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data migration

By Alexander S. Gillis

What is data migration?

Data migration is the process of transferring data between data storage systems, data formats or computer systems. An organization can undertake a data migration project for numerous reasons, including when they're doing the following:

The data migration process requires organizations to prepare, extract and transform data and to follow a specified set plan -- which differs by organization and migration.

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Why is data migration important?

Data migration ensures that data is successfully and securely transferred to another application, storage system or cloud. Although moving data from one platform to another can be risky and costly, it also provides an organization with numerous benefits. For example, in addition to upgrading applications and services, organizations can boost their productivity and reduce storage costs.

Types of data migrations and their challenges

Data migration is typically performed using one of the following methods:

During data migrations, teams must pay careful attention to the following challenges:

Data migration strategies

Although implementation differs by migration type, there are still two main strategies organizations use: big bang and trickle migrations.

Big bang migrations transfer all associated data within a set time window. The advantages of creating a migration strategy around this method include lower cost, a quicker move and less complexity. The downside, however, is that big bang migrations require the system to be offline for the entire migration. There's also a risk of losing data if it isn't properly backed up to another location ahead of time.

Trickle migrations complete a data migration within phases. During the migration, both old and new systems run at the same time, so there's no downtime, which means there's less risk of losing data. However, trickle migrations are more complicated and need more planning and time to implement properly.

How to create a data migration plan

A data migration project can be challenging because administrators must maintain data integrity and time the project so there's minimal effect on the business and they can keep an eye on costs. Having a data migration plan helps to ensure there's minimal disruption and downtime to business processes.

Factors to consider during a data migration project include how long the migration will take, the amount of downtime required, and the risk to the business due to technical compatibility issues, data corruption or application performance.

Data migration planning should include the following general phases:

Examples of data migration tools include Microsoft SQL, AWS Data Migration Service, Varonis DatAdvantage and Varonis Data Transport Engine.

There are three broad categories of data movers: host-based, array-based and network appliances.

Data migration best practices

The following best practices should be used to protect data during a migration:

Data migration vs. data integration vs. data conversion

While data migration is the process of transferring data between data storage systems or formats, data integration is the process of combining data from multiple source systems -- creating a unified set of data for operational and analytical uses. The primary goal of data integration is to produce consolidated data sets that are clean and consistent. Integration is a core element of the data management process.

Data conversion is the process of changing data from one format to another. If a legacy system and a new system have identical fields, an organization could just do a data migration; however, the data from the legacy system is generally different and needs to be modified before migrating. Data conversion is often a step in the data migration process.

Follow these steps to help ease storage area network data migration challenges.

02 Dec 2022

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