Project Introduction:

A global leader in the tyre manufacturing industry, operating worldwide, was generating massive volumes of production, inventory, and customer data every single day.

Despite using multiple enterprise systems across plants, the company struggled with fragmented data, slow reporting cycles, and limited visibility across departments. Analytics requests often took three to four months to fulfil, delaying decisions and reducing agility.

That’s when the organization partnered with Credenca to unify their data landscape, automate data flows, strengthen governance, and transform data into a reliable foundation for faster decision-making.

What Made This Transformation Powerful:

• A unified Lakehouse platform consolidating global plant data
• Structured Medallion Architecture for clean, reliable datasets
• Automated data pipelines replacing manual reconciliation
• Purpose-built data products for business teams
• Strong role-based governance with secure access controls
• A scalable foundation ready for advanced analytics and AI

The Real Challenges on the Ground:

• Data scattered across ERP, production, and inventory systems
• No single source of truth across global plants
• Heavy manual data reconciliation processes
• Limited governance and unclear data ownership
• No ready-to-use datasets for dashboards
• Low trust in enterprise reporting

The result? Slow analytics delivery, operational blind spots, and difficulty scaling predictive initiatives.

How Credenca Simplified the Problem:

We designed a modern data platform built on Microsoft Azure and Databricks, consolidating fragmented systems into a single, scalable Lakehouse environment.

The focus was not just integration but structure, governance, and usability.

What We Did:

• Consolidated ERP, production, and inventory data into a centralized Azure-based Lakehouse
• Implemented Medallion Architecture (Bronze, Silver, Gold layers) for structured data refinement
• Automated data ingestion and transformation pipelines
• Applied role-based governance using Unity Catalogue
• Integrated data quality validation frameworks
• Created eight curated data products aligned with Sales, Supply Chain, Inventory, and Production
• Enabled dashboarding and advanced analytics readiness through Power BI and AI integration

The Impact That Mattered:

For Business & Leadership Teams

• Faster access to trusted enterprise KPIs
• Improved visibility across 50+ global plants
• Reduced dependency on manual reporting
• Stronger confidence in decision-making

For Operations & Teams

• Improved production data synchronization
• Standardized master data across systems
• Better tracking of inventory and workflows
• Reduced operational data inconsistencies

Measurable Results:

• Analytics turnaround reduced from 3–4 months to weeks or days
• 20% improvement in production data flow efficiency
• 10% reduction in customer master data inconsistencies
• Significant improvement in dashboard trust and adoption
• Stronger foundation for predictive and AI-driven initiatives

This engagement showcases how Credenca helps manufacturing enterprises transform fragmented data ecosystems into unified, governed, and scalable platforms using Microsoft Azure, Databricks Lakehouse, and Power BI, delivering faster decisions, stronger governance, and measurable operational impact.