Imagine you have just added a new vessel to your fleet. It is a fantastic milestone, but it comes with a major operational challenge: the ship runs on a different Planned Maintenance System (PMS) than the rest of your fleet.
As the new owner, you naturally want immediate, full visibility into outstanding maintenance tasks, job descriptions, counter values, certificates, and the vessel’s complete history. You receive a backup file from the previous owner, but as soon as you try to import it, you hit a wall: your own system’s database uses a completely different data model.
Transferring this data is unfortunately not a simple matter of copying files. It is a strategic transformation. When you are moving data between databases, you are translating the structure, meaning, and behaviour between two completely different systems. What are the biggest challenges of such a data migration, and how do you handle it efficiently?
The 9 challenges of data migrationÂ
When executing a migration between two different databases, you encounter several complex barriers:
1. Schema and structure differences
You are often dealing with fundamentally different data models, such as Relational (tables, rows, foreign keys) versus NoSQL (documents, key-value, graphs). This causes a mismatch in entities and relationships; for example, one table in your source might need to map to multiple collections or documents in the target system, or vice versa. A classic example is taking a Customer table + Orders table and transforming it into a single document with embedded orders.
2. Data mapping complexity
Field names rarely match up exactly between systems (e.g., cust_id transforming into customerId). You will also encounter data type mismatches, such as integers converting to strings, conflicting date formats, or navigating boolean versus enum values. Developing and maintaining these complex mapping rules requires absolute precision.
3. Data quality issues
Legacy databases frequently come with pre-existing data quality issues. You will have to clean up missing or inconsistent data, duplicate records, and invalid formats before the data can safely sit in your new system.
4. Referential integrity and relationships
When moving data between different database architectures, preserving the relationships between your data points (like linking specific parts to specific maintenance jobs) without native system support becomes a massive challenge.
5. Data volume and performance
Do not underestimate the size of maritime data histories. Migrating exceptionally large datasets can cause long migration times and put a heavy strain on your systems, leading to high memory and CPU usage.
6. Data semantics and business logic
The exact same field name may mean entirely different things in each system. Furthermore, critical business rules that were embedded directly into the source database may not exist in your target system and will need complete reimplementation.
7. Tooling and automation
Depending on the systems the previous owner used, you might find there is very limited tooling available for certain niche or older database combinations, making automation more difficult.
8. Testing and validation
How do you know the process worked? A major hurdle is thoroughly ensuring data completeness and total accuracy after the transformation has taken place.
9. Security and compliance
Throughout the entire process, you must maintain strict control over sensitive data handling and have a bulletproof fallback strategy ready if something fails mid-migration.
Best practices for your migration processÂ
To ensure a smooth migration and a reliable PMS from day one, a structured approach is essential:
- Define a clear mapping specification: Map out exactly how the fields from the old system relate to the new system beforehand, using pre-defined templates.
- Utilise the right tooling: Use specialised ETL (Extract, Transform, Load) tools or pipelines to automate the process and minimise human error.
- Test small, scale Later: Perform small test migrations first to catch any errors or mismatches in the mapping rules at an early stage.
- Implement validation checks: Set up automated data validation checks to verify that all data has been transferred completely and accurately.
- Plan for an incremental migration: Breaking the migration down into phases keeps the process manageable and protects system performance.
How Mastex Software can help
Successfully migrating maritime data requires a deep understanding of both the technology behind the database and the practical reality on board. At Mastex Software, we have broad experience in seamlessly migrating data from a wide range of systems to our platform, including TM Master, Marad, IDEA, Amos, DNV ShipManager and Star IPS to our platform.
Want to learn more about how we ensure your new vessel is up and running in your own PMS without any data hassle? Get in touch with us or request a free demo!
