Data Migration : Seamlessly Transition Enterprise Data from On-Premise to Cloud Infrastructure

In today’s fast-evolving digital landscape, enterprises are under increasing pressure to modernize their data infrastructure. One of the most impactful transformations is the shift from traditional on-premise systems to scalable, cloud-based environments

Our company helps organizations seamlessly transition their enterprise data to the cloud, helping reduce complexity, improving scalability, and unlocking the full potential of modern data platforms. Through careful planning, robust architecture, and managed services, we ensure that the migration process is smooth, secure, and strategically aligned with business goals.

High-Level Overview

To modernize their data ecosystem and reduce costs, our customer initiated a strategic shift from an on-premise Hadoop-based data lake and warehouse to a cloud-native architecture using Amazon Web Services (AWS). The key driver of this initiative was not only the high licensing costs of existing ETL tools, but also the pressing need to modernize the company’s big data infrastructure. Over time, the data lake had accumulated large volumes of legacy and duplicated data, increasing complexity, reducing efficiency, and making data governance difficult. To address these challenges, the customer adopted AWS Glue as a serverless ETL (Extract, Transform, Load) solution and Amazon S3 as the central cloud storage platform. This shift significantly reduced operational overhead by eliminating licensing fees and enabling pay-as-you-go scalability. To further support efficient, real-time analysis, Amazon Athena was integrated as a serverless SQL query engine, allowing users to explore data directly in S3 without provisioning or managing infrastructure.

The project was executed in two main phases:

1. Migrating and transforming existing on-premise data to align with a new, cloud-based design.

2. Creating a new data pipeline to process raw data from source systems directly into the AWS cloud platform.
   

Using Glue, we back up, cleaned, enriched, and transformed data for both legacy and new data sources. Data was stored efficiently in S3 buckets, enabling secure, scalable, and highly durable storage. Athena provided analysts and developers with easy, direct access to query structured data using familiar SQL syntax, without the need for additional compute provisioning.

Key Challenges Encountered

• Incomplete Master Data / Reference Tables Enrichment logic relied on reference data that was not yet available, causing processing delays and temporary reliance on sample data.

• Inconsistent Data Sources Significant differences between on-premise data and live source systems required separate ETL logic, increasing complexity.

• Evolving Design Requirements Changes to data models mid-project introduced rework and impacted delivery timelines.

• Table Dependencies Interconnected tables created sequencing challenges and bottlenecks in processing.

• Multiple Sources of Truth The customer’s legacy environment included scattered, redundant datasets. A major goal of this project was to consolidate and streamline these into a single source of truth to help make data easier to govern, analyze, and trust.

  
  

Despite these hurdles, our cloud-native approach with Glue, S3, and Athena laid a scalable and cost-efficient foundation for the customer’s future data initiatives which unlocks faster insights, improved data quality, and simplified operations.

Why Choose Our Data Migration Solution?

Migrating enterprise data to the cloud involves more than just moving files, it requires smart orchestration, reliable execution, and the ability to adapt to changing requirements. Our team delivers end-to-end data migration services that ensure a smooth transition from on-premise Hadoop environments to AWS cloud infrastructure. Using AWS Glue and Athena, we manage everything from data backup to transformation, enrichment, and pipeline development, while minimizing downtime and aligning with evolving business needs.

Key Benefits

• Seamless Cloud Transition Smooth migration from Hadoop-based systems to AWS S3 with minimal disruption.

• Modern, Scalable Architecture A future-ready design that supports both batch and real-time data processing.

• Improved Data Quality Integrated cleaning and enrichment processes ensure accuracy and consistency.

• Adaptability to Change Flexible approach to handle design updates, interdependencies, and incomplete reference data.

• Full Managed Support Continuous guidance, monitoring, and optimization throughout the migration lifecycle.
  

Why EXPECC?

Our experience has helped us deliver benefits to our clients, including:

• Improved Data Quality: By centralizing and standardizing data, this ensures data accuracy and consistency.

• Enhanced Data Accessibility: A unified data system makes it easier for users to access and analyze information.

• Better Decision-Making: Reliable and integrated data enables more informed and effective decision-making.

• Increased Efficiency: Streamlining data management processes improves operational efficiency.

• Comprehensive Reporting: A unified data view facilitates the creation of comprehensive and insightful reports.

• Cloud-Native Expertise: Deep knowledge of AWS services like Glue, Athena, and S3, enabling efficient, cost-effective solutions.
  

Our deep expertise and proven best practices in Data Migration ensures that we deliver reliable and effective solutions for our clients.