Top 10 Data Migration Challenges and Ways to Overcome Them

Transitioning your data from one source to another seems a simple task. But not for businesses that daily collect big volumes of structured and unstructured data. According to Oracle, more than 80% of data migration projects fail to meet deadlines or stick to the budget. One of the top 4 reasons for this is that companies neglect data migration challenges, ignore careful planning, and cannot handle the damage these risks bring to their projects.

If you are determined to change this tendency and complete your data transfer on time and according to your budget, this article is for you.

Today, we will explore the top 10 data migration challenges and the solutions to overcome them. Keep reading to learn what successful data transition is, what data migration types exist, and how to minimize major data migration risks that can affect your budget and performance.

What Is Data Migration and Why Is It Challenging for Businesses?

Migrating data is the process of transferring your data from one system to another that ensures data integrity. The system your data is supposed to migrate to is called the target system. The data transfer process involves the use of certain data transition approaches, principles, and techniques that help companies prevent data loss and minimize risks in data transition. Check out our blog to discover the difference between data migration and data conversion.

Here are some factors that should be considered when planning data migration.

• Data volume. If you plan to migrate a limited volume of data (for example, up to 10 terabytes), this can be done simply and quickly. However, if your company’s data exceeds the petabyte, you will likely need to involve special data migration tools. This will help you minimize the transition risks and data migration efforts and ensure that the process runs smoothly.
• Workload type. The type of workload will shape the data migration strategy. If you use specialized data types (such as virtual machines or databases), you can use the tools that are usually provided by the software vendors. If you migrate data that is mission-critical, try to break the process into several stages. Otherwise, plan the migration to be done when your business and your clients are inactive (for example, during the night hours).
• The optimal timeline for the project. The more time you dedicate to the project, the less disruptive the transition will be. Define the scope of time and budget you are ready to invest in data migration. It will help your software vendors plan the process securely and with no risks.

Data migration is challenging for several reasons. First, the complexity of modern data environments means information often comes from various systems, formats, and sources. So, it’s difficult to migrate without losing structure or meaning. There’s also the risk of data loss or corruption. Imagine that just one mistake can result in missing or damaged information that’s hard to recover. Finally, migration can cause downtime or disruption, especially if systems need to be taken offline.

Types of Data Migration

Here are the common 5 types of data transition projects:

Database migration

Under this data transition process, you move your data from one database to another. For example, you decide to move your data from PostgreSQL to MySQL. Typically, migrating existing data from one database to another does not involve changing the structure of data but presupposes preserving data quality. Before choosing the database, you need to check if its size matches your expectations. Also, consider how critical data will be protected in this database. To eliminate data migration challenges, assess the database by testing it with test apps.

Database upgrade

This involves transitioning your data from the legacy system to the new version of the same database. This decision can be caused by the fact that the older versions will no longer be supported, or that the new version offers more benefits for businesses.

An example of a database upgrade is moving from Universal Analytics to Google Analytics 4. Starting from July 2023, Universal Analytics will stop processing data. It will be replaced by the next-gen Google Analytics 4. The property will automatically be created for businesses that have been using Universal Analytics before. Businesses will continue to collect data in a new upgraded Analytics version. But what should they do with historical data stored in the previous version? According to Google, they will be able to access it for nearly 6 months. Then, the data will be unavailable to users. Therefore, Google encourages businesses to export their historical data to the upgraded solution.

Contact Forbytes if you need help with data migration, with our expertise, we’ll transfer your data without any risks of data loss.

App migration

This is migrating your application from one framework to another. This process involves changing the model of data, which is usually unique for every application. To perform a successful transition of this type, you should make sure that the data formats are communicable between the two solutions. If you migrate incompatible data, you increase the risks of data loss.

Infrastructure migration

This data transition type involves migrating the whole infrastructure that consists of solutions, data systems, applications, etc. The most popular example of infrastructure transition is migrating from legacy from on-premises to the cloud. Because of the low maintenance costs and effort, more and more companies are moving their business ecosystem to the cloud. By leveraging effective cloud migration strategies, they cut expenses, prevent data damage, and ensure data integrity as well as real-time access for all stakeholders.

Storage migration

Storage migration is when you change the storage space where your existing data is kept. Data transitions of this type involve changing the hardware device for data storage from one to another. This may be done for data protection purposes. If another data storage provider offers better data protection (such as cloning, validating data, etc.), mind this data migration type for your business.

Data Migration Benefits

Why are data teams investing so much time into data migration? We have revealed the reasons for what they gain:

• Scalability: Modern tools like Snowflake, dbt, and Fivetran make it easier (and cheaper) to store, move, and transform data. Plus, they’re built to grow with your team. Everyone from analysts to engineers can jump in and contribute, making data work more collaborative and scalable.
• Cost savings: Migrating from on-premise to cloud? You’ll cut costs on hardware and maintenance. Tools like dbt and Airbyte are open-source, and platforms like Fivetran eliminate the need for custom ETL scripts. Less complexity means more efficiency.
• Better data governance: Modern stacks let you control who sees what, track every change, and build in testing. That means cleaner data, fewer surprises, and more peace of mind.

Thinking about migrating your data? Our team is ready to assist. Just contact us, and we’ll return with our plan of action.

10 Data Migration Challenges and Solutions to Overcome Them

Here are the top 10 migration risks you may face and the solutions to eliminate them:

1. Data Loss

In the process of migration, some parts of your data may not be transmitted. If you face this risk, you can lose your data irrevocably. Here is what you should do to prevent this from happening:

Solution: Before migrating your data, you need to develop a reliable data backup strategy. In case something goes wrong during the migration, you will always have the chance to restore the data using the backup source. Also, to check if all data migrated to a new location, your data migration partner will conduct data migration testing. This will help you make sure that all your historical data is preserved, and you can keep leveraging it in reporting and data analysis.

