Global Packaging Material Manufacturer Streamlines Data with Azure Databricks

A global packaging material manufacturer was holding on to immense amounts of critical data. Ordering systems, printing queues, and regional operations all spoke different dialects, with little to no integration. Each function ran in its own silo, creating data bottlenecks, reporting delays, and IT chaos. The infrastructure was a patchwork of legacy systems that lacked scalability, reliability, and long-term viability. 

Wavicle was brought in to change that. Tasked with building a metadata-driven digital product platform, the goal was clear: migrate massive datasets from multiple legacy systems across brands, integrate them seamlessly, and create a reliable foundation for analytics, reporting, and future growth. 

Challenge 

The manufacturer’s environment reflected years of incremental growth. Multiple relational database systems including Oracle, SQL Server, and PostgreSQL held large volumes of structured data, but without a centralized repository, the business had no single source of truth. Operations remained disconnected, and teams often worked from fragmented views of the business. 

With regional teams relying on timely data for BI and front-end applications, the company faced a tight, phased timeline to consolidate its data and enable near-real-time access without disrupting ongoing operations. They also needed a scalable architecture that could support new systems in the years to come.  

Solution 

Wavicle partnered closely with the client’s global and regional stakeholders to design a metadata-driven ingestion automated pipeline in Azure Databricks. This pipeline was built to work with the structured data already present in the manufacturer’s systems, while also remaining flexible enough to support future growth and integration needs. 

The approach was both strategic and practical. By creating a modular architecture, each source system could be onboarded independently, making the platform easy to expand without repeated rework. Because the manufacturer’s source data was relatively clean and consistent, Wavicle was able to streamline the Medallion architecture by moving directly from Bronze to Gold, avoiding unnecessary processing steps and reducing overall complexity. 

The team also addressed performance and speed across the migration effort. Databricks served as the core platform, leveraging PySpark, Spark SQL, Delta Tables, and Workflows to manage large-scale data movement. One PostgreSQL system alone contained more than a terabyte of data, which Wavicle successfully migrated into Delta Tables in under three days without downtime. This demonstrated the scalability and reliability of the platform. Throughout the process, Wavicle worked closely with internal IT and other stakeholders to validate each step and ensure alignment with the manufacturer’s business needs.

Results 

The new digital product platform transformed the manufacturer’s ability to manage and leverage their data. Internal teams gained timely access to a trusted gold layer through Delta Sharing, enabling faster and more accurate decision-making. The simplified architecture reduced processing time and complexity, while the modular, metadata-driven design ensured that future systems could be added with minimal effort. The platform also enabled seamless integration of structured data from multiple legacy systems and demonstrated the scalability needed to support long-term growth.  

Through a combination of metadata-driven architecture, modular design, and close collaboration, Wavicle helped this global RFID manufacturer transform a fragmented ecosystem into a streamlined, future-ready digital platform. 

The solution not only addressed the manufacturer’s immediate needs but also provided a foundation for growth, scalability, and innovation well into the future.

Wavicle continues to help global enterprises modernize their data foundations with scalable, metadata-driven solutions. To explore how we can help your organization achieve similar results, get in touch with our experts.