved either from the backup database or audit logs if captured correctly.

#4) Data Volume:

Huge Data that requires a lot of time to migrate within the downtime window of the migration activity. ​E.g:​ Scratch cards in Telecom industry, users on an Intelligent network platform etc., here the challenge is by the time, the legacy data is cleared, a huge new data will be created, which needs to be migrated again. Automation is the solution for huge data migration.

#5) Simulation of a real-time environment (with the actual data):

Simulation of a real-time environment​ ​in the testing lab is another real challenge, where testers get into different kind of issues with the real data and the real system, which is not faced during testing.

So, data sampling, replication of real environment, identification of volume of data involved in migration is quite important while carrying out data Migration Testing.

#6) Simulation of the volume of data:

Teams need to study the data in the live system very carefully and should come up with the typical analysis and sampling of the data.

E.g:​ users with age group below 10 years, 10-30 years etc., As far as possible, data from the live needs to be obtained, if not data creation needs to be done in the testing environment. Automated tools need to be used to create a large volume of data. Extrapolation, wherever applicable can be used, if the volume cannot be simulated.

 

Data Migration Testing Part 1

Database Migration

The following is a four part series of educational material to examine in depth the processes of Data Migration, Testing and Automation that are fundamental for any proper operation to take place. 

Below is a short summary of the content that will be covered in the 4 part series, followed by part 1. 

Reasons and benefits as to why organization will choose Database Migration,

  • Application can have multiple databases at the backend to support huge customer data
  • Data enhancement can be achieved
  • Proper analysis of data will help in improving the data quality
  • Data sampling & data cleansing helps in keeping the database clean and effective
  • To carry out data analytics

Examples of Database Migration:

  • Migration from one RDBMS to another RDBMS
  • Migration from RDBMS to MongoDB
  • Upgrading from Informix HC4 to HC6 or HC7

Testing:

  • Ensuring that the legacy database is not updated during tests after migration.
  • To ensure the mapping at field and table levels do not change.
  • Ensuring data is migrated accurately and completely.
  • Pre-migration and Post-migration testing activities.

Testing Migration in a same type database:

  • Verify if the queries executed in the new database yield same results as in the older one.
  • Verify if the number of records in the old database and new database is the same. 
  • Verify that there are no redundancies and new database works exactly as the older one.
  • Verify if the schema, relationships, table structures are unaltered or set back to match the old database image.
  • Verify whether the changes made in application updates new database with correct values and type.
  • Verify if after the new database connection is provided to all the components of the application (Application, server, interfaces, firewall, network connectivity etc.).
  • Verify the query performance (time-taken to execute complex queries) of the new database is not more than earlier performance.

Automated Testing

  • Understanding the Cost Benefit analysis of Automated Data Migration Testing. 
  • Challenges of managing the data quantity required to be tested.
  • Ensuring the quality of the output. 

Conclusion

Considering the complexity involved in carrying out data Migration Testing, understanding that even missing a small aspect of of verification will lead to potential failure or damage to valuable data. It is very important to carry out careful and thorough examination and analysis of the system before and after migration. Plan and design the effective migration strategy with the robust tools along with skilled teams.

As we know that Migration has a huge impact on quality of the application, a good amount of effort must be put up by the entire team to verify the entire system in all aspects like functionality, performance, security, usability, availability, reliability, compatibility etc., which in turn will ensure successful ‘Migration Testing’.

 

Part 1, Overview of Data Migration Testing:

Data migration is the process of selecting, preparing, extracting, and transforming data and permanently transferring it from one computer storage system to another (Wikipedia, 2019). In many organizations data needs to be migrated for a variety of reasons, ranging from newer servers to better applications. But what does this actually mean? In this paper we will look thoroughly in to the process of data migration, and examine what is needed for a successful operation. Data Migration can be cut down to two major processes, the migration, and testing. From the testing point of view, it all means that the application has to be tested thoroughly end-to-end along with migration from the existing system to the new system successfully. Migration Testing is a verification process of migration of the legacy system to the new system with minimal disruption/downtime, with data integrity and no loss of data, while ensuring that all the specified functional and non-functional aspects of the application are met post-migration.

Data Migration Testing Strategy, is an important piece of the operation as it sets out proper parameters of how and when to evaluate the migration to ensure it is running smoothly throughout  the entire operation. This is to minimize the errors and risks that occur as a result of migration and to perform the migration testing effectively.

Some Important Activities in Testing:

1) Specialized team formation:

Form the testing team with the members having the required knowledge & experience and provide training related to the system that is being migrated.

2) Business risk analysis, possible errors analysis:

Current & ongoing business operations should not be hampered after migration and hence it is important to carry out ‘Business Risk Analysis’ meetings involving the right stakeholders (Test Manager, Business Analyst, Architects, Product Owners, Business Owner etc.,) to identify the risks and the implementable mitigations. The testing should include scenarios to uncover those risks and verify if proper mitigations have been implemented.

Conduct ‘Possible Error Analysis’ using appropriate ‘Error Guessing Approaches’ and then design tests around these errors to unearth them during testing.

3) Migration scope analysis and identification:

Analyze the clear scope of the migration test as when and what needs to be tested.

4) Identify the appropriate Tool for Migration:

While defining the strategy of this testing, automated or manual, identify the tools that are going to be used. E.g: Automated tool to compare source and destination data.

5) Identify the appropriate Test Environment for Migration:

Identify separate environments for Pre and Post Migration environments to carry out any verification that is required as part of testing. Understand and document the technical aspects of the Legacy and New system of Migration, to ensure that the test environment is set up as per that.

6) Migration Test Specification Document and review:

Prepare Migration Test Specification document which clearly describes the test approach, areas of testing, testing methods (automated, manual), testing methodology (black box, white box testing technique), Number of cycles of testing, schedule of testing, approach of creating data and using live data (sensitive info needs to be masked), test environment specification, testers qualification etc., and run a review session with the stakeholders.

7) Production launch of the migrated system:

Analyze and document the to-do list for production migration and publish it well in advance.

 

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Building a data warehouse using SQL Server database on Azure is one of the many use cases that’s gaining traction.

This blog explores and compare some key differences between the 3 options to build data warehouse using SQL Server database on Azure.

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