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What Is Data Migration?

Data migration is the practice of transferring data from one storage structure, platform or location to another. Businesses in diverse industries may need secure migration procedures for different uses, including changing storage systems, updating technology and more. Data migration helps IT managers and data professionals mitigate security, data integrity and cost risks.

Understanding Data Migration

Data migration includes the preparation, transfer and processing of data between systems. Usually implemented when organizations introduce new systems, data migration can involve the following:

  • Storage locations
  • Databases
  • On-premises to cloud
  • Application
  • Data center

These migration use cases, or types, involve moving data from one data environment to another. Careful migration can minimize or prevent data loss, enhance security and maintain data integrity during substantial system changes. This supports the efforts of IT managers and data professionals responsible for large volumes of data in modern organizations.

Data Migration Strategies

Planning your migration strategy should incorporate efficient and secure data extraction, processing and loading. A comprehensive strategy provides support pre-, during and post-migration. It also includes migration support mechanisms like data inspection, system backups, validation and post-loading analysis and monitoring. You can manage these steps using two common strategies:

  • Big Bang Migration: This approach involves one mass data system transfer for swift and more affordable migration. Implementing this approach often results in system downtime and failures as significant systems need to collaborate in the migration. It is a better approach for smaller institutions with less data who may not feel the effects of absolute system downtime profoundly.
  • Trickle Migration: This is a more phased migration technique that sections data transfers into steps. Older systems function parallel to the new structures with limited to no downtime, making trickle migration ideal for larger or big data entities. Planning and executing effective trickle transfers can require complex planning and cost more than the big bang approach.

Potential downtime or migration speed, data volume, data types, receiving and transferring environments and costs are essential factors to consider when planning your migration.

Migration Implementation: Risks, Best Practices and Tools

Data migration allows you to modernize and maintain your data systems. There are risks to consider and plan for when preparing your system transition.

Mitigate data migration risks with these best practices:

  1. Estimate and account for transfer times and potential downtime by working with IT professionals to counter bottlenecks and evaluate efficient migration.
  2. Encrypt and secure your data before beginning migration. Prepare the export and import locations with advanced security features for the transfer to minimize data loss and maintain integrity.
  3. Collaborate with data users to ensure migration occurs in the right format and meets their application needs and data quality standards after the process.
  4. Ensure the source and target systems can support seamless transfers and store the data in necessary formats and schema.

There are many popular migration tools available for diverse user needs. Evaluate your strategy, migration type and system requirements to help you determine your best option. Anomalo can help with governance software for data quality and integrity and data validation tools for pre- and post-migration data checks.

Make Protected Data Moves With Anomalo

Data migration has inherent risks that organizations can alleviate with advanced preparation, careful strategies and secure tools. By implementing migration best practices and utilizing data technologies like Anomalo, you can ensure optimal migration results, including top data quality, security, integrity and structuring.

Learn more about protecting your data during big moves with Anomalo.