Apexon’s collaboration with a leading packaging and supply chain solutions provider was initiated to modernize its data infrastructure and address challenges around fragmented systems, siloed reporting, and manual data extraction processes. The scope of work involved designing and implementing a unified data lakehouse on AWS, enabling centralized access to high-quality data, automated data workflows, and support for advanced analytics. Apexon’s solution streamlined data management, eliminated reliance on SMEs for reporting, and ensured scalability for future AI/ML initiatives. This partnership aligned with the client’s goals of enhancing customer experience, enabling data-driven decisions, and improving operational efficiency, resulting in significant time savings and readiness for advanced analytics.
The client, headquartered in Neenah, Wisconsin, operates across 112 locations in North America and Europe. The company comprises two core business units: one specializing in retail merchandising packaging, corrugated packaging, shipping containers, and fulfilment services; and another a leader in manufacturing reusable containers, pallets, dunnage, bulk systems, and metal racks that optimize supply chain product flow. Together, these units serve diverse industries with innovative packaging and logistics solutions.
The client relies on on-premises Oracle data warehouses, SAP, and Salesforce to manage data across its business areas. As part of its strategic growth plan, the company sought to modernize its data platforms to enable efficient access to high-quality datasets for both internal business users and external customers. By partnering with Apexon, an advanced AWS consulting and migration partner, the client leveraged expertise in cloud migrations and the Migration Acceleration Program (MAP) framework to achieve a comprehensive cloud modernization solution.
Overcoming Data Fragmentation and Inefficiency
The client faced significant challenges with manual data collection and reporting by subject matter experts, leading to inefficiencies and delays. Technical limitations of existing platforms hindered data consolidation, while unclear data ownership resulted in inconsistent, low-quality data across business functions, impeding effective decision-making. These challenges impacted the client’s ability to deliver seamless customer experiences and optimize operations.
Key obstacles included:
Absence of a centralized data lakehouse limited the ability to access and analyze data across systems like SAP, Salesforce, and Oracle.
Heavy reliance on SMEs to manually extract and compile data caused inefficiencies and delayed reporting.
Multiple systems operated in isolation, making data consolidation complex and error prone.
Inconsistent data formats and lack of standardization affected accuracy and trust in reporting.
Legacy systems lacked the flexibility and performance needed to support AI, ML, and real-time analytics.
These challenges stemmed from two key root causes:
- Manual Reliance: The client relied heavily on manual processes for data extraction and reporting, which were time-consuming, error-prone, and unscalable.
- Resource Strain: Growing data demands strained resources, hindering effective tracking and analysis.
- High Costs: Manual data preparation increased labor and resource costs.
- Limited Insights: Inability to consolidate disparate data limited ad-hoc insights for strategic decisions.
- Information Avalanche: The client struggled to process large volumes of data from multiple sources in various formats, requiring efficient centralization and cleaning.
- Data Ownership Issues: Lack of clear ownership led to inconsistent data quality and reporting challenges.
- Scalability Demands: Legacy systems couldn’t handle growing data volumes or support advanced analytics.
These challenges created significant barriers to enhancing customer experiences and operational efficiency, necessitating a robust, scalable solution.
Empowering Data-Driven Growth with a Unified AWS Data Lakehouse
Apexon partnered with the client to deliver a modern data lakehouse on AWS, enabling seamless ingestion, processing, and transformation of data from multiple sources. By leveraging a suite of AWS services, Apexon migrated, cleaned, and modeled data to support unified reporting and analytics. The centralized platform ensured secure, role-based access, making high-quality, trusted data readily available for business use while preparing the infrastructure for future AI/ML initiatives.
Key components of Apexon’s solution included:
- Leveraged OData services to migrate data from SAP and Salesforce into the centralized platform.
- Extracted data from Oracle, MS SQL, and Excel sources for efficient processing.
- Performed data cleanup and transformation to ensure consistency and quality.
- Orchestrated data workflows and processes for automated, end-to-end pipelines.
- Provided scalable and fast data access and analytics for self-service reporting.
- Ensured secure, role-specific data access control to safeguard sensitive information.
Apexon’s comprehensive approach included:
- Integrated data from SAP, Salesforce, Oracle, MS SQL, and external sources like Excel into the AWS data lakehouse.
- Cleansed and transformed raw data using AWS Glue for consistency and quality.
- Developed data models to support accurate and timely business reporting.
- Implemented IAM role-based policies to ensure secure and controlled data access.
By providing a scalable and automated data platform, Apexon empowered the client to streamline operations, enhance data accessibility, and drive data-driven decision-making.
Delivering Centralized Data Access and Operational Excellence
Apexon’s strategic solutions enabled the client to achieve significant advancements in data management, operational efficiency, and system scalability:
- Unified Access: Centralized data from multiple systems within AWS, improving reporting accuracy.
- High-Quality Data: Delivered clean, standardized data, enhancing trust and consistency across business units.
- Scalable Infrastructure: Achieved high system scalability with near-zero downtime, supporting growing data volumes.
- Streamlined Workflows: Automated data pipelines reduced manual intervention and simplified maintenance.
- Faster Reporting: Enabled self-service analytics, accelerating report generation and data updates.
- Resource Reallocation: Freed up staff to focus on high-value business activities.
- Robust Access Controls: Implemented role-based access, ensuring data security and compliance with zero unauthorized access incidents.
- Continuous Monitoring: Enabled proactive issue detection for system reliability.
- AI Readiness: Optimized infrastructure for advanced analytics and AI use cases.
- 30–40% FTE Reallocation: Reduced manual data preparation efforts, allowing staff to focus on strategic initiatives.
- 100% Data Accessibility: Enabled secure access to centralized, clean data in near real-time for all business users.
- Up to 60% Faster Decision-Making: Streamlined reporting and self-service BI accelerated decision-making processes.
- AI-Ready Infrastructure: Positioned the client for advanced analytics and AI adoption.
By delivering these results, Apexon enabled the client to enhance customer experiences, improve operational efficiency, and establish a foundation for future innovation, strengthening their market position.
