Project Overview
Managing product master data across multiple sources and systems had become a slow and resource-heavy process for a global enterprise. Weeks, sometimes months, were lost in transforming data into usable formats, all while heavily relying on IT and integration teams. Cubet engineered a Talend-based data management platform that redefined how the business handled its data. What used to be a bottleneck is now a streamlined, business-driven operation. Product data transformation cycles that once dragged on for weeks are now completed in a matter of days, empowering business users to take control, reduce operational delays, and drive better decision-making across the organisation.
Industry
Enterprise Product Data Management
The Client
A multinational product-centric enterprise handling high volumes of product master data across global markets. Their data ecosystem was complex, distributed, and deeply dependent on legacy processes that created silos between business teams and data operations.
Challenges Addressed
The organisation faced a range of operational bottlenecks and technical hurdles:
- Massive product data volumes arriving in inconsistent formats from multiple systems
- Prolonged transformation cycles that required hands-on involvement from technical teams.
- Limited reusability of data workflows, leading to redundant development efforts.
- Lack of visibility and control for business users who depended on IT for every data task.
- A need to future-proof data pipelines for scalability and ongoing digital transformation.
The core challenge wasn’t just technical; it was structural. The process needed to shift from an IT-led operation to a scalable, business-led model that still upheld the rigour of enterprise-grade data management.
Collaboration in Action
Cubet’s engagement began with a focused discovery phase to map the client’s data flow, operational pain points, and transformation patterns. By working closely with both business stakeholders and IT teams, Cubet ensured the solution addressed not only the technical requirements but also enabled usability and ownership at the business level. The collaboration delivered a modular, scalable system that dramatically reduced manual intervention and gave analysts direct access to critical data workflows, without the need for deep technical skills.
Technologies Deployed
The solution combined enterprise-grade technologies and automation capabilities, including:
- ETL Platform: Talend Data Integration as the core data processing engine.
- Custom Logic Layer: Java-based routines for client-specific transformation rules.
- Data Storage: PostgreSQL for structured data and AWS S3 for raw file management.
- Workflow Orchestration: Talend Job Conductor integrated with custom scripts
- Deployment Environment: Initially on-premise, with a roadmap towards hybrid cloud adoption on AWS.
- Security Protocols: Role-based access control with robust data encryption—both in transit and at rest.
Innovative Feature
The introduction of a Reusable Job Library and a User-Friendly Interface marked a clear shift from traditional ETL models. The reusable job modules allowed rapid deployment of recurring data processes with minimal rework. A simplified front-end layer enabled non-technical users to trigger, monitor, and manage data pipelines independently. By embedding business-specific transformation logic into the platform via custom Java routines, the solution provided consistency, reusability, and speed, all in one package.
Value Delivered
- Data transformation timelines reduced from several weeks to just 2–3 days.
- Over 60% reduction in dependency on integration and IT support teams.
- Business users gained autonomy to execute critical data operations without coding.
- Greater consistency and accuracy in data outputs across systems.
- Positioned the organisation for downstream analytics, reporting, and AI use cases.
The immediate results included faster time to market for product launches and improved responsiveness to market changes. Long-term, the solution became a scalable foundation for future digital initiatives.
User Feedback
Business analysts praised the newfound control and transparency over data tasks, while IT leadership reported reduced workloads and increased standardisation. Teams noted a sharp drop in rework and support tickets, with data quality issues becoming far less frequent. The shift in ownership allowed both technical and non-technical teams to work in parallel, boosting overall productivity.
Conclusion
This project was not just about accelerating data processing—it was about redistributing ownership, breaking operational silos, and setting up a scalable model for enterprise data management. With Cubet’s Talend-powered solution, the client replaced outdated, manual workflows with reusable automation and intuitive interfaces. What once required specialist intervention is now a self-service model built for speed and growth.
Impact Made
The transformation made product data management a core business capability, not just a backend process. Teams now act on insights faster, launch products quicker, and operate with confidence in their data. Beyond improved timelines and autonomy, the platform has become a strategic asset, powering analytics, fuelling automation, and forming the data backbone for the client’s next generation of digital transformation.