Optimizing Cloud Data Engineering for a Global Enterprise
A global enterprise faced increasing pressure to modernize its data infrastructure and reduce operational costs. The company needed to unify data from multiple ERPs and business systems, optimize transformation processes, and support real-time analytics. Their existing setup lacked scalability, resulting in high storage expenses and slow access to insights.
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Challenge
Legacy data pipelines and fragmented systems made it difficult for the client to make timely decisions and operate efficiently. They needed a scalable, pay-per-use cloud platform to streamline data workflows and boost performance.
Inefficient Data Workflows
Integration and Real-Time Visibility Challenges
Solution
Innovation Strategy
Entrans implemented a cloud-native, AWS-based data engineering platform designed for real-time performance and cost efficiency. The solution focused on automating data integration, transformation, and querying across multiple source systems.
Collaborative Approach
Our teams worked closely with the client’s IT and BI stakeholders across a three-phase execution roadmap—from architecture design to transformation workflows and full-scale deployment.
Key Initiatives
- Architected a curated data lake using Amazon S3
- Used Amazon Redshift for fast analytics and query processing
- Integrated Amazon EMR for semi-structured data transformations
- Enabled Athena for efficient, serverless querying
- Built automated pipelines using GitLab, Jenkins, Azure DevOps, and Octopus Deploy
Business Transformation
The client now operates on a centralized, real-time data platform with reduced infrastructure overhead. With fast, reliable insights, business teams can respond quickly to trends and opportunities.
Future-Ready
With scalable cloud infrastructure and real-time querying in place, the organization is now positioned to roll out predictive analytics, AI-driven dashboards, and enterprise-wide data products.
Client Quote
"Entrans provided us with a game-changing data engineering platform that significantly improved our data processing speed and efficiency. The cloud-based architecture has reduced our costs while enabling real-time analytics, transforming how we make business decisions."
— Client Representative, Global Enterprise
Key Takeaways
- Built a cost-optimized, AWS-based data engineering platform
- Integrated data from multiple ERPs into a real-time analytics layer
- Reduced query times and enabled faster decision-making across teams
Outcomes
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50% reduction in query time — from minutes to milliseconds
Seamless data integration across PoS, ERP, and external sources, with enhanced data accessibility through indexed and curated datasets
Cost savings achieved through pay-per-use compute and storage
