Managing the Migration Migraine

Author by Dan Vogt

Migration – The movement from one part of something to another.

In IT, there are five main types of migration. 

  1. Storage migration – This involves moving physical blocks of data from one type of hardware to another
  2. Database Migration – This kind of migration is used for moving an entire database from one vendor to another, or to upgrade the software currently being used for the database
  3. Application Migration – When an application vendor needs to be changed, it will result in the need for a substantial transformation, since almost every application operates on a specific data model
  4. Business Process Migration – This relates directly to a company’s business practices, often orchestrated by business management tools that will need to be replaced or updated in the even of a merger or acquisition.  Movement of data can be required to be moved from one database or application to another.
  5. Cloud Migration – This is the process of moving data, applications, or other business elements from an organization’s on-site computers to the cloud, or even from one cloud environment to another.

No matter the type of migration that is being performed, there are some general guidelines that should be followed to help ensure all boxes are checked and you are as prepared as possible to handle the task of migrating data.  It can be a very daunting task and hopefully the outline formed below will help to shed some clarity on what to expect.

  1. Evaluate the complexity of the data – Probably the single most important part.  Evaluation is key to understanding and identifying what data is being migrated, where it lives, and what format should it be in post-migration.  During this phase potential risks can be outlined and planned for prior to the move.  The pre-planning process will help to lessen the chance for critical errors being made during the migration process.
  2.  Establish Data Standards – Establishing a set of rules and standards before conducting the migration can help ensure a more successful use of data in the future.
  3. Define Current/Future Business Rules – These rules should ensure compliance and compatibility with business validation rules not only for current data but for all future policy requirements.Image result for technology migration diagram
  4. Establish Roles and Responsibilities – The establishment of who will have the final say, who manages the information, and who is responsible for supporting data quality, access and usage, is a very important step. 
  5. Perform Data Quality Assessment - 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.
  6. Gather Migration Requirements - 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.
  7. Assess and Identify the Proper Tool - The proper tool will be one that enables customized fields, aligns with your organization’s needs and standards and comes highly recommended by the experts.
  8. Risk Management - 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.
  9. 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.

By using the steps outlined above, you’ll be able to successfully move your data from source to target system. Just remember to backup all data before beginning your data migration. In the event an unforeseen problem occurs, you’ll be able to undo the damage and recover the important data your business relies on.