In our daily lives, moving information from one location to another is no more than a simple copy-and-paste operation. Everything gets far more complicated when it comes to transferring millions of data units into a new system.

However, many companies treat even a massive data migration as a low-level, two-clicks task. Such an initial underestimation translates to spending extra time and money. Recent studies revealed that 55 percent of data migration projects went over budget and 62 percent appeared to be harder than expected or actually failed.

How to avoid falling into the same trap? The answer lies in understanding the essentials of the data migration process, from its triggers to final phases.

If you are already familiar with theoretical aspects of the problem, you may jump to the section Data Migration Process where we give practical recommendations. Otherwise, let’s start from the most basic question: What is data migration?

What is data migration?
In general terms, data migration is the transfer of the existing historical data to new storage, system, or file format. This process is not as simple as it may sound. It involves a lot of preparation and post-migration activities including planning, creating backups, quality testing, and validation of results. The migration ends only when the old system, database, or environment is shut down.

data migration triggers
What makes companies migrate their data assets.

Usually, data migration comes as a part of a larger project such as

legacy software modernization or replacement,
the expansion of system and storage capacities,
the introduction of an additional system working alongside the existing application,
the shift to a centralized database to eliminate data silos and achieve interoperability,
moving IT infrastructure to the cloud, or
merger and acquisition (M&A) activities when IT landscapes must be consolidated into a single system.
Explore how AltexSoft helped

ASL Aviation migrate to cloud

Data migration is sometimes confused with other processes involving massive data movements. Before we go any further, it’s important to clear up the differences between data migration, data integration, and data replication.

Data migration vs data integration
Unlike migration dealing with the company’s internal information, integration is about combining data from multiple sources outside and inside the company into a single view. It is an essential element of the data management strategy that enables connectivity between systems and gives access to the content across a wide array of subjects. Consolidated datasets are a prerequisite for accurate analysis, extracting business insights, and reporting.

Data migration is a one-way journey that ends once all the information is transported to a target location. Integration, by contrast, can be a continuous process, that involves streaming real-time data and sharing information across systems.

Data migration vs data replication
In data migration, after the data is completely transferred to a new location, you eventually abandon the old system or database. In replication, you periodically transport data to a target location, without deleting or discarding its source. So, it has a starting point, but no defined completion time.

Data replication can be a part of the data integration process. Also, it may turn into data migration — provided that the source storage is decommissioned.

Now, we’ll discuss only data migration — a one-time and one-way process of moving to a new house, leaving an old one empty.

I can tell you that migrating legacy data is not always as risky and complicated as it may seem at first glance. In fact, you can turn legacy data migration into a simple and painless process. All you need to do is carefully consider all the steps of legacy data migration and assemble a reliable data migration team to manage the entire process.