What is a Data Migration Strategy?


The term “data migration” is used to describe the process of moving information from one system to another. Database migration is a viable option for many businesses for many reasons. A company may decide to switch to a different database (say, Oracle) because it believes that Oracle’s features will provide more value than those of its current database (say, MySQL). Or they could be looking to save money by migrating their on-premises legacy system to something like Amazon RDS in the cloud.

However, it’s not a trivial task to transfer data from one location to another, as evidenced by the statistics presented here. Half of all data migration efforts, says Gartner, end up costing more than expected and hurting the firm as a whole. Most typically, this is due to poor planning and implementation of the database migration. That’s because initiatives to migrate databases typically.

Key Factors to Consider in Data Migration Planning

While the specifics of each strategy will vary depending on the organization’s requirements, all data migration plans should adhere to the following outline.

1. Find and Evaluate the Original Source

Data migration requires an in-depth familiarity with both the source and destination systems. Figure out how much and what kind of information is being pulled over and be carrefull about backups.

There could be a lot of fields in the source data, and not all of them would have to be transferred over to the new system. Sometimes, sources have insufficient information, necessitating the addition of data from another source. Determine what must be transferred, what can be abandoned, and what is missing.

In addition to verifying that the transferable data fields are complete, you should examine the data themselves. You may question the necessity of transferring data if you find that many fields are empty, there are many missing pieces of data, the data is inaccurate, or there are other issues.

A company risks wasting time and money on the migration process if it ignores the source evaluation step and instead makes assumptions about the data. The worst-case scenario is that the company discovers a fatal error in the data mapping that completely halts all forward motion.

2. Outline and Plan the Transfer

In the planning stage, businesses decide whether to implement a “big bang” or “trickle” migration strategy. This also entails documenting the migration procedures and building out the technical architecture of the solution.

Start defining deadlines and project concerns by considering the design, the data to be migrated, and the target system. Document all project details at this stage.

When making plans, prioritizing data security measures is crucial. Ensure the protection of sensitive information throughout the entire process.

3. Construct a Plan for the Migration

It’s easy to be sucked into the “just enough” development mentality during a move. The implementation process is just something you will go through once, so it’s important to do it well. Data is typically segmented, with categories developed and tested individually. It may make sense for a company to develop and test in parallel if they are working on a very large migration.

4. Run an Actual Trial

Testing the code during the build phase is not the end of the testing process. To guarantee the correctness of the implementation and the fullness of the application, it is crucial to verify the data migration architecture with live data.

5. Toggle the Power

Once all of the tests have been passed successfully, the implementation can begin in the predetermined fashion.

6. Audit

Make sure the data migration was accurate by establishing an auditing system after the implementation has gone live.

Common Data Migration Challenges

In this part, we’ll discuss some of the most typical obstacles that businesses encounter during the data transfer process, as well as some helpful advice for getting beyond them.

A Lack of Planning

A well-planned data migration is essential for a smooth transition. If you don’t make a plan, you should expect to fail. Without a robust data migration testing strategy, the project’s budget overrun, significant delays, or failure to achieve objectives are highly likely.

Assessing the data and systems, planning in depth, performing the migration, and maintaining the new environment are all essential parts of a successful cloud data migration strategy. Important considerations such as safety, time, manpower, and money also require factoring in. Organizations increase their chances of successful data migration by dedicating time to developing and implementing a comprehensive plan.

Vulnerable Data Integrity as a Result of Improper Data Mapping

Problems can arise during a data migration if the fields aren’t identical between the old and new systems. To avoid this, you’ll need to plan the data migration and put in place the supporting infrastructure. Data migration requires careful data mapping before the actual migration to guarantee that all data is placed correctly. To avoid the need for frequent field updates and remapping caused by incorrect or missing data mapping, it is crucial to ensure comprehensive and accurate data mapping.

At-Risk Information: Solving the Compatibility Problem

A data migration project can only be successful if the data quality is guaranteed. Poor data quality is unfortunately widespread and can cause considerable difficulties throughout the conversion process. To lessen the severity of these difficulties, preparation for the transfer should prioritize learning about and enhancing data quality.

It’s important to remember that data can exhibit trends and that larger datasets can exhibit even more trends. Data quality problems could be lurking in plain sight, thus it’s crucial to select your sample carefully. Spending the time and energy to improve data quality can help guarantee a smooth migration and head off any potential problems in the future.

