Best practices to follow for data migration
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Migrating data successfully requires planning and a solid process to control your activities. Read here for data migration best practices.
Migrating data, systems, IT infrastructure and applications is no easy feat. But, many companies, pressed to modernize and meet the current market demands of the digital transformation era, may feel the urge to rush through their migration process to keep up with their peers.
SEE: Checklist: PC and Mac migrations (TechRepublic Premium)
Major problems can emerge for organizations that do not have a clear step-by-step plan and overarching strategy in place before they start a data migration. This best practices guide will help shape your own processes and procedures for a successful data migration.
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Data migration is not just about finding the right vendor and deploying automated tools that integrate and migrate your systems. Each company is also responsible for developing its own migration strategy; top migration service providers are most effective when that strategy is well-defined.
There are several components that go into creating a data migration strategy, but the most important ones stem from which of the two main data migration strategies you choose to shape your plan.
SEE: How to identify and avoid common data migration mistakes (TechRepublic)
In a big bang migration strategy, migrations are executed in full, with all data, applications and other pre-identified assets moving at once, even if such a big move leads to system downtime. The big bang approach tends to be the quickest way to complete a migration since everything moves simultaneously.
However, this approach is also more complex, costly and risky. Companies that can’t afford extended downtime or that need to meticulously comb through data security and compliance throughout the process will likely not benefit from this approach.
On the other hand, the trickle migration approach takes on migration in phases. This allows for a more controlled and less intensive migration, which puts less stress on IT teams and business operations and can be less expensive. Needless to say, this process takes more time and may not be appropriate for companies that are on a tight migration schedule.
And while organizations can run their old IT infrastructure during trickle migration, risks are not entirely avoidable. Special care must be taken to design and schedule migration phases according to business-specific requirements.
In both of these approaches to data migration, certain components and processes should be in place to ensure a successful migration. These include:
These critical components and others are detailed in the best practices section below.
While there is no universal consensus on the best practices for data migration, most top technology companies agree on several top priorities. These practices are not just advice and tips but can serve as a guide and blueprint for companies before, during and after migration.
Assessments are foundational for any migration. A thoughtful migration assessment helps organizations develop a clear vision of the entire process of moving data between locations, formats and systems. Data migration assessments should identify risks and benefits, where the data or system is stored, and where it is migrating.
The evaluation also needs to establish if a big bang or trickle approach will be used and how much budget and time needs to be set aside for the project. A detailed timeline should be created at this stage of the process.
Backup, monitoring, targets, security and support are critical components to evaluate during a data migration assessment. Additionally, organizations should look into the quality of the data they are moving and assess possible downtime and other issues that could impact regular business operations.
When companies begin planning and designing their migration, all employees should be made aware of how the migration could affect their work. They should also be given an opportunity to provide feedback.
More often than not, employees outside of the IT department become important stakeholders in the migration process. They can help the team better understand how data assets and systems are currently used in their role and what they hope to see post-migration.
The original source data or system should never be altered or modified during the migration process, even if you notice major issues with the data during that time. Companies should do exhaustive backups to ensure nothing is damaged, altered or corrupted and that reliable data copies are available if needed.
SEE: Best backup software (TechRepublic)
The most significant risk of data migration is losing business-critical assets during the process or mishandling particularly sensitive data. Data backups on separate and highly secure systems aid companies in case of error or data loss during migration.
Migration does not mean you must close shop until the process is complete. An important best practice is to isolate your most crucial production systems during the migration. Those systems that keep a business up and running should only be switched over once the migration has been fully tested on less business-critical assets and systems.
For a successful migration, you must have a clear understanding of your data and your systems. No matter how advanced your new cloud, hybrid, or on-premises environment is, it will not perform well if your code, applications and data are of poor quality.
SEE: Top data quality tools (TechRepublic)
Before migrating, ensure all data is cleansed and fit for use, systems are optimized, and teams in charge of the migration process have a good grip on the migration tools they’ll be using. While this step is already implied in the assessment stage, it deserves additional attention here to avoid some of the most common migration mistakes. It is counterproductive to migrate systems that don’t work correctly.
It’s also not a good idea to upgrade your systems during the migration due to compatibility or other source code errors that could arise and jeopardize success. Ideally, companies should upgrade their original systems and any critical assets before they migrate.
The same can be said for application developers and their projects. Developers should either work on new projects in the new system or complete their applications before migrating them.
Plan your migration in stages, even if you’re using the big bang approach. The average time to migrate to the cloud ranges from one to two months, and larger companies can take even more time to move higher volume and complexity assets. Completing your migration in phases allows you to break the process into micro-targets, making it easier to track progress and potential roadblocks along the way.
SEE: Cloud Data storage policy (TechRepublic Premium)
Doing live tests during each of these phases is recommended. Trials allow you to check your assessment, plan against the live process and test how well migrated systems are performing. Tests can also help companies adjust their migration strategy and control the process.
You should continue testing and monitoring your migration and new systems even after you have flipped the switch. Going live in a new environment will undoubtedly generate new challenges, especially as new data is generated. Regularly testing and ensuring the system is working can help you adjust and improve your current procedures and any future migration plans.
The complexities of data and systems migrations can be alleviated with a strategic assessment and clearly defined responsibilities for your migration team. Speaking of, organizations should consider creating a dedicated migration team with data experts who can manage the process and the technologies while communicating with appropriate stakeholders.
If the migration is handled with a strong strategic plan and follow-through, companies can benefit from the process significantly. Post-migration, they’ll be able to access the latest technology, modernize their workflows and improve many other aspects of their business.
Read next: Top cloud and application migration tools (TechRepublic)
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Best practices to follow for data migration
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