As organizations receive data in various formats from different systems, their existing infrastructure may require upgrading to larger systems or migrating data to alternative platforms. But what is data migration? How does it work?

In essence, data migration enables organizations to expand their data storage and management capabilities, allowing them to fully leverage data to drive business decisions. It is a widely adopted process of transferring data, and almost every organization undertakes it at some point.

Following a proper plan to migrate critical data using efficient tools is crucial.

This article will discuss the basics of what is data migration, why it is needed, how to create an effective data migration plan, and much more. Let’s begin by defining the process.

What is Data Migration?

Data migration is the process of transferring data from one location to another, from one format to another, or from one application to another. It is a key consideration for businesses that are looking to modernize their IT infrastructure, consolidate data silos, or transition to cloud-based systems.

These are some common situations that require data migration:

  • Replacing, upgrading, or expanding storage systems and equipment
  • Migrating from legacy software to newer versions or entirely different applications
  • Businesses transitioning from local storage systems to cloud-based platforms to optimize operations 
  • Consolidating multiple websites or web properties
  • Implementing new systems that need to coexist and interoperate with existing applications
  • Performing infrastructure maintenance tasks
  • Centralizing databases to achieve interoperability
  • Consolidating multiple information systems
  • Relocating data centers

Data migration strategy is a critical element in this process, encompassing the planning and decision-making involved in moving data from one system to another.

Data Migration Process

The process of data migration typically involves several key steps:

  • Data Mapping: Data mapping documents how data fields from the old system correspond to data fields in the new system. It identifies data discrepancies between the systems that must be addressed. This upfront mapping sets the stage for the extraction and transformation steps.
  • Data Extraction: Data is extracted from the legacy source systems based on the data mapping. Extraction scripts pull the required data out of the source databases/files and make it available for loading into the new system.
  • Data Standardization: Extracted data often needs to be standardized or transformed to match the data model used in the new system. Standardization includes activities like renaming fields, formatting, deduplication etc. This is done programmatically by writing data transformation scripts.
  • Data Loads: Once data is extracted and standardized, it is finally loaded into the new target system. This is done in batches through scripts that handle inserts and updates of large data sets.
  • Data Pipelines: For large data sets, data migration is executed through automated data pipelines. These pipelines allow sequential orchestration of the extract, transform and load processes with sufficient flexibility.
  • Reconciliations: Data counts are compared between source and target systems to ensure completeness of the migration. Summary checks and control totals can also be used to validate successful data migration.

By incorporating a data migration checklist, organizations can enhance the efficiency and reliability of their data migration efforts, ensuring a smooth transition with minimized risks and disruptions.

Impact of Data Migration on Business Operations

The impact of data migration on business operations can be substantial. A successful data migration can help businesses:

  • Improve data accessibility and availability by consolidating data into a centralized location or cloud-based platform.
  • Enhance data integrity and security by implementing modern data management practices and leveraging the robust security features of cloud platforms.
  • Increase operational efficiency by streamlining data processes, reducing redundancies, and automating manual tasks.
  • Facilitate better decision-making by providing a comprehensive view of data across the organization.
  • Reduce infrastructure costs by retiring legacy systems and leveraging the scalability and cost-effectiveness of cloud computing

Data Migration Tools

Data migration tools can greatly simplify and streamline the migration process. These tools often provide automated mechanisms for data extraction, transformation, and loading, reducing the risk of manual errors and accelerating the overall migration timeline. 

A vital component of successful data migration is the utilization of a reliable Data Management Service, which helps streamline the entire process. It provides comprehensive solutions for organizing, storing, and transferring data efficiently

Data migration in cloud computing is a common scenario, as more businesses are transitioning to cloud-based platforms and services. Cloud migration involves moving data and applications from on-premises infrastructure to a cloud environment, such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform.

Cloud providers and third-party tools, including data migration software, offer various data migration services and solutions to simplify and streamline the migration process, ensuring secure and reliable data transfer to the cloud. 

Why Choose IntoneSwift?

Thus, by migrating data to the cloud, organizations can benefit from increased scalability, flexibility, cost optimization, and access to advanced cloud-native services and technologies. Whether you’re switching to a better storage system, or moving to the cloud, IntoneSwfit is a tool that can assist you in achieving all of your necessities. It offers:

  • Knowledge graph for all data integrations done
  • 600+ Data, and Application and device connectors
  • A graphical no-code low-code platform.
  • Distributed In-memory operations that give 10X speed in data operations.
  • Attribute level lineage capturing at every data integration map
  • Data encryption at every stage
  • Centralized password and connection management
  • Real-time, streaming & batch processing of data
  • Supports unlimited heterogeneous data source combinations
  • Eye-catching monitoring module that gives real-time updates

Contact us to learn more about how we can help you!