Explanation
The success criteria for data migration and the manual and automated data validation approaches are two key areas of UC's data migration test plan that should be included. The success criteria define the expected outcomes and quality standards for the data migration process. The data validation approaches ensure that the data is accurate, complete, and consistent after the migration.

Explanation
These are the correct answers because the project steering committee plays a role in approving deviations from the chosen methodology, when required to address project issues, and setting the criteria for selecting agile or waterfall methodology to be used on internal projects. The steering committee does not design a methodology, but rather chooses one from the existing ones. The steering committee does not enforce that corporate project stage gates are part of the chosen methodology but rather ensures that the chosen methodology aligns with the corporate project stage gates.

Explanation
Implementing a Hub-and-Spoke multi-org strategy by consolidating customer data in a single org, which will be the master of customer data, and using integration strategies to let the LOBs orgs read and write from it is one of the options an architect can recommend to accomplish the customer 360-degree view. This way, the architect can ensure that there is a single source of truth for the customer data, and that the data is consistent and synchronized across the different orgs. Implementing a Single Package multi-org strategy by developing and deploying to all orgs a managed package which reads and consolidates customer 360-degree view from the different orgs is another option an architect can recommend, as it allows the architect to create a reusable and scalable solution that can provide a unified view of the customer data from multiple sources.
Implementing a Complete Graph multi-org strategy or migrating from multi-org to single-org strategy are not feasible or optimal options, as they can introduce complexity, cost, or risk to the architecture.

Explanation
C and D are the best approaches to develop customizations once and make them available in both orgs, as they use packages that can be installed and updated in multiple orgs. A is not a good approach, as it does not allow for versioning and dependency management of the customizations. B is not a good approach, as it does not support deploying metadata components between orgs.

Explanation
Sandboxes should be refreshed based on the needs of the project and the development lifecycle. Production is the only pristine environment, so it is a good practice to refresh sandboxes from production regularly to ensure data and metadata consistency. Integration sandboxes should be refreshed frequently, not rarely, to avoid conflicts and errors when integrating code from multiple developers. Development environments should generally be refreshed after each working feature has been successfully migrated, to avoid accumulating unnecessary changes and to start fresh for the next feature.