How to Choose the Right Data Migration Method

Did you know, as per Bloor Research’s 2007 Data Migration Customer Survey, that more than 80 percent of data migration projects were either aborted or overran time and budget? Yes, you read that right! The figures may sound alarming but are true.

In our daily lives, moving data from one place to another requires just a simple copy-and-paste operation. However, things get pretty complicated when you have to transfer millions of pieces of data to a new system.

You need to migrate data to keep pace with the dynamics of the industry and technological advancements. Data migration also ensures enhanced cost savings, better accessibility, greater security, and improved compliance. However, it’s easier said than done!

Data migration comes with a lot of challenges. Identifying the right approach and solution is the key to success. Read on to explore everything in detail!

Firstly, let's understand the term ‘Data Migration’ and how it is helpful.

What is data migration?

Simply put, data migration is the process of transferring data from one storage environment to another. It involves extracting data from the original source, transforming it into the desired format, and loading it into the new storage environment.

The process includes migrating data from one operating system to a new target system or moving applications and data from on-premises systems to the cloud platform. Moreover, it may even involve the migration of data from one application to another.

Data migration may appear pretty simple and straightforward. However, it isn’t! A lot of preparation and post-migration activities are essential to ensuring successful outcomes.

Check out this video for a quick intro into data migration:

Key takeaways

• Data migration becomes as a necessity for organizations that are trying to move way from legacy systems.

• Data migraiton improves efficiency, lowers costs, enhances disaster recovery, and increases scalability.

• The process of migrating data is indeed intricate and demands careful preparation, planning, and execution for optimum success.

• Data migration is an opportunity to improve operations, future-proof your organization, and gain a competitive edge.

Data migration in numbers

• The global market size of data migration is likely to reach $33.58 billion by 2030.

• 66 percent of C-suite executives believe that security is among the top benefits of migrating data to the cloud.

• 30 percent of data migration projects result in cost overruns, while 41 percent of projects end up with time overruns.

• Only 36 percent of data migration projects are able to remain within the set budget.

When is data migration essential?

Overhauling and replacing the old systems is indeed the most common reason for data migration. However, there are several other situations when you may need to migrate your existing data into a new system:

• Upgrading data schemas or database management systems owing to the need for greater storage capacity.

• Minimizing operational costs by lowering the number of data hosting systems.

• Upgrading existing applications, hardware, and file formats.

• Setting up new data warehouses for reporting and analytics purposes.

• Shifting to the cloud computing environment from the on-premises systems.

• Removing data that is no longer useful for the organization.

• Consolidating diverse data sources following an acquisition or corporate merger.

Benefits of data migration

Organizations stand to gain a host of benefits from successful data migration projects:

Improves business processes

When you migrate data from the old systems to a new environment, you can easily streamline and improve various processes.

Enhances security

Migrating data to modern platforms allows organizations to strengthen their security and protect their sensitive data against potential attacks and unauthorized access.

Ensures scalability

Data migration provides companies with more space for their databases and makes scaling easier.

Easy data recovery capabilities

Moving your data to the cloud offers you one-click data recovery and backup capabilities, saving time and labor.

Reduces storage costs

Data migration enables organizations to avail themselves of the best services, and that too at a very competitive price.

Common mistakes made in data migration projects

Before you proceed to identify the correct approach and strategy for data migration success, having an idea of common mistakes committed in data migration projects is a must. Make sure you take into account these six most common mistakes:

Lack of planning

You may be tempted to get started with data migration without any prior planning. However, it isn’t a wise decision. Having a solid plan can actually save you hours during the data migration process.

Not involving the key stakeholders

Irrespective of the size of the migration, there is always someone who is affected by the data you are moving. So, involving them in the process can increase the chances of success and prevent unnecessary disruption. Track the key stakeholders and explain to them the need for data migration. Moreover, you can also clearly highlight the impact of the move.

Lack of expertise

You need to have appropriate technical skills to ensure smooth data migration. With an incomplete understanding of data, you are likely to end up making costly errors, thereby exceeding the budget.

Inconsistent data

Maintaining the consistency of the data can indeed be challenging. Especially when the data formats and structures of the old and new systems differ, it can be even more difficult.

Incorrect estimation

Not estimating the time, effort, and cost accurately can complicate organizational endeavors. It may either lead to unavailability of resources or disrupt the operations of your business.

Inaccurate data backup

Before you migrate data to the new system, keeping a backup is a must. However, inaccurate or incomplete data backup can be a serious threat to the organization. It will not only result in process failures but also loss of confidential and crucial organizational data.

Best practices to follow for successful data migration

Following established best practices for data migration can save you significant time and effort. Let's take a brief look at some of them:

• Define and examine the data prior to migration.

• Before moving data, you need access to the source to understand what you are migrating and whether it will fit the target.

• Test and validate the migrated data properly.

• Prepare a solid data protection and backup plan.

• Properly allocate your resources for smooth operations.

• Hire specialists to run the data migration project and ensure optimum success.

Most popular data migration methods

Migrating important and sensitive data isn’t a task to be taken lightly. Botched data migraton initiatives can cause issues like data loss, compatibility issues, business disruption, and downtime, affecting your overall business. That is why choosing the right approach matters a lot. Delve into the most prominent successful data migration methods below!

1. Big Bang data migration

Do you have less time for data migration? Opting for the Big Bang of data migration can be an ideal solution. In this approach, you move data assets from the original source to the target system in just one operation. The overall process takes place within a short period of time.

This approach empowers organizations to complete data migration in the shortest time possible. You get to save a lot of time and effort.

