For Life Science Companies
In our previous article we outlined the nature of risks faced by regulated companies undertaking data migrations. We also gave some ideas on how that risk needs to be addressed and mitigated, primarily through the implementation of an appropriate and effective testing strategy. This article aims to continue that discussion and elaborate on what makes an appropriate and effective testing strategy for your particular environment.
This article also introduces a broad set of data migration testing techniques beginning with pre-migration testing. These techniques are all well established and offer a number of benefits. After a review of these techniques, a set of "top ten" recommendations are provided for the design of an appropriate migration testing strategy.
Traditionally, migrations have been tested using some form of post-migration testing, often limited to sampling. While this certainly has a role for some migrations, it starts relatively late in the overall process, is labor intensive, and misses many data-level errors.
Traditionally, migrations have been tested using some form of post-migration testing, often limited to sampling. While this certainly has a role for some migrations, it starts relatively late in the overall process, is labor intensive, and misses many data-level errors. These limitations come into play particularly in highly regulated companies where the required margins of error are not feasible.
The concept of pre-migration testing is not often, if ever, covered during migration planning. There is not a strong awareness among migrations professionals regarding comprehensive pre-migration testing and the value it can add to a migration and particularly those migrations that are considered complex.
Pre-migration testing takes place prior to the actual migration of any data, including test migrations. If done properly, pre-migration testing will assist with:
Formal Design Review
Conduct a formal design review of the migration specification when the pre-migration testing is near complete, or during the earliest stages of the migration tool configuration. The specification should include a definition of the source systems, the source system's data sets and queries, the mappings between the source system fields and the destination system, number of source records, number of source systems records created per unit time (to be used to define the migration timing and downtime), identification of supplementary sources, data cleansing requirements, performance requirements, and testing requirements. The formal design review should include representatives from the appropriate user communities, IT and management. The outcome of a formal design review should include a list of open issues, the means to close each issue and approve the migration specification and a process to keep the specification in sync with the migration tool configuration (which seems to continuously change until the production migration).
Once a migration is done, additional end-to-end testing can be executed. Expect a significant sum of errors to be identified during the initial test runs although it will be minimized if sufficient pre-migration testing is well executed. Post-migration is typically performed in a test environment and includes:
User Acceptance Testing
Functional subtleties related to the co-mingling of migrated data and data created in the destination system may be difficult to identify early on in the migration process. User acceptance testing provides an opportunity for the user community to interact with legacy data in the destination system prior to production release, and most often, this is the first such opportunity for the users. Attention should be given to reporting, downstream feeds, and other system processes that rely on migrated data.
All of the testing completed prior to the production migration does not guarantee that the production process will be completed without error. Challenges seen at this point include procedural errors, and at times, production system configuration errors. If an automated testing tool has been used for post migration testing of data and content, executing another testing run is straightforward and recommended. If an automated approach had not been used, some level of sampling or summary verification is still recommended.
Recommendations for the Design of Migration Testing Strategies
In the context of data and content migrations, business and compliance risks are a direct result of migration error. A thorough testing strategy minimizes the likelihood of data and content migration errors. The list below provides a set of recommendations to define such a testing strategy for a specific system:
If you are going to select the testing strategy that is right for you, it is important to understand that the various options that are available do extend beyond the traditional sampling approach. Evaluate the potential that pre-migration testing could play in your project, understand the efficiency and cost implications of sampling vs. automated testing, and don't underestimate the impact that an effective design review and user testing can have on a migration project. Doing so will not only increase the likelihood for your migration's success, it will also save time and money along the way.
David Katzoff has, over the past 20 years, architected and developed technology that has been used in some of the largest document migration and consolidation projects undertaken in the life sciences arena. Today David is a highly valued resource in many of the largest life sciences companies in the world and is responsible for designing and implementing migration strategies in critical document management environments.
David Katzoff is managing director of product development and chief architect for Valiance. He brings more than twenty years of software applications engineering, technical training, project management and compliant business solutions design experience to this role. Much of it concentrated in enterprise-class content management for GxP data, content and processes.
David has spent much of the last seven years focusing on product and strategy for content management migrations. His efforts have been leveraged from some of the largest systems consolidation efforts completed to date as such clients as Amgen, Pfizer, Wyeth, Celgene, Bayer-Schering, Covidien, BMW and others.
David earned a Bachelor of Science in Electrical Engineering from the University of Rochester in Rochester, New York, and is a member of the Phi Beta Kappa Society.