data migration testing approach ppt

Execute performance testing and record the execution time of migration process to understand if it is falling within the acceptance criteria. Privacy Policy | Diversity & Inclusion | Modern Slavery Statement 2020, Get the latest news and blogs on the software testing industry, CESA – Cigniti Enterprise Sentiment Analyzer, How software quality assurance helps make technology dependable. Analyze the business requirements and build the end-to-end migration specification, then review and manage it appropriately. They should be notified about the time period of the migration process, and till when the old system will not be in use. A common tactic is to break the data into subsets and build out one category at a time, followed by a test. Contact us to navigate through your data migration needs successfully. Categorize success and failure circumstances and identify application interface requirements. At iCEDQ, we suggest the agile rules based testing approach for all data integration projects. Maintenance of applications / IT systems – technology and hardware upgrades wherein data needs to be migrated from legacy systems to the latest ones. Likewise, changes in target application during data migration makes itself incompatible to the migrated data. Data migrations are usually divided into “extract, transfer and load,” a better approach might be “evaluate, plan, prepare, extract, test, transfer, validate, load, validate.” Connect with us to help you manage your most important asset, data. As of this date, Scribd will manage your SlideShare account and any content you may have on SlideShare, and Scribd's General Terms of Use and Privacy Policy will apply. Listen on the go! The original data and its backup has to be deleted after a successful data migration. QA Challenges in Data Integration Sandesh Gawande. Waters Corporation - Food QC, Safety & Research. Automate data warehouse etl testing and migration testing the agile way Sandesh Gawande. If you continue browsing the site, you agree to the use of cookies on this website. Subsequently, proceed with the data migration again. It advises them to not to raise an incident / service ticket to resolve the issues arising in the existing application, and to not to change the environments or platforms used during migration. Improper assessment of existing data in terms of quality, nature and behavior can turn out to be a huge pitfall, Data is prone to get corrupted during migration which might result into crash of applications / IT systems, Mismatch of units for some fields in the target and source data bases, Loss of data might lead into incorrect business decisions, Extended duration of data migration leads to extended downtime for the application, Ignorance of interdependence between various fields and objects results into serious mishaps, Data migration might hamper stability and functionality of application and performance of data base. We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. Review and inspect the failures of data migration observed during testing. Looks like you’ve clipped this slide to already. Challenges of Data Migration include: A well-defined testing strategy is essential to mitigating the risks involved and delivering a successful data migration. If you wish to opt out, please close your SlideShare account. Automate Data Warehouse, ETL Testing and Migration Testing The Agile Way Data Warehouse, ETL & Migration projects are exposed to huge financial risks due to lack of QA automation. A Complete Guide to Data Migration Testing Success . It requires specialized skills, expertise, tools, and resources. Now customize the name of a clipboard to store your clips. Hence, data is the lifeline for the success of any business. Scope frequently gets refined based upon the limitations exposed through pre and post migration testing. INDIUM SOFTWARE It also captures not only field name mismatches, but also values like time taken to execute each record. This helps in re-starting the tests and reproducing bugs as needed while testing.

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