Analyze the information environment, identifying where and how the data will be leveraged—and who will actually use the data—while thoroughly assessing the information environment. Determine how data could be used differently tomorrow, in analytics, for example.
2Take an As-is Assessment Before Moving Data
Data is dynamic—changing all the time—and it is tied directly to business processes and uses. Establish data standards and define business rules for migration and ongoing data use with owners and subject matter experts.
3Account for Data Quality, Especially in Legacy Systems
Migrating involves more than moving data. Perform a thorough quality assessment to ensure standardization that supports new uses and users today and tomorrow. This should include deduplication, removal of other non-relevant files and possibly a master data management-type process.
4Validate and Redefine Business Rules
Data must comply, and be compatible with, current business and validation rules. Define rules for one-time data conversion and migration, while designing them for adaptability to future regulatory and policy requirements.
5Ensure that Governance Rules are Established Early and Define Who Is Responsible for the Data
After determining who owns and has final say-so over information, establish strategic and operational data “stewards” aligned to “C-level” sponsors for continuing guidance on scope, direction and support.
6Take Responsibility for Your Data Migration
The company, not only the systems integrator, must live with the results of data migration. Based on aptitude and attitude, find the right people to manage processes and technology correctly.
7Dont Rely 100 Percent on the Tool
Tools are only that. Tailor fields and business rules to your company’s needs with internal experts leveraging tools while obtaining the right information to complete data migration.
8Validate Throughout the Process
Don’t wait until migration is completed to look for problems. Fixing mistakes after the fact are exorbitantly expensive. Carefully choose testing and evaluation personnel based on critical participant and data consumer needs.
9Engage the Business
As migration takes place and nears completion, be ever mindful of which users, customers and business partners have to live with the results. Choose carefully and accurately who makes the final decision whether the migration is “good enough.”
10Measure Impact
Take your time in determining who should be involved in testing, evaluation and final sign-off of the data migration, while being keenly aware of the data’s ultimate consumer. After “go-live,” focus on operational business processes to maintain relevant, high-quality data.
AI 3D Generators are powerful tools for many different industries. Discover the best AI 3D Generators, and learn which is best for your specific use case.
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