A point to note here is that the source databases will remain down and unavailable until the migration of data is complete. Therefore, it is always a smart move to implement this approach during a holiday, when customers will not be using the application.

The Big Bang migration approach is suitable for small businesses working with a smaller amount of data.

Pros

Simplicity of planning: This data migration approach involves only one migration event. So, the planning process is pretty straightforward in comparison to the phased approaches.

Immediate functionality: After the migration is complete, the new system becomes completely operational. That means you can get access to all functionalities without having to wait any longer. The Big Bang data migration approach can be completed in much less time. It prevents the need to run both systems simultaneously for a prolonged period.

Lower cost: In this approach, the old and new systems do not run for an extended period of time. So, you can expect better cost savings in terms of support and maintenance.

Cons

High risk: In case something goes wrong during the data migration process, it can have a direct impact on the entire organization.

Potentially disruptive: The sudden change may be disruptive to business operations. Moreover, it requires significant downtime for a successful transition.

Limited flexibility: Making necessary adjustments to the strategy in the middle of the process isn’t possible. As a result, the issues identified later can be difficult and costly to fix.

2. Trickle data migration

Trickle data migration is often referred to as iterative or phased migration, as it involves moving the data in different phases.

In this approach, the entire process is divided into sub-migrations. Each transfer comes with unique goals, scope, timelines, and quality checks.

During the migration process, both the old and new systems will run in parallel, and data transfer occurs in small increments. That means you need not worry about downtime. With this, keeping your customers happy with 24/7 application availability becomes simple and easy.

However, the iterative approach can consume a lot of time and may complicate the entire process. You need to keep track of which data has already been transported to the new system and which is yet to be sent. Moreover, you also have to ensure that data across both platforms is synchronized in real time and users are capable of switching between systems to access the required data.

The trickle data migration approach is suitable for medium and large organizations, as they cannot afford lengthy downtime.

Pros

Minimal disruption: Both systems will continue to operate during the migration. As a result, it can significantly lower disruptions to business processes. As you can make small changes throughout the process, it significantly minimizes the chances of failures.

Flexibility: This approach allows you to make refinements and adjustments to the strategies throughout the migration process.

Easy management: Smaller changes are easy to test, manage, and troubleshoot.

Cons

Higher costs: In this approach, you need to run both systems for an extended period of time. As a result, it can give rise to additional costs.

Complexity: Maintaining data synchronization between both systems can be resource-intensive and complex.

3. Lift-and-shift data migration

Planning to transfer data to the cloud? Then lift-and-shift data migration is the most suitable approach. It reflects no or minimal changes to the data flow, multi-cloud architecture, and authentication mechanisms of the application.

When there isn’t any change required, you can easily lift the application from the source system and shift it to the new location. However, for optimum success, make sure to plan the cloud migration properly, keeping aspects like the computing, networking, and storage requirements of the application in mind.

Pros

Speed: In this approach, you do not have to dedicate time to code revisions or optimization. As a result, the migration can be completed in much less time.

Minimal planning: Planning a data migration can take up to one year. However, this approach requires the least amount of resources and strategy, thereby minimizing the need for extensive planning.

Cost savings: In this data migration approach, you do not have to pay for configuration or code changes. So, you can expect greater savings in the long run.

Cons

Optimization issues: Optimizing your legacy workload without any native environment resources can be challenging.

Security risks: This approach doesn’t allow you to examine potential weaknesses beforehand. Once in the cloud, the weaknesses can lead to security risks.

Choosing the ideal data migration solution

With a plethora of data migration solutions available, selecting the right one can be confusing. Make sure to choose a solution that can effectively address the challenges of data migration. There are a few key capabilities you need to consider:

Adequate connectors

The data migration solution should enable the source and target databases to be well connected through a variety of file types and heterogeneous sources.

Portability

The data migration process of the solution needs to be functional and portable in all compatible environments, ensuring optimum convenience for ongoing migrations.

Convenient data mapping

Look for an intuitive solution that comes with a graphical user interface. It will make it easier for you to visualize the entire data migration process.

A solution with drag-and-drop and a code-free GUI can easily map the source and target data. Moreover, it will completely eliminate or, at least, reduce tedious efforts during the data migration process.

Data integrity

The solution you choose must be able to factor in the orchestration of the relevant tables and migrate data accordingly to ensure that the records of tables in the source and target systems are in sync.

Data reconciliation report

The solution should provide detailed performance statistics on the volume of data migrated, its completeness, accuracy, and more, offering in-depth insights into the efficiency of the overall data migration process.

Data migration content to consume

• Video–Maximizing Efficiency: Data Migration and Mapping Insights from a Business Analyst and Scrum Master
• Podcast—Data Migration Best Practice – Overcoming Persistent Missteps
• Article–What is Data Migration?

Conclusion

Digital transformation may require businesses to move data to modern systems. Successful data migration necessitates careful planning and execution. You can choose between Big Bang, trickle, and lift-and-shift approaches for effective migration. Moreover, make sure to select the right solutions to perform the move in a hassle-free and convenient manner.

Recent developments in data integration technology have made techniques like data virtualization available to solve data migration problems. Data virtualization introduces a semantic layer over distributed data sources and enables access through SQL, REST, or GraphQL. By eliminating the need to replicate and move data, data virtualization creates a single view of truth without the hassle of data migration.

Peaka takes data virtualization to another level and puts an end to the data sprawl problem that results from data migration projects. Its zero-ETL approach makes data integration possible without any data warehouses, complex data pipelines, and expensive data teams involved.

Book a free demo and discover how Peaka can simplify your data migration project!