Modern-day businesses need modern-day data operation solutions. A company that excels at its core competence and yet fails to manage its data well, will underperform in the market because data is the basic infrastructural unit of every business now.
Data migration is one such process that companies need to strategize for effective data operations within the company.
Data migration refers to transferring data from one system to the other. This might sound as simple as watching the old Windows illustrate on-loop file transfer animation.
But this is a complex and crucial process.
Companies undergo data migration continuously and for various reasons. Sometimes, it is a change of data warehouse, merging new data from different sources, system updates, and hardware updates.
An un-strategized data migration process can come with consequences like data loss, inaccurate or repetitive data migration, and many other complications that can take a toll on the company’s data operations.
So, here is the best methodology for successful data migration:
Assess the source and target systems
If there is one rookie mistake that most companies make before setting up their data migration process, it is to not assess the quality and compatibility of source and target systems.
Too many times, companies lose important data in the migration process before the migrated data is not supported by the target system.
Before putting the process into action, it helps to evaluate the data and detect any inaccurate, incomplete, or problematic data.
So as step one, assess the source and target system’s compatibility and quality of data to migrate.
Once the major barrier is out of the way and you have sorted your systems and data, it is time to ponder over the methodology or approach that works best for you.
1. The ‘go once and go big’ data migration method
If one can afford to do this, this is highly recommended because it’s not only cheaper but is much less complicated. This is a method where you completely turn off the system operations and make it unacceptable to any user and just migrate the data all at once, and then proceed with the new system.
The only problem however is during this process the systems are practically going through downtime and might take away from the productivity or pause vital operations in the company.
So usually, companies carry out this type of migration during public holidays to avoid losses from downtime.
2. The ‘phased out’ data migration approach
This is a method where data migration is broken down into parts to run for several days or weeks based on the weight of the data.
This method is recommended for companies that cannot afford to shut their operation down for a while or for data migration processes that are estimated to take a longer time to migrate.
This process will need a lot more strategizing than the previous approach, given that the migration takes place alongside the regular operations.
The size of the data needs to be accurately estimated along with the time in transfer to get the time taken to migrate it. The target system, since it is functioning and carries its data, needs enough space to accommodate the data in migration.
Once you have narrowed down the methodology, it is important to remember a couple of things to ensure smooth data migration.
Always start the process with professional assistance, especially if the data is sensitive and critical or bigger. An unassisted data process is prone to going astray with data loss and malfunction.
Always go through a dedicated data cleaning before migration, because it does not do to transfer inaccurate, unnecessary space-eating, and inferior quality data to the new system to inherit all the same problems to the system.
