What Is Data Migration and Its Types?

Nearly around 80% of the world’s population use various types of computer networks in order to communicate and transfer data from one place to another.

But, what if I ask you how data is transferred from one place to another or what is data migration? Most of us won’t have a proper understanding of this term. So let’s dive deeper into the article in order to understand this term.

You can also explore: Types Of Computer Networks

So what exactly is data migration and its types? Before answering this question, let’s quickly go through the topics we will cover in this blog related to data migration.

• What is data migration
• Data migration example
• Types of data migration
• Data migration tools
• Data migration steps
• Data migration challenges

What is data migration

Data migration definition: The process of moving an organization’s data, applications, and digital systems from one location to another is known as data migration. It can, however, also refer to transferring data from one format to another or from one application to another.

You can also explore: What is networking?

Data migration is a one-way trip that ends once all of the information has been transferred, and it is a critical component of an organization’s overall data management strategy. Organizations migrate data for various reasons, such as upgrading a database, establishing a new database, merging new data from other sources, transferring data to a new computing environment (e.g., the cloud), and so on. There are several key factors to consider regardless of the type of data migration you are undertaking, such as data integrity, business impact, cost, potential downtime, data assessment, user experience and impact, and data quality. Regardless of the specific reason for the data migration, the overall goal is to improve performance and competitiveness.

You must explore: Networking Basics – A Beginner’s Guide

Many of us get mixed up between data migration and data integration. Let us try to understand it in a simple way to clear it up. As stated above, data migration is a one-way trip that concludes once all information has been transported to the desired location. Data integration, on the other hand, can be a continuous process involving real-time data streaming and information sharing across systems.

Data migration example 

Some of the most common data migration examples are:

• Merging new data from other sources.
• Moving data to a new storage device to replace an old system.
• Moving data from on-premises to cloud storage as it provides better services and security.

You can also explore: What is LAN (Local Area Network)?

Types of data migration 

There are many types of data migration. Some of the most common data migration types are:

Database migration

Definition: The process of migrating data between two database engines is known as database migration.

This migration is used to move an entire database from one vendor to another or upgrade the current database software. Because there are numerous small tasks associated with the process, such as deciding the storage capacity of the target database, testing applications, and ensuring the confidentiality of data, this type of data migration necessitates careful planning and testing.

Application migration

Definition: The process that occurs when an organization switches from one platform or vendor application to another is called application migration.

Moving the entire application from an on-premises IT center to the cloud and moving between clouds are all examples of this type of migration. Because almost every application operates on a specific data model, changing an application vendor necessitates a significant transformation.

Storage migration

Definition: The process of migrating data from one storage system to another, such as a hard disk or the cloud, is known as storage migration. 

Storage migration involves moving physical blocks of data from one type of hardware. This type of data migration offers significantly faster performance and more cost-effective scaling while enabling data management features such as snapshots, cloning, backup and disaster recovery, etc.

Cloud migration

Definition: The migration process of data or applications from an on-premises location to the cloud or from one cloud environment to another is called cloud migration.

Moving to the cloud ensures scalability, necessitates fewer storage resources and saves money. The migrated data is protected by the cloud’s firewall, which is easily implemented using cloud data migration tools.

Data migration tools 

Data migration is a time-consuming task that would necessitate a significant number of human resources to accomplish manually. As a result, it has been automated and is done programmatically using tools designed for the purpose. Various tools can help you in completing the data migration process. Some of the most popular data migration tools are: 

• Hevo: This tool allows you to replicate data in near real-time from 150+ sources to the destination of your choice, including BigQuery, Redshift, Snowflake, and Firebolt, without writing a single line of code. 
• Fivetran: This tool provides automated data migration on a fully managed ELT architecture. Because of its idempotent core architecture, it is resistant to data duplication and failure and thus minimizes computational costs. Fivetran reduces the need for user maintenance and guarantees 99.9% uptime.
• Matillion: This tool is a cloud-based ETL platform that allows you to migrate, extract, and transform your data in the Cloud. This tool enables you to gain new perspectives and make more informed choices.
• Dextrux: This tool helps you with self-service data ingestion, streaming, transformations, cleansing, preparation, wrangling, reporting, and machine learning modeling.
• DBConvert Studio: This tool is the most suitable for database migration and synchronization. It supports ten of the most popular on-premises databases, including SQL Server, MySQL, PostgreSQL, Oracle, and more.
• AWS Data Migration: Amazon owns this tool, one of the best-suited tools for cloud data migration. It helps to migrate databases to AWS securely and efficiently.

You can also explore: What is a Wireless Networking?

Data migration steps 

There are six data migration steps or stages that complete a data migration process, and by using these steps, you’ll be able to successfully move your data from the source to the target system. These data migration steps are:

1. Project scoping: In this step, you draw a complete plan that sets out critical areas of the project’s structure before the project starts. This plan is made after considering various factors such as stakeholders and their required deliverables, budget, deadlines, the data’s current format, location, what format it should be in post-migration, etc.
2. Resource evolution: In this step, you assess the resources that you are thinking to use for completing the data migration process. The following are some critical questions about the data migration software or tools used for the project: how flexible is your preferred migration tool? Is there a match between the skills of the project team members?
3. Create back up: In this step, you ensure all of your data is backed up, especially the files you’ll be migrating.
4. Execute plan: In this step, you closely monitor your data migration during the process in order to spot and address any issues that may arise.
5. Test system: In this step, you ensure all data migrated is correct, secure, and in the proper location. In order to verify this, you can conduct unit, system, volume, web-based application, and batch application tests.
6. Follow-up and maintenance: In this step, you thoroughly audit the system and data quality in order to ensure everything is in place and order after completing the data migration process. If you discover errors, missing, incomplete, or corrupt data, restore it from a backup.

Data migration challenges 

An individual or an organization can face many challenges while completing the data migration process. Some of those challenges are:

• Data loss: Data can be lost during migration; therefore, it is critical to back up and plan the migration meticulously with the assistance of professionals.
• Incompatibility between old and new data formats: This can occur when data is transferred from one system to another that utilizes a different database structure or when data is transferred to a new system that employs a different file format.
• Lengthy process: A common data migration challenge is that it can be time-consuming, especially if you have a large amount of data to migrate. The total time required to complete this process is determined by various factors, including the size of your data, the number of data sources, the speed of your network connection, and so on.
• Unclear requirements: Uncertain requirements can cause misunderstandings and miscommunication between the migration team and the business stakeholders.
• Lack of documentation: It can be difficult to understand the data and how it should be migrated without documentation.
• Complex data structures: When migrating data from one system to another, an issue may arise because the data may not fit into the new system’s structure.
• Inadequate data quality: If data on the source platform is incomplete or inaccurate, it can cause issues when migrating to the destination platform.

Conclusion

Data migration enables us to consolidate our data in a single storage system, such as a cloud data warehouse. Organizations migrate data for a variety of reasons. They may need to redesign an entire system, upgrade databases, create a new data warehouse, or merge new data from an acquisition or another source.