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Last Updated Date Mar 26, 2024 |


Following a proven implementation methodology ensures the success of the project and maximizes available resources. As the build phase begins, start by reviewing the project scope and plan developed during the planning phase. You may implement working with your own IT team, with a team of consultants or a blend of both.

Implementation begins with aligning the source attributes to the 360 solution data model. An accelerator data model can be used and extended, such as Customer 360 or Supplier 360. Otherwise, a new data model can be constructed de novo following best practices. Integration mapping from source to target then can begin.

The data profiling assessment and feedback from the planning phase will be used during the implementation to:

  • Develop business rules/data validations
  • Determine derivations of conformed attributes (record types or new fields)
  • Determine configurations for matching and survivorship

Match tuning may be another activity that will iterate the data through match rule configurations, with each iteration’s analysis reviewed by Subject Matter Experts and business stakeholders.

The data stewardship requirements will be implemented by configuring the User Interface, configuring user roles for data authorizations, and developing BPM workflows to manage and audit data authorship.

Establishing governance policies is critical so that data is used in accordance with corporate and regulatory data privacy mandates. Finally, the solution can be put into operations, and the IT team typically takes over the primary responsibility.

Testing and tuning is imperative. Key stakeholders should be involved in acceptance testing to ensure that business objectives are met. Establish the overall test strategy, including the user acceptance testing plan. Determine the performance benchmarks, and test thoroughly to ensure that these will be reached in a production environment. User training is also critical to facilitate acceptance and adoption.

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