Turning enterprise data into operational insight.

01 / Customer experience

Situation

Ludhiana Beverages Pvt. Ltd. (LBPL), a trusted Coca-Cola bottling partner for more than three decades, operates high-volume production plants and a wide distribution network across Punjab. With daily operations spanning manufacturing, inventory management, logistics, and market execution, LBPL generated a growing volume of data from a variety of systems.

However, this data lived in deep silos-spread across ERP platforms, production line equipment, warehouse systems, sales applications, and route-to-market tools. Each department relied on separate datasets stored in isolated databases or spreadsheets, creating disconnected pockets of information.

Because the systems could not communicate with each other, LBPL lacked a unified, organization-wide view of performance. Leadership teams struggled to access timely insights needed to make data-driven decisions, and analysts spent significant time manually stitching data together. The absence of integrated, cleansed data made it difficult to identify bottlenecks, optimize operations, or respond quickly to market changes.

LBPL recognized the need for a modern analytics foundation that would break down data silos, unify enterprise data, and deliver actionable insights across the entire value chain.

02 / Customer experience

The challenge

Production, sales, logistics, and finance systems all operated independently. Siloed data prevented the organization from understanding cross-functional performance and slowed decision-making.

Without consolidated data, leaders could not connect upstream and downstream metrics—such as linking plant output to delivery timelines or sales demand.

Analysts relied on spreadsheets and manual data pulls from different systems, creating delays, inaccuracies, and inconsistent reports across teams.

Siloed systems made it impossible to generate unified dashboards for production efficiency, sales trends, or route performance in real time.

The existing environment did not support automation, lineage, quality checks, or more advanced analytics such as predictive modeling.

03 / Customer experience

The solution

LBPL selected Microsoft Fabric to modernize its analytics environment and create a unified, governed data foundation across the enterprise. Fabric’s end-to-end capabilities-spanning data engineering, storage, warehousing, and analytics—enabled LBPL to consolidate data, standardize processes, and accelerate insight delivery.

• Unified data architecture with OneLake — LBPL centralized all major data sources into OneLake, Fabric’s multi-cloud data lake, enabling a single data estate accessible across teams and workloads.
• Enterprise Data Warehouse with Fabric — Using the Fabric Data Warehouse, LBPL built a central repository for production, sales, logistic, and finance data. This created a trusted data foundation with consistent KPIs and business definitions.
• Medallion architecture for scalable data management — LBPL adopted Fabric’s medallion architecture, organizing data into Bronze (raw), Silver (cleaned), and Gold (business-ready) layers. This approach improved data quality, traceability, and governance while simplifying downstream analytics.
• Data engineering with Fabric Pipelines and Notebooks — Using Data Factory pipelines, the team automated ingestion from ERP systems, production equipment data, and distribution logs. Fabric Notebooks were used to run complex transformations, validate data, and maintain processing logic at scale.
• Governance built into the platform — Fabric’s integrated governance and security capabilities ensure that data access, lineage, and quality are maintained consistently across workloads.
• Real-time analytics using Power BI — Business users now access dynamic Power BI dashboards built on Gold-layer datasets. Leaders across production, sales, and logistics can monitor KPIs such as production efficiency, sales growth by region, route performance and on-time delivery, and inventory turnover and warehouse utilization.

04 / Customer experience

Key outcomes

• A single source of truth across the enterprise - By consolidating production, sales, logistics, and finance data into OneLake, LBPL now operates from a unified data foundation. Teams access consistent, trusted datasets, reducing discrepancies and enabling cross-functional alignment.
• Faster and more confident decision-making - Leaders now receive real-time insights through Power BI, enabling them to spot trends, monitor operational performance, and act quickly. Whether reviewing plant throughput or delivery timelines, teams can make decisions with greater clarity and precision.
• Reduced manual effort for analysts - Fabric Pipelines and Notebooks automate ingestion and transformation, significantly cutting down the hours previously spent gathering data from spreadsheets and disparate systems. Analysts can now focus on forward-looking analysis instead of manual preparation.
• Improved data quality and reliability - Using Fabric’s medallion architecture, LBPL ensures that data is cleansed, enriched, and validated before reaching business users. The result is higher-quality insights and greater confidence in enterprise reporting.
• Scalable platform for future analytics and AI - With Microsoft Fabric, LBPL has a modern, cloud-based environment ready to support forecasting, predictive insights, and advanced optimization scenarios. The platform can easily scale as the business grows.

05 / Customer experience

Overall business impact

The Microsoft Fabric transformation delivered measurable business growth, enhancing operational efficiency, data capacity, and analytics readiness. LBPL is now well-positioned to expand its reach and strengthen its leadership in beverage manufacturing while maintaining focus on data-driven decision-making across the value chain.