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Technology industry: Migrating on-premises systems to AWS cloud

Brief Overview

A leading grocery retailer sought to integrate intelligent automation and artificial intelligence into its fresh produce supply chain to ensure consistently high product quality across stores. The organization required a reliable technology partner with proven expertise in implementing AI-driven retail solutions. By transforming the existing data infrastructure and leveraging real-time machine learning insights, DC Tech delivered a scalable and future-ready solution that reduced operational costs, enhanced inspection accuracy and significantly improved overall supply chain efficiency.

INDUSTRY

Retail

KEY SOLUTIONS

Integrated data workflows, robust data governance, AI-driven capabilities and next-generation data infrastructure transformation.

KEY TECHNOLOGIES

Databricks, Machine Learning, AI, Cloud

MEET THE TEAM

MIKE.P

VP CONSULTING SOLUTIONS
DATA & AI

JATIN PAL

SVP BUSINESS PARTNER

RAJ KUMAR

MANAGER
SOLUTIONS DELIVERY

Discover the power of partnership

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Challenge

A global technology organization specializing in consumer electronics, software, and digital services was operating multiple on-premises payment, financial, and network traffic applications. To improve scalability, flexibility, and cost efficiency, the company aimed to accelerate the migration of these systems to AWS. However, several challenges needed to be addressed during the transition from on-premises infrastructure to the cloud, including:

Architecture and infrastructure design

Developing a scalable and high-performance cloud architecture capable of supporting business workloads in the AWS environment.

Container integration

Implementing containerization to enable seamless deployment and management of applications within the AWS ecosystem.

Traffic management optimization

Establishing effective traffic routing and management to maintain system stability and ensure uninterrupted performance.

Secure data migration and integration

Preserving data accuracy, integrity, and consistency while transferring and integrating datasets during the migration process.

Challenge Image
Background

Solution

To overcome these obstacles, DC Tech designed and deployed a cloud-based data ecosystem powered by Databricks. The solution incorporated real-time streaming workflows, structured datasets built on a Medallion framework and AI-powered quality assessment models that enabled inspectors to make informed decisions instantly. This end-to-end transformation strengthened cold-chain management and equipped the retailer with actionable insights to minimize spoilage risks during transportation.

This comprehensive solution optimized cold-chain operations and gave the grocer the insights needed to reduce the risk of food going bad in transit.

Data Acquisition Framework

The team built robust pipelines to collect data from both internal systems and external applications (e.g., temperature sensors, logistics platforms).

Data preparation and reporting

Data was curated, standardized and presented in accessible formats for internal stakeholders.

Data harmonization

DC tech joined data from multiple systems to create a unified Fresh Domain Data layer.

A PROGRESSIVE DATA JOURNEY

ANALYTICS

Uncover improvement opportunities

OPERATIONAL INSIGHTS

Extract meaningful next steps

REAL-TIME ADJUSTMENTS

Empower active participation in day-to-day decisions

For instance, data analysis might indicate that temperature-sensitive items such as leafy vegetables and bananas are regularly subjected to elevated temperatures while being transported from distribution hubs to retail outlets. With these insights, leadership teams can pinpoint operational gaps, initiate corrective actions and address underlying causes. This proactive approach significantly minimizes the likelihood of customers encountering spoiled or compromised fresh produce in stores.

Deliverables

Scalable supply chain intelligence

Developed and deployed a comprehensive cloud-first architecture to enable advanced, real-time analytics across the entire supply network.

Secure and governed data ecosystem

Established centralized data governance using Databricks Unity Catalog to streamline access management, enforce policies and maintain consistent metadata standards. Integrated robust validation, testing and monitoring mechanisms to preserve data integrity and reliability over time.

Optimized data processing framework

Adopted a Medallion-based architecture within Databricks, implementing Bronze, Silver and Gold layers to ensure structured processing, improved traceability and enhanced data lineage visibility.

Deliverables Image

Project outcomes

The grocery retailer effectively embedded AI into its core operations and experienced rapid results, including improved product freshness and greater efficiency across supply chain processes.

The project delivered several non-quantitative improvements:

30%

Reduction in food waste

35%

Faster operational response

20%

Improved inventory visibility

45%

Better cold-chain monitoring

Custom solutions to achieve your goals

From strategy to implementation, we provide the knowledge and leadership our clients rely on to accelerate their business. Our proven team takes a unified approach to driving large-scale change and unlocking new opportunities for growth and success.