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Data Migration – 10 Best Practices
- Data migration is a very complex task. Today we present the best practices that will help you to carry out this process properly.
- You will learn what a data migration strategy is, what to include in it and what to keep in mind when planning migration.
- We describe frequent problems that occur after and during migration – this way you will avoid surprises.
- And in addition, you’ll learn how to properly perform the tests after the migration.
Why do businesses perform data migration? For many reasons, for example, to replace servers, to transfer their on-premise IT infrastructure to a cloud computing environment, to update their current database with new data due to a merger or acquisition or to move their data to a new CRM.
According to statistics, between 70-90% of data migration projects fail to meet expectations. This is why it’s crucial to follow some data migration best practices to ensure the process goes smoothly.
What are the data migration best practices?
Here are 10 data migration best practices that will help you turn your data transfer into success.
Back up your data
Sometimes things don’t go according to plan, so before you start to migrate your data from one system to another, make sure you have a data backup to avoid any potential data loss. If problems arise, for instance, your files get corrupted, go missing or are incomplete, you’ll be able to restore your data to its primary state.
Verify data complexity and quality
Another best practice for data migration is verifying data complexity to decide on the best approach to take. Check and assess different forms of organizational data, verify what data you’re going to migrate, where it sits, where and how it’s stored, and the format it’s going to take after the transfer.
Check how clean your current data is, does it require any updating? It’s worth conducting a data quality assessment to detect the quality of legacy data and implement firewalls to separate good data from bad data and eliminate duplicates.
Agree on data standards
As soon as you know how complex the data is you must put some standards in place. Why? To allow yourself to spot any problem areas and to ensure you can avoid unexpected issues occurring at the final stage of the project. Furthermore, data is fluid, it changes continuously, therefore putting standards in place will help you with data consolidation and as a result, ensure more successful data use in the future.
Specify future and current business rules
You have to guarantee regulatory compliance and this means defining current and future business rules for your data migration process. They must be in line with various validation and business rules to enable you to transfer data consistently, and this can only be done through establishing data migration policies.
You might have to come up with a set of rules for your data prior to migration and then re-evaluate these rules and increase their complexity for your data after the migration process ends.
Create a data migration strategy
The next step to successful data migration is agreeing on the strategy. There are two approaches you can take: “big bang” migration or “trickle” migration.
If you select the big bang migration, the entire data transfer is completed within a specific timeframe for example in 24 hours. Live systems are down while data goes through ETL processing and is moved into a new database. It’s quicker but riskier.
The trickle migration splits data migration into stages. Both systems – the new one and the old one run concurrently. This means there is no downtime. While this approach is more complex, it’s safer, as data is migrated continuously.
Communicate your data migration process
The data migration process will most probably require the involvement of multiple teams. Making sure you communicate the process to them is an important data migration best practice. They have to know what’s expected of them. This means you need to assign tasks and responsibilities. List all the tasks and deliverables and assign roles to activities. Verify if you have the right resources to complete each task.
You have to think about:
- who has the final say over the data migration process
- who has the power to decide whether it was successfully completed
- who is responsible for data validation after the migration
If you fail to implement a clear division of tasks and responsibilities then it might lead to organizational chaos and delay your migration process or even lead to failure.
Use the right tools
Can you imagine migrating scripts/data manually? Not the best idea. Using the right tools during data migration will make the process faster and more efficient. You can use the tools for data profiling, discovery, data quality verification and for testing.
Consider choosing the right migration tools as one of the key components of your planning process. Your choice should be based on the organization’s use case and business requirements.
Implement a risk management strategy
Risk management is something you must think of while conducting your data migration process. There are many problems that could potentially occur. Listing them and coming up with ways to either resolve them or prevent them from occurring in the first place, will make the process more successful. Think of depreciated data values, security, user testing, application dependencies, etc.
Migrating is a hard thing to do and as statistics say 70-90 % failed to meet expectations. You have to consider all pros and cons before. Additionally you have to consider migrating data can couse downtimes, inconsistency problems and more. Be prepared. Python Developer
Approach it with an agile mindset
Using agile during data migration will help you maintain high data quality thanks to frequent testing, spot and eliminate errors as they occur and overall make the process more transparent. It will also make the costs and schedule more predictable, as it requires a clear division of tasks and responsibilities and sticking to deadlines.
What you should remember about testing?
Waiting until your data transfer has been completed to test it could cost you dearly. Test your data migration during each phase: planning, design, implementation, and maintenance. Only then you’ll be able to achieve the desired outcome in a timely manner.
Data migration can be a complex process, but it’s something your company will have to go through at some point. Backup your data to avoid losing it if things don’t go as planned and they frequently don’t. That’s why it’s worth having a risk management strategy in place – figure out all the potential problems and try to come up with solutions to quickly resolve them.
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