What is Data Migration?
Data migration is the process of migrating the data from one system to another or one location to another, or from one data format to another. With the modernization effort going on in various industries, many companies are trying to migrate their existing data from private cluster to cloud based environment. In this blog post, we’ll delve into the explore data migration process, its importance, challenge and best practices.
Types of Data Migration?
There are many advantages a firm can have when migrating the data from an existing inefficient system to a cloud based system.
There are mainly three types of migration that are popular.
- Storage Migration
- Application Migration
- Cloud Migration
- Database Migration
- Data Center Migration
Why do we need Data migration ?
There are many scenarios in which data migration needs to be performed.
- Upgrading and replication Legacy pieces of software
- Migrating a Data Centre
- Maintain or Upgrading Infrastructure
- Migrating data from Private data center to Cloud
- Replacing, Upgrading, and Expanding existing storage systems hardware
Data Migration Challenges
Since Data migration is a complex process, there can be several challenges that may arise when organizations start this journey. Below are the common challenges.
- System Compatibility Issues
- Data Formatting Issues
- Data Quality issues
- Data loss or Corruption
- Testing and Quality Assurance
- Security and Privacy
- Downtime and Business Disruption
Best Practices and Steps for Data Migration
There are many ways to do Data Migration. But there are some best practices one can follow when migrating the data. Important ones are listed below.
- Planning and Strategy: Develop a detailed migration plan that includes objectives, scope, timelines and all the pre- and post-migration validation steps
- Assess and Data Preparation: Make sure to clean, transform and validate the date.
- Choosing right tool for the Job: Use automated tools, software and Scripts instead of following manual ones
- Testing and Validation: Prepare a robust Test plan to avoid data loss or corruption to ensure the data integrity and functionality.
- Execution and Monitoring: Monitor the data in real-time when it gets migrated in phases.
- Decommission: Make sure to get rid of old system once data migration is completed successfully.
- Communication and Documentation: Communicate with the stakeholders and product owners throughout the process
Conclusion
Data migration is a complex process that requires careful planning, execution and testing. In this blog post, we learned about data migration, its types, challenges and its best practices.
