Our Optim Implementation Methodology
Our Optim Implementation Methodology contains the process we use to implement all IBM Optim Solutions—Data Growth, Test Data Management, and Data Privacy. Clients use these products to assist them in managing data volume growth and data compliance—lowering their IT costs, improving system performance and reducing data compliance risk—as a cornerstone of their enterprise data management strategy.
Our Optim Implementation Methodology imbeds the best practices we have developed from our experience in data archiving, test data management and databases. It follows a multi-stage approach consisting of:
Project Planning
During the Project Planning stage, we plan and launch the project, train our client on the flow of a typical Optim implementation, and install and configure the software. Time properly spent during this stage manifests itself in time savings and risk reduction throughout the project. To ensure that our client receives the full benefit of our onsite presence, we provide a checklist of items to be completed prior to our arrival.
Requirements Analysis
The goal of Requirements Analysis is to determine our client’s data archiving and/or sub-setting requirements in detail, and familiarize the client team with the IBM Optim solution to be implemented. During this stage, we facilitate analysis sessions to determine which critical decisions need to be made regarding the Optim architecture to be used. This includes a walk-through of business application flows, and identification of requirements and best practices to be implemented.
Design & Build
During this stage, we design and build the Optim artifacts to support our client’s data archiving and/or sub-setting requirements. This provides the first opportunity to validate the client’s application data structures and archived data reporting needs, as determined during Requirements Analysis, and to make any required changes to the configuration of the archive/extract definitions. This stage also includes the design of custom extensions, the refinement of the technical architecture design, and the inclusion of data transformation rules (typically used for test data management/data privacy projects).
Test & Validate
During this stage, we first test the solution in a non-production environment to establish the strategy to be used to move the solution to production. We perform both modular and integrated testing, and verify that the proposed solution is ready for production use.
Project Transition
During this stage, we assess production readiness, and finalize the production deployment plan. All the elements of the implementation must come together to transition successfully to actual production. The project team trains IT staff and end users who will use the solution.
At this point, we typically transition the management of the solution to client staff, and we provide support to the team during an initial period, including internal support escalation during production.
