Data & AI Evangelist
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Data migration should be a strategic process. Yet, many organizations play fast and loose with their data migration strategy, overlooking the careful consideration and planning it requires. This lack of foresight triggers various costly consequences, such as overrun budgets, missed deadlines, and disrupted operations that ultimately affect not just the business but also its customers.
The recent studies shed light on just how widespread these issues are. 80% of data migration projects go over budgets and fail to deliver on time. Even more concerning, fewer than 70% are deemed successful. These numbers serve as a wake-up call, emphasizing the need for businesses to rethink their approach to the data migration process. Moreover, it also reveals how poor planning and lack of focus can instantly transform a critical process into a costly setback.
So why does data migration go wrong so often? Is it a lack of expertise, insufficient planning, or underestimating the scale of the task? In this blog, we’ll uncover the data migration challenges that cause migration failures and explore solutions that organizations can opt for to get over this critical process successfully. Additionally, we’ll provide a quick checklist to ensure a smooth and effortless data migration journey.
Learn more: Understand the concept of data migration, its importance, and its key types.
What causes data migration failure?
Data migration might sound like just moving data from point A to B but in reality, it’s a complex process that requires thorough planning and execution. Therefore, to avoid data migration failure, it is important to understand what can go wrong and why. Below are some of the major root causes that contribute to data migration failure, a strategic mitigation plan to address them.
Lack of proper strategy and planning
When it comes to migrating data, most organizations begin transitioning their data to an advanced data platform without understanding the “why” behind the data migration. For example, is the goal to consolidate systems, improve performance, or meet compliance requirements?
If the goals and objectives aren’t clear from the start, it’s easy for the whole process to get off track, with teams pulling in different directions. The data migration risks, such as unexpected downtime or data corruption, often go unnoticed in the early stages, and without a solid risk assessment, these issues can throw the entire migration off course.
Solution
To avoid failures stemming from inadequate planning and strategy, it’s important to approach migration with a clear and structured data migration plan, conduct a thorough risk assessment, and prioritize comprehensive data migration testing. This proactive approach will ensure a smooth migration without a hitch.
Poor data quality
When data quality isn’t up to par, the migration journey becomes much more challenging and prone to failure. Poor data – like incomplete, duplicate, or inconsistent data cause all sorts of issues, leading to errors that slow everything down. On top of that, dealing with outdated or unstructured data formats is challenging, as they often don’t map well to modern systems.
Another significant factor that causes data migration failure is data corruption when the files or databases get messed up, causing delays and threatening the integrity of your business data. Without high-quality, well-organized data, the data migration process becomes much riskier and puts your entire business operations at risk.
Solution
To avoid such failures, start with a detailed audit to identify and clean issues like duplicates, inconsistencies, and corrupted files. Use automated tools for data profiling and transformation and validate data through pilot testing before full migration.
Underestimating the data complexity
One of the biggest challenges in data migration is the underestimation of data complexity. Organizations often assume that transferring data from one system to another is a straightforward process. However, data migration is rarely simple – it involves multiple layers of complexity that, if overlooked, can lead to project delays, cost overruns, and even failure.
Hidden dependencies, poor data quality, and unstructured data challenges often lead to project delays, cost overruns, and operational disruptions.
On top of that, many data sets and applications are deeply interconnected, creating dependencies that aren’t always obvious. Overlooking these connections can cause integration issues, breaking workflows and disrupting operations.
Solution
To mitigate the risks of underestimating data migration complexity, businesses should thoroughly access data migration from legacy systems, map out how everything is connected, and run small test migrations first.
Quick read: Modern Data Platforms: Your guide to data-driven decisions.
Overlooking data governance policies
A lack of proper data governance best practices and clear methods is another major reason why data migration projects plan fails. Just moving data to a new system isn’t enough—if the data is technically valid but inaccurate, it won’t meet business needs. Without a structured plan for managing data quality, teams often don’t know what “good” data should look like, leading to confusion and inconsistent fixes.
Traditional approaches, like the waterfall method, don’t work well for data migration because they lack the flexibility needed to clean and improve data during the process. These issues together lead to poor data quality, inefficiency, and a higher chance of failure.
Solution
A structured approach to managing data is essential to avoid migration failures. This includes implementing data quality standards, using automated tools for cleansing and validation, adopting iterative methods, and conducting pilot tests to ensure accuracy and consistency.
Picking the wrong data migration tools
A good match between the crucial data migration tool and migration requirements is key to a smooth and successful migration. Choosing incompatible data migration tools leads to errors, data loss, and incomplete transfers, especially when they fail to handle specific formats, structures, or large data volumes.
Migration tools lacking advanced features like real-time validation, error handling, or automation may increase manual work and the risk of human errors. Without proper compatibility with legacy systems or target platforms, the data migration process flow can stall, leading to delays, increased costs, and a failure to meet business objectives.
Solution
To overcome failure caused by the selection of wrong migration tool, businesses should access migration requirements, research and evaluate tools, and test the tool on a small dataset to ensure it handles the migration efficiently and meets the requirements.
Simplifying data migration: Checklist for a seamless transition
The high rate of data migration failures doesn’t mean your efforts are bound to fail, it’s a reminder of the importance of smart planning, attention to detail, and the right strategies. By following a well-thought-out data migration checklist, you can tackle potential data migration challenges head-on, minimize risks, and set the stage for a smooth migration.
- Understanding the legacy system’s data and the new system’s requirements is important for compatibility. This ensures accurate mapping and transformation, minimizing errors during data migration.
- Ensure you have a rock-solid backup and rollback plan in place to prevent data loss and keep downtime to a minimum if migration challenges arise.
- Profile your data thoroughly to uncover risks, identify discrepancies, analyze root causes, and prioritize “must-have” versus “nice-to-have” requirements.
- Establish strong data governance by defining clear roles, responsibilities, and processes for managing data quality, including standards for duplicates and remediation steps.
- Embrace iteration and change by refining the process through repeated cycles and staying flexible to adapt to changes throughout the migration.
- Separate data from applications by managing them as distinct entities with unique requirements to ensure smoother and more efficient migration.
- Instead of viewing data migration as a one-time event, treat it as an ongoing, repeatable process. Establish a “data migration factory” with a structured methodology, clear workflows, and a dedicated data quality engine to ensure a seamless transition from source to target systems.
Ensure a smooth and transformative data migration with Confiz
Migrating data from legacy systems to modern platforms doesn’t have to be complex. With Confiz as your trusted partner, we ensure a seamless transition backed by a well-crafted migration strategy that minimizes disruptions and prioritizes data integrity and security. Our expertise goes beyond solving data migration challenges – we empower your organization to harness the full potential of your data, driving innovation and unlocking new opportunities.
Take the first step toward a successful migration today! Reach out to us at marketing@confiz.com and let our team guide you through a confident and transformative data migration journey.
