Data migration in the days of paper filing systems was a physically strenuous but relatively simple proposition, a matter of transferring records from one location to another. It’s different in the age of big data. Transferring your valuable data from one server or repository to a target system might seem similarly straightforward, but the diversity of data in the 21st century makes the process more complicated than it looks at first glance. To get the job done while preserving the security and integrity of your data, you need a data migration strategy.

Here, we’ll look at the key steps in a cloud migration process for a modern business, focused on the data migration tools you’ll need and the best ways to preserve your data quality as you move resources from a source system — or a series of legacy systems — to your new target systems.

Why You Need a Data Migration Strategy

Data Migration Strategy

Simply put, data migration occurs when your company needs to move data from one system to another. It’s basically what needs to happen when your business is looking to introduce new systems and applications and needs to transfer your existing data from your legacy system into a new setting. Understanding data migration and the potential intricacies it involves will help you avoid data loss during this process, taking advantage of data migration software and specialists and leveraging backup resources to your advantage.

There are several types of data migration, and it’s important to understand them in order to keep your business processes up and running efficiently throughout the entire process.

  • Database migration is the process of migrating your databases to take advantage of more advanced data management, improved performance or cost-effective scaling.
  • Storage migration becomes necessary when upgrading your storage technology or switching from on-premises data storage to a cloud solution.
  • Application migration is about moving data between app platforms or vendor ecosystems to take advantage of new opportunities.

Without a structured data migration strategy, you could find that even with a seemingly sound base of source data, you might wind up with redundancies and uncertainties in the new data set. Issues that had gone unnoticed in the source data can become amplified in the migrated data, leading to missed deadlines, budget overruns or even the migration project’s overall failure.

Ingredients of a Successful Data Migration Project

Delivering a successful data migration projection means having a structured approach and a dedicated team that can give the task their full attention. There are a few key ingredients that go into making this work.

Data Migration Team

The whole process depends on bringing the right people to your data migration team and giving them the space and time to carry out the process. Both business users and IT staff and consultants should be involved, and the data migration should be its own independent priority for them, not a subordinate part of some larger project. A consistent team should work together across the entire process, and everyone should have access to an easy-to-use data migration software solution.

Data Audit

A thorough data audit is a necessity before you get started. This will alert you to any possible issues in the source data before it becomes an issue.

Data Cleanup

Any problems the audit uncovers with inaccurate data or other data quality issues will need to be cleaned up before proceeding. Additional data migration tools and third-party resources might be necessary, depending on the scale of the job.

Data Protection

Your important data will tend to degrade over time unless you have controls in place to maintain optimal data quality.

Data Governance

Use automated and user-friendly tools and processes to track and report on the migration process to ensure data quality and integrity.

In order to achieve these outcomes, you need to decide what type of data migration you’ll be using and consider a few key steps.

Data Migration on Computer

Deciding on the Type of Data Migration

There are two major approaches to data migration: the big bang project and trickle migration.

Big Bang Migration

A big bang migration assigns a specific window of time for transferring data. It involves downtime while the data is processed and transitioned. This presents the attraction of compressing the entire process into a single event but can also involve intense pressure, the more so the longer the downtime lasts. It’s often advisable to rehearse this kind of process before attempting the real thing.

Trickle Migration

The legacy system and the new system run in parallel, as a trickle migration happens in phases. This type of migration is designed to keep your business processes up and running and uninterrupted throughout the process while your data is migrated. Planning a trickle migration can be complex, but it pays dividends in the form of reduced risk.

The Key Steps of Data Migration

The key steps in a data migration strategy are planning, preparation, design, execution, testing and maintenance.

  • Planning is about assessing the scope of the proposed project, choosing the type of migration and selecting a team, planning the retirement of the legacy system and choosing any software tools you might need.
  • Preparation involves auditing the source data, backing it up before the migration process starts — having comprehensive backups is extremely important — and establishing who has rights to access, edit and remove data from the legacy system and to work directly on the target system.
  • Design means mapping out the specifics of the migration and which fields and file types in the legacy system will end up in which locations on the target system.
  • Execution is the process of extracting the data, transforming it into the correct formats if needed and loading it into the target system. This may involve a rehearsal phase in the case of a big bang project.
  • Testing involves testing out each batch of transferred data in a trickle migration or testing the entire transferred data set in a big bang migration, spotting and fixing any issues discovered and then testing again until all stakeholders are satisfied before going live.
  • Maintenance is about completing a post-migration audit and monitoring the new system to ensure it’s performing up to expectations.

Creating and executing a successful data migration strategy is best done in consultation with data experts like the team at EIRE Systems. Contact us today and discover how we can optimize data migration processes and make your business agile and competitive in a fast-moving modern marketplace.