Image: Margarita/Adobe Stock Organizations frequently require to establish customized information migration strategies and utilize specialized software to complete the data migration process successfully. They likewise need to select which data migration approach is most fit to their needs.
SEE: Data migration testing list: Through pre- and post-migration (TechRepublic Premium)
In this guide, we’ll cover the fundamentals of what an information migration requires, but we’ll also dive deeper into the various types of information migration and when you may want to utilize every one.
What is data migration?
Information migration is the procedure of moving information from one place to another. This might be a transfer between databases, storage systems, applications, or a variety of other formats and systems. The data migration process usually consists of multiple steps to make information migration-ready, including information preparation, extraction and transformation.
SEE: An intro to data migration (TechRepublic)
The objectives of data migration are to guarantee information is properly and completely migrated, minimize information downtime and reduce migration costs. Common information migration scenarios include site debt consolidation, legacy system upgrades or replacements, the adoption of a cloud-based system, facilities maintenance or consolidation of details systems.
Information migration types by system format
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Although lots of information migration best practices and methods will remain the exact same no matter the data format or system type you’re dealing with, it is essential to understand that certain actions will need to be added or revamped depending upon the type of data you’re moving in addition to the source and target systems that are involved.
Database or schema migration
A database or schema migration takes place when a database schema is adapted to a previous or brand-new version of the database to make migration more smooth. Due to the fact that lots of business work in tradition database and file system formats, data change actions are frequently an important part of this kind of migration.
This type of task involves moving datasets from one storage system or format to another. Today, this typically includes moving information from tape or a traditional disk drive to a higher-capacity hard disk drive or the cloud.
Data center migration
A data center migration includes moving your whole information center to a new physical area or a new non-physical system, like the cloud. Due to the fact that of the scale of this task, extensive data mapping and preparation is necessary to effectively migrate.
Cloud migration occurs when organizations move from tradition on-premises systems to the cloud or when they transfer from one cloud company to another. Applications, databases and a variety of other company possessions will all require to be moved in this sort of migration. Due to its intricacy, the majority of people depend on a third-party supplier or provider to help with cloud migration.
This type of migration might involve moving application(s) from one environment to another, but it can likewise involve moving datasets from one application to another application. This kind of migration often takes place in parallel with cloud or information center migrations, however it can also happen when you’re changing from one supplier to another for a task management application, for example.
Organization process migration
Particularly throughout mergers and acquisitions, in addition to other major organization changes, company procedure migration is used to make sure all understanding is shared with the target system and getting company. This type of migration, depending on the market and area, might involve a specific emphasis on data governance and security procedures.
Main kinds of data migration methods
Picking the right data migration method can have a significant effect on the success of the migration, ensuring a smooth transition and no serious hold-ups. The two standard information migration techniques are a big bang information migration and a trickle data migration.
Big bang data migration technique
The big bang approach includes transferring all data, from the source to the target, in one operation. This makes huge bang data migrations less intricate, less pricey and less time-consuming than drip data migrations. Some companies can finish a huge bang information migration over a vacation or weekend when they are not using the application(s) that are involved.
SEE: Data migration vs data integration: What’s the distinction? (TechRepublic)
It is worth noting that during a big bang data migration, there is significant downtime, as the systems that use the information will be down and unavailable till the migration is total. The downtime could be more for organizations that are moving vast quantities of information.
In addition, the limited throughput of networks and APIs can even more delay the information migration process. As the intricacy and volume of information continue to increase, the big bang data migration approach could become more challenging to carry out.
- Takes less time
- Less complicated
- Less pricey
- Needs information downtime
- Greater risk of expensive failure
The big bang data migration approach is best suited for small businesses or information migration tasks that involve small amounts of information. This technique is not ideal for the migration of mission-critical data that should be available 24/7.
Drip data migration technique
The trickle data migration technique is a kind of iterative or phased migration. It uses nimble strategies to finish the data transfer.
The entire procedure is divided into smaller sub-migrations pieces, each with its own timeline, objectives, scope and quality checks. One of the main goals of trickle data migration is to ensure there is absolutely no downtime, making this strategy suitable for organizations that need access to data 24/7. The source and target systems run in parallel as the data is moved in little increments.
The downsides of the trickle information migration method are that it takes longer to finish the migration process and substantial resources need to be assigned to the task to keep 2 parallel systems running concurrently. In addition, data engineers must ensure the data is synchronized in real-time on both systems.
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A common approach is to have the source system running until completion of the migration, with users only switching to the target system once the whole migration achieves success. However, information engineers need to be conscious that any updates or modifications to the source system must be shown in the target system.
- Absolutely no downtime
- Less prone to unforeseen failures
- More costly
- More time-consuming
- Requirements additional resources to keep 2 systems running
Medium-sized and larger organizations may prefer this data migration approach as there is no data downtime. Larger companies may likewise have the resources and technical competence needed to run two systems at the same time.
Data migration best practices
Back up information
The purpose of data backup is to develop a copy of data that can be recovered in the event of data failure. It is best to profile all source data before writing mapping scripts.
Create a dedicated group for information migration
Assigning or hiring data migration experts will guarantee the job is completed efficiently, If there are problems, a well-trained and highly-qualified team ought to have the capacity, skills and experience to manage them.
Total constant screening
Information engineers must evaluate information migration through all of its phases, including the preparation, style and maintenance stages.
Do not fast to switch off the old platform
Sometimes, the first attempt to complete information migration is unsuccessful, requiring a rollback and another attempt. It is best to wait till the target migration is finished and checked prior to you entirely move away from old systems and applications.
Read next: Top cloud and application migration tools (TechRepublic)