Data Migration: A Key Role for Solutions Architects - A Preamble

As part of my promised lab series in the life of a Solutions Architect, I wish to dive into Data Migration and explore why it is such an important concept today in the cloud and on-premise production environments.

Data they say is king. A lot of it is generated every day. As of 2025, the world generates approximately 402.74 million terabytes of data every single day. This includes everything from emails, social media posts, video streams, online transactions, sensor data from smart devices etc. The importance of data cannot be overemphasized due to the varied means by which is applied. This varies from healthcare to finance to transportation and to government and this is to mention a few.

Data is harnessed in various forms today and this is typically done in the following ways; Collection, Storage, Processing & Cleaning, Analysis, Visualization, Decision Making and Automation & AI. In all these forms, data is required to be in a certain form and way for it to perform the task it is designed for. Today data can be broadly organized into three classes; Structured(Organized in rows and columns e.g.. databases and spreadsheets), Unstructured( without predefined format like emails, videos, social media posts) and Semi-structured(a mix of the some structure and not rigid like XML, JSON files)

Due to the very dynamic nature of data today, it becomes imperative that it would be moved from one place to another. This is also known as data migration. Some of the key reasons why data migration has become a very important exercise today include the following; Cloud Adoption(moving from on-premises servers to cloud platforms like AWS, Azure, GCP etc.), System upgrades(Businesses can decide to upgrade legacy systems(like CRMs or ERPs) to modern platforms), Data Centre relocations, Mergers & acquisitions(Combining businesses would need to fuse their IT systems and databases), Compliance and security and Analytics and AI to mention a few.

In the post, I wish to narrate some of the data migration experiences of mine in recent times. This is enable for documentation and arouse some positive reactions from those who are also involved in this exercise. I will be focusing on structured data cutting across the AWS cloud platform and popular database offerings like Microsoft SQL, Oracle, MySQL and PostgreSQL. Some of the tools used in data migration like AWS Database Migration Service(DMS) and AWS DataSync. Also I will be looking at such services such as Assessment & Planning, Data Mapping & Transformation, Testing & Validation, Backup & Recovery etc.

In the next post, I will continue with how a database in an on-premise environment can be migrated to the AWS cloud. Therein we will explore what AWS RDS means and also look at the concept of homogeneous and heterogenous database migration.