2. Semantics errors

Even if all your data was successfully transitioned to the new location, some failures in data semantics could occur. For instance, in your previous data storage, there was a field called “grand total.” After the data transitions to the target location, the data from this field ends up in a different field or column. This can result in inaccurate reporting, wrong interpretations, and data gaps.

Solution: Data transfer testing will also help to prevent this risk. It’s highly recommended to conduct multiple testing sessions, particularly when the transfer process involves big volumes of existing data.

3. Extended downtime

This data migration risk occurs when the transition process takes longer than expected. This may result in significant losses for your business. As your system does not work during the migration, you stop collecting data and may lose some part of the essential business insights.

Solution: You need to choose a data transition company that ensures minimal downtime. Here at Forbytes, we do our best to reduce downtime to a minimum and ensure a non-disruptive data migration process.

If your business is located in the US, a good idea is to choose a software engineering partner from Eastern Europe. Because of the big time zone difference, your partnering team will work on the data migration steps when you sleep and your business is outside of work hours.

4. Data corruption

Data corruption is one of the data transfer risks that can happen if unwanted data types are migrated to the new system. As a result, you can face a system crash or damage the data organization.

Solution: To prevent this data migration risk, the data migration company you hire should perform an audit of the data types and sources that your business uses before moving to the data-transferring project itself.

5. App performance

Your target platform can work unstably because of several reasons. This can be the poor code quality of an application, app bugs, or the inability of the app to handle the high workload. Also, some problems with the app’s performance may be associated with data migrations. For example, issues can happen when a company uses unstable or insecure data migration tools for transitioning data.

Solution: The right choice of software systems and solutions for data transfer determines if the process is successful and if you can handle migration risks. If your team lacks experience in data transition, consider hiring experts in this field. Together, you will pick the best tech stack with regard to your typical workload, requirements, and goals.

6. Data orchestration

Orchestration means taking siloed data from different sources and migrating it to one location in an organized way. Without proper data transfer planning, you can lose track of the data points that you use, which will only increase the number of data silos. If so, the data transition project will be incomplete. The problem arises when multiple disconnected teams are working in different departments. Also, it can occur when functional and technical teams are leveraging data in plenty of ways.

Solution: To prevent this data transfer risk, plan out the process thoroughly. Before focusing on the migration itself, focus on your business processes. Conduct an audit of all data-related processes in your organization and make a list of all data sources to be united under one central solution.

7. Integration problems

Your data sources can be integrated with other tools and systems to share and exchange data. If you choose an ineffective data migration strategy, you are at risk of losing access to insights generated from the collected data.

Solution: To minimize this type of data transfer challenge, you should communicate your business goals in advance. Also, your tech partner should make sure that your legacy system can be integrated with other solutions. This will enable you to keep generating insights and producing value for your business.

8. User training

Transferring data to a new location means that the staff’s focus will also move from the system they use daily to a brand-new solution. A lack of knowledge on how to manage a new system can lead to human errors in the system. The data can be collected, interpreted, or organized incorrectly.

Solution: Launch staff training if needed. If your team has never worked with the new solution before, they may need guidance and help. On the one hand, taking your team away from their daily tasks and teaching them to use new technology can be disruptive to your business. On the other hand, this complex process should not be neglected by the companies as the risks of human error can have a much adverse effect on performance.

9. Data security

This is one of the most common transition risks. When migrating existing data, you get one more challenge — exposing your data to third parties. Besides, it can turn out that your target system is more prone to vulnerabilities compared to legacy systems.

Solution: Compile the list of security requirements and specifications you have with regard to the target system. When choosing, make sure that it meets all your needs and can ensure robust data security. To minimize risks in data transfer, you should build a data security strategy as a part of a data migration strategy.

10. Data quality

Businesses collect big volumes of data. But not all data is of high quality and importance. Migrating missing, inconsistent, useless, or incorrect data may adversely affect the performance of the target system. Poor data quality can also lead to bugs and system errors.

Solution: To prevent data quality issues, make sure that you perform data cleansing before migration. Here at Forbytes, we implement a 6-step migration process that involves data cleansing.

Best Practices for Data Migration

Once your team has identified and assigned common data migration tasks, it’s time to focus on the roadmap for getting it done. It’s easy to picture the final result, but the real challenge is putting in the work to get there. So, we’ve prepared some tips to prepare you for data migration process:

• Plan ahead: Define what data will move, the timeline, and required resources.

• Map your data: Match fields between systems to ensure accurate migration.

• Clean it up: Remove outdated or duplicate data to keep the migration clean.

• Test & validate: Run tests to confirm everything transferred correctly.

• Use the right tools: A good migration tool can save time and reduce errors.

• Document the process: Keep track of each step for future reference.

• Monitor & adjust: After the move, check your data and fix any issues.

• Train your team: Help users understand how to use and manage the new system.

• Provide support: Offer ongoing maintenance to keep data accurate and reliable.

Following these steps helps ensure a smooth, successful migration without surprises. The main thing now is to follow these simple steps and decide on tools and a team that can assist you.

Need Help with Data Migration?

As you see, numerous data migration challenges can occur when you decide to move your data to a better and safer location. In this article, we outlined the top 10 data migration risks and the simple ways to overcome them.

Overall, to secure your business, you need to develop a robust data migration strategy. Having a step-by-step data migration plan will help you think about the migration risks in advance and prepare an instant response.

Get in touch with us if you need help with planning and implementing data migration. Our software engineering experts will provide you with vital support and maintenance services after the migration to make sure that you see the positive impact of such a decision on your business performance.