Data drives big business, and data migration is the process of selecting, preparing, extracting and transforming data from one system to another. There is no one-size-fits-all approach and data is much more than just coding; it’s an art form. This article dives into the challenges of data migration and four best practices companies can follow to ensure its effectiveness.
Why cloud migration costs can get out of control
Data is an increasingly valuable business asset and, for enterprises, migrating existing databases to new systems and cloud infrastructures is a daunting yet vital step in their digital transformation journeys. Migrating data to the cloud helps businesses increase their speed to market, improve scalability and reduce the need for technical resources.
However, moving data isn’t straightforward. Many businesses end up overspending because they try to migrate too quickly or without the adequate strategy or expertise in place. The process of data migration needs to be seamless and well-established to run efficiently. So, what are the best processes to achieve the most efficient data migration?
Step one: Data security and compliance
A lack of data security can have devastating consequences, which is why businesses must take this issue seriously. Sensitive data should be completely secure and comply with local data security regulations. Before you start any data migration process, check the security measures in place and who has access to the data at what level.
For your security plan to be cost-effective, the effort you put into it must be proportional to the value of the data itself and the implications of a security breach.
Step two: Disentangle your data
Allow time at the beginning of a migration to sort out data and application complexities, such as data gravity and data silos. This will save you time, money and effort in the long run. Data gravity happens when data attracts other data and applications to it, this makes it difficult to disentangle the data from the applications that are using it.
Data silos are isolated, incompatible data formats that develop when an application works with unique data structures that don’t communicate with the rest of the system. It’s important to spend time resolving these issues before migration.
Step three: Decide your strategy
Your business needs and requirements should determine your data migration strategy. There is a myriad of different ways to migrate data, however, most strategies fall into the below two categories.
Big bang migration
In a big bang data migration, all data is migrated from an old, legacy system to a new system in a single operation at a single moment in time. Live systems go into downtime while data goes through processing and is moved to the new database.
The advantage of this strategy is that it is the simplest option and saves time. However, a big disadvantage is that downtime can place pressure on business operations.
Trickle migration follows an agile approach. Migration is broken down into phases. During these, the old and new systems run simultaneously, so the advantage is that you eliminate downtime and operational interruptions. The disadvantage is that this strategy takes more time and these implementations can be complex in design.
However, if done well, the added complexity usually reduces risk because it’s easier to confirm the success of each phase and to learn lessons from any failures quickly. This means you’re less likely to experience unexpected failures.
Step four: Choose the right partner
Your choice of migration partner will determine the success of your cloud migration strategy. Many businesses’ strategies fail because they select their partner based on who they know or the lowest price they can find. Others try to save money but give this task to an internal team who are unlikely to have the right experience or expertise. Such choices are a false economy as they lead to mistakes that increase costs in the long term.
Outsourcing specialists have years of experience providing the support businesses need to make complex data migrations as smooth and efficient as possible.
The bottom line
Though every data migration is different, businesses can use these four steps as a guide to ensure they are migrating data in the most efficient, effective and secure way possible.