Risks Associated with Improper Data Management

Careless data handling during data migration poses a serious threat to businesses, risking the potential loss of mission-critical assets. Mistreatment of data, particularly when sensitive information is involved, disrupts the chain of custody. The quality of your new system relies on the accuracy of the data used to build it. Incomplete, incorrect, or inconsistent data can result in undesirable outcomes and subsequent expenses. While the data may not be flawless, proper treatment can prevent last-minute problems. To mitigate risks, businesses should maintain multiple copies of critical data on separate, highly secure platforms.

Insufficient Testing: The Value of Careful Validation

Despite the challenges involved, the importance of thorough testing during a data move is often overlooked. Testing holds a vital role in any project and should extend beyond the development phase. While developers possess expertise in the technology being tested, involving specialists from other areas of the company’s operations is equally important.

After developing a strategy, conduct a trial migration of a small subset of data to test the plan and ensure a smooth transition. If the migration proceeds without issues, gradually add more information. Investigating and resolving problems promptly is crucial to prevent them from escalating into major issues.

Why you can’t afford to disregard compatibility problems when integrating or exchanging data
Large-scale data migration increases the likelihood of coming across incompatible data of diverse forms and flavors. When working with data that isn’t already in the same format, transformation is essential. To achieve this goal, it is helpful to segment the work, identify its constituent pieces, and write appropriate code. Alternatively, using a data management platform consolidates diverse data sources into one accessible, valuable, and secure repository.

Data integration challenges that arise as a result of ignoring compatibility concerns might put vital business processes at risk. That’s why it’s crucial to check the data for compatibility before moving it and to think about how the data will be affected by any transformations. With these precautions taken, enterprises may secure a problem-free data migration.

Choosing the Right Data Migration Approach

Once you have removed the primary roadblock and organized your systems and data, you can start considering the most effective methodology or approach.

Data Migration with a “One and Done” Approach

It is highly recommended to choose this more cost-effective and easier option if feasible. This strategy involves system shutdown, complete data migration, and a fresh start in the new system.

However, the downside is that the systems will be temporarily unavailable, potentially impacting productivity and essential business processes.

To mitigate the financial impact, businesses often schedule such migrations during employee downtime.

The ‘Phased out’ Strategy for Data Migration

Depending on the data volume, completing this approach may take many days or weeks.

Companies that cannot afford an extended shutdown period during data migration make ideal candidates for this approach.

Since the migration will run parallel to ongoing operations, extensive planning is necessary compared to the previous method.

To estimate migration duration, accurate knowledge of data size and transfer time is crucial. The target system must accommodate the migrated data, be fully functional, and already possess its data.

After selecting a strategy, several additional considerations ensure a trouble-free data transfer.

For exceptionally important or large data, consulting an expert should be the first step. Unassisted data processing often leads to data loss and system failure.

Never transfer inaccurate, bloated, or low-quality data to a new system without undergoing a thorough data cleaning process for a seamless transition.

Tools and Techniques for Successful Data Migration

The data itself is secondary to the approach and technology used to migrate it.

Data fuels our daily operations and commercial activities, now widely recognized for its significance.

The global data migration market grows as business data volumes rise, regulations evolve, and historical data preservation becomes imperative.

When merging with or selling off another company (known as an “M&A” or “Divestiture”), it’s easy to lose sight of the finer details that make a big difference.

For a more successful data center migration strategy, it is important to take into account the following three factors:

What are the precise goals, outcomes, and dangers of both of these choices? Can as much data be transferred as needed with a free utility as with a commercial software solution?

While a free tool can save you money, it may not offer the complete solution or cover all of your needs.

Compatibility of Migration Tools To Meet Requirements

Finding the right provider of data transfer tools is crucial to better satisfying your company’s needs. Many often overlook the restrictions of data, mapping of user permissions, additional hardware or software expenditures (servers, storage, etc.), and so on, in favor of superficial aspects when evaluating a software application.

You may end up spending more than planned if you rush to complete the data migration strategy.


Most people view the process of data migration as a nuisance instead of recognizing it as an opportunity to deliver value. This perspective seems to be the primary cause of most if not all, problems. Recognizing migration as a vital innovation initiative that warrants dedicated resources is half the battle won.