7 Common data migration challenges (and how to solve them)
Data migration is a critical process that involves transferring data from one location, format, or application to another. Typically, this occurs when an organization introduces a new system or location for its data, often driven by a need to consolidate or migrate legacy systems to newer ones that can better utilize the data. Migrating to a new enterprise application brings numerous benefits, including improved performance, increased competitiveness, scalability, cost savings, and maximized value, among others.
However, these benefits can come with significant challenges. Migrating existing data to a new application can be a daunting task that introduces inaccuracies, redundancies, and security issues, putting the entire organization at risk. To minimize these risks and ensure a successful outcome, it's crucial to approach data migration with proper preparation and planning.
In this blog post, we'll explore some of the most common challenges organizations face during the data migration process and provide practical tips to overcome them.
1. Failing to plan: The number one pitfall in data migration
To ensure a successful data migration, proper planning is critical. In other words, fail to plan, plan to fail. Neglecting to create a comprehensive plan can significantly increase the risk of the project going over budget, experiencing significant delays, and not meeting objectives, ultimately leading to failure.
A robust data migration plan should include a thorough assessment of the data and systems, detailed preparation, the actual migration process, and ongoing management. Additionally, it should address critical factors such as security, timeline, staffing, and cost. By creating and implementing a well-planned data migration strategy, organizations can minimize risks and ensure a successful outcome.
2. Compromised data integrity: The risky outcome of poor data mapping
When migrating data to a new system, there’s a good chance the fields may not be identical, which can create issues during the migration process. To prevent this, you’ll need to make decisions on how to migrate the data and set up the necessary infrastructure. A crucial step in data migration is to perform thorough data mapping before the migration occurs to ensure that all data is accurately placed. Missing or incomplete data mapping can result in certain pieces of data ending up in the wrong fields, resulting in the need to spend significant time and effort periodically updating and mapping fields.
3. Data quality at risk: Addressing data compatibility
Ensuring data quality is crucial to the success of any data migration project. Unfortunately, it is not uncommon to encounter poor data quality, which can lead to significant challenges during the migration process. To mitigate these challenges, it’s essential to invest sufficient time and effort to understand and improve data quality before beginning the migration.
It’s worth noting that data can have trends, and larger datasets can have even more trends. To identify data quality issues that may be hiding in plain sight, it’s important to be scrupulous when selecting your data sample. By investing the time and effort required to improve data quality, you can help ensure a successful migration and avoid potential delays and complications down the road.
4. Broken chain of custody: The risks of poor data handling
Poor data handling during data migration can result in the loss of business-critical assets, posing a significant risk to organizations. The chain of custody is broken when data is mishandled, especially when sensitive information is involved. It’s essential to remember that your new system will only be as good as the data that supports it. Missing, invalid, or inconsistent data can cause unintended consequences that can be costly to fix. Even if the data is not completely perfect, proper handling is crucial to prevent last-minute issues. To mitigate this risk, companies can ensure data backups are available on separate and highly secure systems during migration.
5. Inadequate testing: The significance of thorough validation
Data migration is a complex process, and despite its complexity, comprehensive testing is often not given enough attention. As a rule of thumb, testing should be carried out throughout the project and not solely by developers. While developers play a crucial role in the testing process as technology professionals, individuals from other business areas should also actively participate in testing.
Once a plan is in place, it is essential to test it thoroughly by initially migrating a small amount of data to ensure that everything runs smoothly. If everything functions as expected, gradually migrate more data. If any issues arise, it is imperative to troubleshoot and resolve them before they cause critical problems.
6. Data incompatibility and integration issues: Why compatibility cannot be ignored
When migrating large amounts of data, there is a higher chance of encountering incompatible data in various types and varieties. In dealing with dissimilar data, it is key to transform it into a compatible format. This can be done by breaking it down into smaller chunks, dividing it into various parts, and developing code. Alternatively, you could use a data management platform to centralize fragmented data in one location, making it accessible, useful, and secure.
Ignoring compatibility issues can result in data integration problems and put critical business processes at risk. Therefore, it is essential to ensure that all data is compatible before migrating it, as well as to consider the impact of any changes made to the data during the migration process. By taking these measures, businesses can avoid potential issues and ensure a smooth transition when migrating data.
7. Poor project management: Failing to communicate during data migration
Data migration is often a component of a more extensive initiative. Without effective communication among IT and cross-functional teams, there is a high likelihood of unintended outcomes. To promote project management excellence and guarantee the overall success of the project, it is important to encourage transparency between functional and technical teams. This way, the migration can satisfy everyone’s expectations.
Continuous communication keeps all stakeholders informed, mitigates risks, and is critical to the success of data migration. Failure to communicate can lead to delays, errors, and misalignment of expectations, which can ultimately cause costly setbacks. For this reason, ensuring open communication channels among all parties involved is crucial to achieving a successful data migration process.
From chaos to clarity
Data migration is an essential process to any successful information governance strategy. As the amount, sources, and types of data continue to grow, it’s important to understand and address the common challenges that can arise during the migration process. Prioritizing validation, addressing compatibility issues, and maintaining open communication channels can help ensure a smooth and successful transition of data to new systems or platforms.
Interested in delving deeper into data migrations? Watch our webinar, “Mastering data migration: From chaos to clarity,” to learn strategies for planning and executing your own successful migration project.