Data Migration Best Practices : Aalpha
Data migration can be simply described as moving data from one point to another. It involves the extraction of the data, which then undergoes a series of preparations before being loaded to the intended destination. It is, however, a complex process that often requires multiple systems and is time-consuming.
For an effective and seamless migration, a sound strategy is important to save both time and even money. Luckily, there are tools, strategies, techniques, and best practices to assist in making the process more successful.
Considerations to make during data migration
- Data integrity
- User experience and impact
- Business Impact
- Potential downtime
- Data assessment
- Data quality
Types of data migration
Data can be migrated in wholesale meaning the entire migration is carried out at once or it can also be done in phases. Below are 3 types of migration namely:
This involves transferring data from one storage to another. This can be from one on-premise location to another or from an on-premise location to the cloud. It seems a straightforward process but requires careful planning and execution just like the other data migration processes.
It is more involving than storage migration as it involves moving a whole database of files from one location to another. The large amount of differently formatted files involved makes it more complex. The databases need to be backed up first before being migrated.
This migration involves moving a software application from one place to another. Often it involves the combination of both storage and database migration. It is advisable to involve the application provider in the process to ensure the process is more effective.
Key components of a data migration strategy
A data migration strategy is paramount before the process of data migration starts. Some of the components to include in your strategy should be:
This will involve evaluating and looking at all scenarios and the effects the process will have on the business.
Should have a call-to-action plan where everybody is to be updated on their roles and a commencement date communicated.
Have a feel of what the whole landscape of your whole ecosystem will look like before the migration.
Come up with the migration design of what will move and to where.
Here the code for the software logic to facilitate automation of the migration will be built and tested.
Decommissioning the old systems will be the final process. A strategy to carry it out securely will also be important.
Data migration challenges
Poor organizational structures and processes can create bottlenecks for a seamless migration process. Broken files or data structures have to be dealt with in advance.
Lack of a backup plan in case of an unseen mishap can lead to huge losses and a lot of time wastage. Potential mishaps should be anticipated and possible backup plans come up with.
Automation and the use of complimentary software help to speed up the process. Failure to use automation will result in a loss of time.
Data migration tools
Some of the data migration tools you can use to facilitate ease of data migration are:
This one will help you move large data amounts between storage devices, systems, and software platforms. It can also help in cloud migrations by helping you in separating the data you need to migrate to the one that stays.
This tool provides one with visibility on the data including who has access to it. The detailed visualizations help reduce risk during the migration process.
Factors to consider while choosing a data migrating tool
Data migration best practices
To make your data transfer successful here are some best practices to apply:
Ensure you have a backup of your data before migrating. This is in case of a problem like missing, corrupted or incomplete files, you can easily get the data from the backup.
This will at the end help in deciding the best approach to take. Verifying will involve identifying the data to be transferred, where it is stored and the format it will take after the migration.
Verifying quality will help eliminate duplicate data and also help separate good data from bad data by implementing firewalls.
When you put standards on the data and make it clear how complex it is, unexpected issues can be avoided later in the process.
Do this by coming up with data migration policies that ought to be in line with other validation and business rules. This helps to guarantee regulatory compliance. Come up with the rules before the migration then evaluate them after the process ends.
There are two strategies one can choose from:
1.Big bang strategy
In this migration strategy, full data transfer is done within a specific window of time, say for example 24hrs. Live systems will experience downtime but the data will go through ETL processing to the new database
2.Trickle migration strategy
Here migration is done in phases. The old and new systems run in parallel hence eliminating downtime and interruptions.
Since the migration involves a team. Communicating the process is a best practice. Every team member has to know their roles and responsibilities.
The right choice of migration tools will make the migration effective and faster.
This will involve trying to map out areas where problems might arise and coming up with solutions on how they will be tackled if need be, or even prevent them from arising in the first place.
Data migration is something that as a growing company you cannot avoid. It is complex but it can be done seamlessly by implementing migration best practices. With the right tools which are readily available and a good strategy your migration will be successful.
Finally, to know about data migration best practices, connect with database development company!
Originally published at https://www.aalpha.net on August 8, 2022.