For example, if we have a field called amount in the source database and it is getting migrated to base amount in target application. In the source database, most information can be fetched by putting simple joins between 2 or 3 tables, but in target database, this was not the case. Sampling is not defect proof system as it selects small random records. There can be two folded reconciliation, Count Reconciliation and Key financial column reconciliation. In the source application, this particular field deals with the Indian rupee but at target side, the base amount field considers US dollars. The member ID generated in each source system was unique on its own but only within the source system and our application was configured separately for each server and there were no sync jobs to sync the data between these two servers. In such situations, interference risk arises. Challenges faced in data migration testing, Article Copyright 2016 by ErGauravSharma, AgarwalPriyanka, Last Visit: 12-Nov-20 9:58 Last Update: 12-Nov-20 9:58. Nice article about data migration testing. Due to data migration, anomalies or redundant or duplicated data or presence of non-meaningful data are related to data integrity issues. Use Ctrl+Left/Right to switch messages, Ctrl+Up/Down to switch threads, Ctrl+Shift+Left/Right to switch pages. One way is to plan multiple mock run involving all stakeholders and also planning dry run in pre-production environment involving all stakeholders. We picked out the records which were having the IDs overlapped and appended source system ID in them. Ensure there are backup assets and that they’ve been tested before you continue. For example, the source table columns were directly mapped to the primary keys from master tables with common data types such as. When a business process changes due merger, Acquisition, business optimization takes places, Depend upon nature of business process changes, data need to be moved between various storage system or application or location. Sometimes the source application field’s deal with decimal points up to 2 but target application does not consider any such constraints. Complete data set validation: It is ideal validation method that we should strive in migration testing. 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. When a data center is moved from one location to other location, we need to migrate data from legacy data center database to target data center database. Other such example is the source application fields deal with decimal points up to 2 but target application does not consider any such constraints. Challenges faced in this testing are mainly with data. Save my name, email, and website in this browser for the next time I comment. B-88, First Floor, Sector-64, The first and biggest challenge was Data Mapping. Cost involved rectifying data loss and business cost involved due to poor data adds up as to financial and reputation risk. If your framework experiences the procedure and outcasts as a perfect work of art, at that point you will have an application that has various databases at the backend to support the huge data. We had this opportunity to work on our very first database migration testing project a few months ago. Regardless of which implementation technique you pursue, there are some prescribed best practices to keep in mind: Back up the data before executing. Data in the source table may be present as a character, but in the target table the mapped column is an integer. by TestOrigen | Aug 30, 2019 | Big Data and Data Analytics, Software Testing | 0 comments. Key financial column reconciliation is recording summation of all key financial columns ex closing balance, available balance etc. Your email address will not be published. Format and content of data in legacy system and target system is different in comparison due to migration process then it is called corrupted data. When two different database vendors are involved, such comparison is impossible, to overcome instance need to create in either one database with both legacy and target system data. Comparing number of records in legacy system and target system will give fair assessment about data loss in migration. Any kind of data loss or corruption during the process of data migration can prove to be catastrophic for an organization. During the testing, we got this chance to articulate our SQL query writing skills. It requires particular abilities, skill, tools, and assets. This all happened because the Member ID which was unique within the system was overlapping with the Member ID of the other source system. In Data Centre Migration projects, the aim of testing is not to find defects in the software but to ensure that applications are functioning ‘as is’ and there is no impact to the business. Sample data validation: It involves in random selection of record from legacy system and comparing same with target system. Therefore, it’s extremely important to develop a fit for purpose test approach based on the following principles: Some records were having check-in counts more than the expected and some of them were not having a single check-in record. People often use term "Data conversion" as a synonym of "Data Migration", but we should know that conversion is an integral part of Migration. Want to Choose Best Database Software? Only advantage is it select more records and expecting more data coverage based on higher probability. Test Cases versus Test Scripts: Difference you want to know, End To End Software Testing Solutions proliferating business, Inappropriate evaluation of existing data as far as quality, behavior, and nature can end up being a huge pitfall, Data is prone to get debased during migration which may result in a crash of apps/IT frameworks, The incongruity of units for certain fields in the objective and source databases, Loss of data may prompt inaccurate business choices, Extended-term of data migration prompts expanded downtime for the application, Ignorance of interdependence between different objects and fields result in serious mishaps, Data migration may hamper the functionality and security of app and performance of database. Attributable to the criticality of the data and its utilization in business basic leadership, data migration testing turns out to be much significant. If 10 INR (Indian Rupee) is getting migrated to 10 US dollars, it is a mistake because 10 INR can never be considered as 10 US dollars. This was achieved by using the temp tables and full outer join. Noida (UP) – 201301 As these Member IDs were auto-generated at run-time and due to the difference of servers at different locations and no syncing activity going on between them created these kind of records. Important to notice in this scenario is data is not loosed or corrupted, migration is successful yet not useful in term of objective. Additionally, an appropriate analysis of data can add to the quality of the data and data purifying, and inspecting can keep the database spotless just as effective. and comparing between legacy and target system will result in identification of data loss. from the legacy source systems into a new system, known as the target system or the application. Challenges in Data Migration Testing We had this opportunity to work on our very first database migration testing project a few months ago. Difference in the count of rows in source and database was the result set of the above script. As an assembled independent software testing services and pro-QA staffing services organization, TestOrigen gives advanced data migration testing services. when a data is migrated from existing database vendor to other database vendor or existing data base is updated to latest version. We created an initial mapping document by studying the source and target database table structure to start with and got it approved by the concerned team. After having several meetings to discuss the solution for the above issue, the team decided to modify the Role ID and Member ID in the target and source tables by appending the source system id in the Member ID of one of the source system’s records. Data loss is highest risk in data migration. Get in touch with us to explore through your data migration needs successfully. But our target system was a common system having a single server handling the data for each source system in one. During the design and planning stages, and all through maintenance and implementation, test the data migration to ensure you will, in the long run, accomplish the ideal result.
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