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Monday, September 10, 2012
Data Migration Project Planning: 10 Best Practices to Implement
Data integration involves combining and reconciling data residing in different storage areas, which could be on site or in the cloud, and giving users a unified view of this data. This process becomes a significant undertaking in a variety of situations, which include both commercial (when two similar companies need to merge their databases) and scientific (combining research results from different bioinformatics repositories, for example) domains. Data integration issues are increasing in frequency as the volume, the number of file formats and the need to share existing data explodes. It has become the focus of extensive theoretical work and numerous open problems remain unsolved. In management circles, people frequently refer to data integration as Enterprise Information Integration. Sometimes, it's difficult to know where to start a data migration project, because in any enterprise, there are many data stores and agendas. To try to shed some light on the problems, eWEEK and integration expert Arvind Singh, CEO of data management consultancy Utopia Inc., have put together some best practices to think about before starting an enterprise data migration project.
Determine the Purpose of Your Data
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.
Take 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.
Account 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.
Validate 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.
Ensure 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.
Take 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.
Don't 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.
Validate 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.
Engage 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."
Measure 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.
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