Data migration is often necessary to keep up with technological advancements and industry standards, but it requires great effort.
Data from various storage areas — both onsite and in the cloud — must be evaluated, analyzed, cleaned up and organized before it can be combined and reconciled.
One of the most important practices in a successful data migration is to evaluate what knowledge resources the organization possesses, where and how they are stored and how complex the data itself is. The complexity of data strings, and the complexity of the current data classification systems, may largely influence the direction your organization takes as you move forward with the migration and integration process.
Before your organization can move forward after evaluating the complexity of your data, it is a good idea to make sure you have a comprehensive set of data standards in place. Since data is so integral to business processes, yet so hard to pin down as it is always changing, establishing a set of rules and standards before conducting the migration will help ensure more successful use of data in the future.
What to keep in mind when data migration is the mission?
- Define Current and Future Business Rules: In addition to establishing data standards, it’s also important to define the current and future business rules that will apply to your use of data. These rules should ensure compliance and compatibility with business and validation rules, not only for the current data migration but for all future policy requirements and regulations.
- Establish Information Governance Roles and Responsibilities: Establishing information governance for your new data system starts by figuring out who will have final say, who manages the information and who is responsible for supporting data quality, access and usage throughout the organization. The entire company will be affected by the data migration—so be careful when choosing the team members and managers to handle these important tasks and technologies.
- Perform Data Quality Assessment: Of course, a data migration entails much more than moving data from point A to point B. Before any data can be transferred from one system to another, it must first be assessed to ensure a high level of quality once the new database becomes available to current and future users. The data quality assessment process should involve removal of duplicate content and all files that are not relevant to current or future business processes, and, if applicable, creation of a master data file.
- Gather Migration Requirements: Gathering migration requirements should be fairly straightforward once data complexity and quality have been established, rules and standards have been defined, and an information governance structure has been put in place. Make sure to carefully analyze how and where your organization’s data will be used, who will use it and how this might change in the future.
- Risk Management: Risk management is integral to the data management process, so it makes sense that it should be an integral component of the migration process as well. Make sure that all data will be easily accessible for any potential audits and that all information systems comply with government, industrywide and companywide regulations.
- Change Management: This might just be the most important practice in a successful data migration. Managing change in an organizational setting requires careful consideration of the users, customers, vendors and partners that will be participating in the new system. Change management is all about making it a successful transition for everyone involved, and keeping everyone on board for the long haul.
Moving Migration Forward
Migration testing should be performed long before the migration is complete. Testing should be performed throughout the migration process to catch mistakes and issues while they’re still fixable. And once the migration is complete, your team of data experts should perform a more extensive set of tests to evaluate and approve the new system before people start using it companywide.