Executive Summary

A retail company successfully migrated its legacy Oracle on-premises database to a cloud-based Azure SQL Database. This initiative aimed to reduce infrastructure costs, improve system scalability, and enhance data accessibility across multiple retail locations. The project has achieved improvement in query performance while reducing operational costs.

About the Client

The client is a mid-sized retail company operating multiple locations, managing inventory, sales, and customer data through an on-premises Oracle database. As their business grew, the limitations of the legacy system, including high maintenance costs and scalability issues, became apparent. Seeking a more efficient solution, the client decided to migrate to a cloud-based Azure SQL Database. The migration aimed to reduce operational costs, improve performance, and enable centralized data access across all locations for enhanced collaboration and decision-making.

Problem Statement

The company was running an on-premises Oracle database to manage inventory, sales, and customer data across its retail stores. However, the system faced several challenges

High Maintenance Costs

The on-premises infrastructure required significant expenses for hardware upgrades, software licensing, and IT support.

Scalability Issues

The legacy system struggled to handle the growing volume of data and user requests during peak sales periods.

Limited Accessibility

The lack of centralized and remote data access hindered collaboration between stores and headquarters.

These issues prompted the company to explore a cloud-based solution for improved efficiency and cost-effectiveness.

Solution Overview

We decided to migrate its database to Azure SQL Database, leveraging Microsoft's cloud infrastructure to achieve scalability, accessibility, and operational efficiency. The migration process was carried out in the following phases.

Assessment and Planning

Analyzed the existing Oracle database structure, identified data dependencies, and developed a migration roadmap.

Data Profiling and Cleansing

Ensured data quality by addressing inconsistencies, duplicates, and errors before migration.

Incremental Migration

Conducted a phased migration to minimize downtime and validate data accuracy.

Post-Migration Optimization

Tuned the new database for performance and trained the staff for seamless operations.

Key Components

#1 Migration Strategy

Lift-and-Shift: Transferred the entire database to Azure SQL as-is, with minimal changes to application logic.
Incremental Loads: Used incremental migration to ensure continuity of business operations during the transition.

#2 Data Validation

Conducted thorough testing using scripts to validate data integrity and consistency post-migration.
Used Azure Data Studio for data comparison and SQL query validation.

#3 Performance Tuning

Optimized query performance using Azure SQL's automatic tuning and indexing recommendations.

Tech Stack & Tools

Cloud Platform

Microsoft Azure

Database

Azure SQL Database

ETL Tools

Azure Data Factory

Monitoring & Logging

Azure Monitor, Log Analytics

Data Validation

Azure Data Studio, custom SQL scripts

Backup & Recovery

Azure Backup

Results

47% Reduction in Operational Costs

Removing On-premises infrastructure results in 47% reduction in operational costs within first quarter, significantly improving its cost-efficiency.

30% Faster Query Execution

Azure SQL led to around 30% improvement in query execution times, reducing system latency and ensuring smooth operations during peak sales hours.

100% Increase in Scalability

With Azure SQL’s elastic, the system seamlessly handled all concurrent transactions during seasonal data spikes, ensuring high performance even under heavy loads.

22% Faster Data Retrieval

Centralizing data access improved collaboration and decision-making, resulting in 22% faster data retrieval across all retail locations.

Only 2 Hours of Downtime During Migration

The final migration process was completed with just 2 hours of total system downtime, ensuring minimal disruption to retail operations and a smooth transition to the cloud.

Team Composition

Project Manager: 1
Data Architects: 1
Cloud Engineer: 1
QA Analyst: 1
Support Engineer: 1

Testimonials

Our Slam Book

Tony Lehtimaki

DIRECTOR - AMEOS

Spain

Very professional, accurate and efficient team despite all the changes I had them do. I look forward to working with them again.

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CEO - BEESPOKE

France

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DIRECTOR - COVERTEK CERAMICA

Gujarat

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