Data migration is imperative for IT operations in virtually every organization at some point and there are many reasons why it may occur.
Whether it’s for the relocation of a data center, the unification of storage or servers, the replacement of a server, a storage upgrade or performance-related maintenance, data migration not only keeps operations tidy but also helps keep businesses up to date with new technological advancements.
When it comes to undertaking data migration there are some essential elements that need to be considered. Here we investigate some of these elements.
What is Data Migration?
The definition of data migration is really quite simple. It’s essentially the process of moving data from:
- one location to another
- one format to another
- one platform to another
It’s usually initiated due to the implementation of a new system or location for the data. Recently the move from on-premises infrastructure and applications to cloud-based storage has been responsible for data migrations within many organizations.
The Process
Depending on the complexity of the data there are usually five keys steps to the data migration process.
- design – identifying existing data sources and deciding on how the data will be converted depending on the requirements of the new system
- extract – export the data from the existing source
- cleanse – assess the quality of the data and identify any issues or inaccurate data
- load – import the cleansed data to the new system
- verify – test the data and validate upload success
The Essential Elements
Risk Management
Risk management is an extremely important part of the data migration process. It’s vital that all the risks are managed efficiently because if not you lose risking the data. With the increasing amount of data being stored in data storage structures, the data migration process has become more complex and thus makes the migration of data a much riskier.
Challenges that you may face when undertaking data migration are things such as data loss, data corruption, interference, extended downtime risk. These are all things that can be evaded with effective risk management.
Assessing Data Quality
Assessing the quality of your data will eliminate any old or duplicate content that will no longer be relevant to current and future business processes.
This assessment process makes sure that the information being transferred is high quality and that the quality information remains accessible to both current and future users.
Change Management
A big change within an organization such as a large data migration project not only requires careful consideration of the data, but also of the customers, vendors, partners, and everyone who will be using the new system. Change management ensures everyone involved is guided through the process. Contact and communication are key when it comes to managing change within a business.
Data Complexity
Before commencing the data migration process it’s important that you establish the complexity of the data. The intricacy of data strings and current data classification systems can significantly influence how a business approaches the data migration process. Evaluating the data includes analyzing what kind of resources the organization possesses, the type of storage where these data resources are stored, and how complex is the data that is stored.
