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Published January 30, 2025
Article summary:
This article explains all the data migration process inside out, including the data migration types, the process of data migration, and the best practices.
Head of Database Migration Department, Ispirer Systems
What is data migration?
Data migration involves moving data from one place to another or from one storage system to a different one. It also encompasses converting data across various formats and applications.
Data migration includes data type mapping, which involves deciding how fields transition from the old database to the new system. The complexity of migration depends on the source and target databases, data structure, and volume. The primary objective is to transfer data efficiently, accurately, and securely, allowing organizations to handle their data seamlessly in the new setting.
The reasons for data migration
There are many reasons why companies initiate data migration. It might be essential to merge data from diverse sources into a single central repository accessible by various organizational divisions. This often happens following an acquisition, for example, when systems from different companies should be integrated or if systems are isolated across the organization. Poor data analytics can also be a reason for migrating data from one storage to another. Whether you are modernizing your database from the legacy one to the modern one, improving your database management opportunities or you are moving to the cloud, data migration is your go-to solution.
Data migration types
There are five common types of data migration:
- Database migration involves migrating not only data but also SQL code, including tables, indexes, and relationships. Basically, migrating from one relational database management system to another (for example, from SQL Server to MySQL) is like moving out from one house to another: everything should be organized in the same way but adapted to the new space. So whether you migrate a database or transform data, the process requires careful planning of a migration roadmap to avoid any troubles, such as data loss.
- Storage migration happens when data is transferred from one storage system to another. Often, companies need to upgrade to new technologies to achieve faster performance and more cost-efficient scaling. One frequent motivation for storage migration is enhancing storage systems to more advanced, contemporary solutions. This process includes transitioning from paper to digital formats, tapes to hard disk drives (HDD), HDD to solid-state drives, and hardware-based storage to cloud-based virtual storage. Storage migration is not driven by a lack of space but rather by a desire to upgrade the storage infrastructure.
- Application migration refers to the process an organization undergoes when it switches application software or changes its application vendor. This transition involves moving data from one computing environment to a different one. It is not easy because the operating systems, virtual machine settings, data storage solutions, and management tools can differ significantly. The good news is that the market is full of various middleware products that can help to solve this issue and simplify the process.
- Cloud migration, as it goes from the name, moves data from on-premises to the cloud storage environment or from one cloud environment to another. Given the complexity involved, organizations often rely on third-party vendors or service providers to facilitate data migrations. Specialists in information technology predict that we will keep seeing a rise in the global market share of cloud services. Most companies will utilize cloud technology before the end of the decade in 2030.
- Business process migration involves migrating business applications and moving data, such as customer, product, and operational metrics, to a new environment. The need for such a migration is often motivated by goals such as mergers and acquisitions, reorganization, or optimization that are crucial for maintaining a competitive edge or discovering new markets.
Data migration process
The data migration process includes the following steps:
1. Planning. In order to make data migration smooth and simple, you should not neglect the planning stage. This is the stage of an in-depth analysis of the source and target environments, determining the proper migration strategy. should not be neglected. Here the customer should decide which data migration strategy to choose, for example, the trickle method or the Bing Bang one. What is more, this is the right time to determine the budget, timeline, schedule and deadlines.
2. Data preparation. There are a number of pre-migration tasks to be set before starting the migration process. The main ones can include:
- Assess (profile) data sources, destinations and formats
- Inspect data quality, anomalies, or duplications
- Identify impacted users and potential disruption
- Define hardware, software, and security requirements
- Determine costs, staff, and data migration tools required
- Set a migration completion timeline
- Clean or reformat data
- Back up data and determining what to do with obsolete data
- Decide on a specific approach (Bing bang or the trickle method)
- Create risk mitigation and stakeholder communication plans
- Data backup. This is a mandatory step. All the best practices for data migration include advice to back up all the content you plan to migrate. Consequently, you gain an additional security measure against unforeseen data losses.
3. Migration execution. In case a company plans to migrate terabytes of data, then it is necessary to use third-party migration tools that automate migration. One of the examples of such a tool is SQLWays Wizard. The tool facilitates the migration of data and database schema. With its advanced features and comprehensive functionality, it automates migration of more than 40 RDBMSs, including Oracle, IBM DB2, Sybase, SQL Server, PostgreSQL, MySQL, and more. As soon as the data is successfully transferred, you can “go-live”, switch to the new database.
4. Post-migration. Data migration is the process that is not complete after “flipping the switch.” The results of the migration must be audited and validated to make sure everything has been correctly transferred and logged. Once the post-migration audit is deemed successful, the old system can be decommissioned.
Data migration best practices
While each data migration project has its requirements and involves its challenges, there are golden rules that will guarantee the companies transfer their data assets successfully.
- Hire a data migration team that will set up the right specialists to manage the project.
- Think carefully about the data migration approach (Bing bang or trickle)
- Consider data integration opportunities. Does a new system provide any data integration options?
- Use data migration as a chance to increase the data quality and clean data. Such a step guarantees easier data management in the future
- Assess the source and target environments carefully. Are there any database issues that should be resolved before the data migration?
- Verify business requirements and potential impact early in the process. What kind of migration timeline is necessary? How do the data security requirements are implemented? Are you sure about data integrity? Does it comply with data privacy policy within your company?
- Appropriately sizing the data to be migrated is essential. Data cleaning can help ensure that only valuable and relevant data is transferred.
- Before starting the migration, back up the data to prevent potential data loss.
- Dedicate ample time to the design stage, as it significantly influences the project's success.
- Avoid rushing to deactivate the old platform. There may be a situation in which the initial data migration attempt was not successful, and a rollback and another attempt are required.
Case study: From Oracle to PostgreSQL: migrating 12 TB of data in 12 hours
Customer: A provider of emergency response solutions
Source tech: Oracle
Target tech: PostgreSQL
Project scope: 24 databases, 500 000 LoC, 12 TB of data
Duration: 8 months
A Canadian provider of emergency response solutions needed to migrate 24 databases (12TB of data, 500,000 LoC) from Oracle to PostgreSQL. A key challenge was migrating such a large volume of data while maintaining ongoing software development and adhering to a strict 12-hour downtime window. Ispirer used a combination of automated migration with Ispirer Toolkit, pre-migration of cold data, manual adjustments, and close collaboration with the client's QA team for testing. The database migration was completed in 8 months, including schema conversion, testing, database updates, and the final production migration. The data migration was completed successfully in just 12 hours. A portion of the business logic was also moved from the database to the application level.
Read the full case study: From Oracle to PostgreSQL: migrating 12 TB of data in 12 hours
Bottom line
Our blog offers comprehensive coverage of migration-related topics, including SQL and data migration strategies, best practices, and valuable insights in data transformation. We will continue our exploration of data migration in upcoming posts. Follow our updates to receive a detailed guide on data migration using SQLWays Wizard.
If you are planning a database migration project and need a solution that will make you confident about the whole migration process, SQLWays Wizard is your go-to choice. Book a meeting with our experts to discuss the details of your migration project, or check out the pricing.