A Full-Stack Commerce Data Platform, Built and Tested End-to-End

IDS delivered full-stack development (Java backend, React front end) with a dedicated QA workstream running in parallel from the start — functional, regression, and performance testing built into every sprint — under a single programme manager accountable for scope, timeline, and quality together.

Client

A Full-Stack Commerce Data Platform, Built and Tested End-to-End

About the project

Our solution

The Customer: Who they are

An omnichannel retail chain building a new internal platform to unify online and in-store commerce data for its operations teams.

The Challenge: Identifying the villain

A previous attempt at a similar platform, built by a different vendor, had shipped with minimal testing and generated a wave of production incidents that eroded trust in the whole initiative. “The business had already been burned once,” said the Head of PMO.

The Journey: The search for a solution

The retailer initially looked for a pure development shop to rebuild the platform quickly, but leadership was wary of repeating the same testing gap that caused the last failure.

The Discovery: Finding IDS

IDS was shortlisted specifically for its “Build / Validate / Manage” delivery model — testing embedded from day one rather than bolted on at the end.

The Solution: The hero arrives

IDS delivered full-stack development (Java backend, React front end) with a dedicated QA workstream running in parallel from the start — functional, regression, and performance testing built into every sprint — under a single programme manager accountable for scope, timeline, and quality together.

The Implementation: The battle

Delivery ran in two-week sprints with automated regression suites via Selenium expanding alongside new features, so quality didn’t degrade as functionality grew. The obstacle: integrating with a fragile legacy POS API; IDS built a resilient adapter layer with contract tests to catch upstream changes before they broke production.

The Results: The happy ending

  • Delivered on original timeline and budget 
  • Post-launch defect rate: significantly lower than the prior attempt 
  • Automated regression coverage: 80%+ of critical user flows 
  • Full knowledge transfer completed, internal team self-sufficient post-handover

“This is the first platform project that didn’t blow up in year one.” — Head of PMO

Technologies used: Java · React · Selenium · DevOps toolchain

Facebook
LinkedIn
Send on E-mail

More use cases

One Platform, Two Data Worlds: A Big Data Analytics Mart for Banking Group Controlling

Client: Leading Banking Group
IDS designed and built a new analytical data mart purpose-built for Controlling, constructed entirely on big data technologies rather than the client’s Oracle stack.

Migrating Without Missing a Beat: A New Data Warehouse Foundation for a Banking Controlling Team

Client: Leading Banking Institution
When the migration to the new DWH began, IDS took on the task of carrying that Datamart — and the business logic behind it — onto the new platform.

From Hadoop to Databricks: Scaling a Banking Data Platform Beyond Its Limits

Client: Banking Client
IDS Consulting was brought in to provide hands-on technical support and consultancy for the migration to Databricks.

From Days to Minutes: An 8-Year Data Warehouse Transformation for a Leading Telecom Operator

Client: Leading Telecom Operator
IDS Consulting was brought in not for a single fix, but as an ongoing extension of the client’s Data Warehouse team. The mandate: modernize how data moved through the platform, and keep it evolving safely as the business — and the underlying infrastructure — kept changing around it.

Full-Stack Data Platform with Embedded Testing & Knowledge Transfer

Client: A mid-size IT services company
IDS delivered the platform end-to-end (Python and .NET services, automated test coverage from day one) while running a structured knowledge transfer track in parallel — pairing IDS engineers with the client’s internal team throughout, not just in a handover week at the end.

Multi-Cloud Strategy & Cost Optimisation

Client: A growing SaaS / IT services company
IDS ran a cost and architecture review across both AWS and Azure environments, then designed a rationalized multi-cloud strategy — keeping each provider for the workloads it did best, eliminating duplicated pipelines, and applying rightsizing and reserved-capacity planning where waste was highest.