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4 Steps to an Efficient Data Migration Process

Data migration is a sensitive business. Not only are there a myriad of pitfalls to avoid — like disrupting stakeholders down the data line or finding errors during the go-live — but the migration also involves a highly valuable asset: data.

In recent years, data modernization has been the second most popular reason for businesses to migrate to the cloud, just behind security and data protection. Companies realize that data is valuable when used effectively, which often means analysis in the cloud following a data migration. But executing an efficient data migration strategy takes planning, alignment, and vision.

Considerations like deciding between a phased or big bang adoption can impact the efficiency of your data migration today and in the future. Other things to consider are the quality of data, its use, and the type of IT partner you bring on board to help plan and execute the data migration strategy.

To ensure a smooth and successful data migration, navigate through the following crucial steps:

1. Clearly Define the Scope of Work

Data reaches far within an organization. When in the early stages of planning a data migration process, map out a strategy clearly defining the destination and who this shift will affect along the way. A successful migration begins with identifying the size and constraints of the migration.

Budget and timelines are foundational elements to an efficient data migration strategy. These fundamental values not only keep the migration team focused and intentional, but they also hold the migration team accountable in a way that’s translatable to outside stakeholders. And stakeholder buy-in across an organization and its partners is vital. When stakeholders can see the scope — or broad strokes — of a data migration, they’re more likely to align with the strategy and aid if needed.

Once you establish budget and timeline, identify a location and prepare the new environment for your data. Consider the types of software and hardware needed to migrate the data. You may need to procure or update this before the migration. Also critical is the initial evaluation of data: does it need to be cleaned up before an efficient migration occurs?

Addressing this as well as the target structure and organization of that data in the new system will eliminate much of the “on the fly” work. This clearly defined scope and plan make for an intentional and lower-risk data migration process.

2. Evaluate Quality and Integrity of Source Data

No one wants to invest resources in a data migration only to find that the data was compromised, inaccurate, or duplicated. A thorough evaluation of data should always precede the migration process.

Additionally, companies will want to make sure that the data they’re focusing on is of value to the business. Data that doesn’t align with a business’s strategic initiatives or serve a meaningful purpose should probably be safely discarded or stored elsewhere to avoid cluttering up the migration. The evaluation process builds in time for companies to consider their data.

Data integrity is also an essential factor to consider. Once it has been established that the data in question is of company value, it should be evaluated according to the four areas of data integrity.

  • Domain integrity ensures information in the database follows the defined rules
  • Entity integrity checks that each row in a table is an identifiable entity
  • Referential integrity makes sure the relationships between tables is intact as data is modified
  • User-defined integrity gives you the ability to define specific business rules

If these are all intact, the data is ready.

3. Build a Roadmap for Your Data Migration Strategy

A roadmap is essential to help fill out the steps from point A to point B. Without those steps, guesswork takes over, which is the antithesis to efficient movement. To build out an efficient data migration strategy, a roadmap is necessary.

An efficient migration requires a predetermined design, process, and destination. For instance, if the destination is in the cloud, an organization needs to complete the targeting, purchasing, and partnering with cloud-based resources before migration can occur.

Organizations should also establish alignment throughout departments and governance over the new tech, creating strategies to continue data maintenance and ensure high-quality, usable data.

But perhaps the most critical aspect of a roadmap is the type of migration. There are two types of data migration strategies: phased adoption and direct changeover.

Phased adoption is incremental. It offers continuity for businesses that use enterprise data. However, it takes longer to implement the migration and carries over legacy attributes since the new system needs to stay connected to the old system.

Direct changeover, also known as big bang adoption, is exactly like it sounds: fast. There’s no transition period between old and new systems, meaning it’s simpler and quicker. However, this strategy is riskier as there’s a steeper learning curve for all stakeholders.

4. Test and Execute the Migration

Once you have a destination, stakeholders on board, and a strategic roadmap, it’s time to test. You should only execute the migration after feeling confident after a good test run.

As the old adage goes: measure twice, cut once. Testing is extremely important. No organization wants supplemental migrations to support a failed first attempt. When testing a migration strategy, it’s essential to audit and edit the plan to achieve the desired results. Before execution, develop contingency plans and notify stakeholders.

Once you execute the migration, the work isn’t over. You need to establish new standards for data, governance, and new cloud-based opportunities.

If the destination of data is the cloud, there are myriad opportunities to unlock the power of that data. This can range from enterprise solutions to AI to cutting-edge analysis — things not achievable before a migration. Using these new tools to utilize data insights for growth and scalability will show stakeholders the value of these IT solutions.

Find the Partner that Fits Your Data Migration Process Needs

From planning to evaluation to execution, data migration is a big job that benefits from bringing on a trusted, experienced consultant to make sure the journey is smooth and safe for the business, data, and stakeholders.

Soliant delivers data migration consulting as part of its overall business solution development packages. If your next business application requires a data migration, we can help you with the entire end-to-end process — from scope-building and solution development to data migration and deployment of new systems that better leverage your data.

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