Decrease in MS Azure cloud spend
Global sites enabled with real-time decisions
A leading global retailer, with an operational footprint of over 2,300 stores across North America and Europe, determined that its aging data infrastructure was a significant impediment to operational agility and strategic growth. The organization’s legacy systems, principally an IBM AS/400 mainframe and a substantial SQL-based repository, had long formed the backbone of its operations. However, with escalating data volumes and increasing business complexity, these platforms proved insufficient to meet the company's requirements for timely, actionable insights and rapid decision-making.
The client confronted significant challenges originating from its fragmented and slow-moving data architecture. Data was distributed across disconnected platforms, which precluded the establishment of a single source of truth. Reporting processes were frequently compromised by inconsistent data update intervals, and the generation of even fundamental insights was a time-intensive endeavor. The absence of real-time data severely constrained the company's capacity to respond to market dynamics, manage inventory effectively, and optimize store-level performance.
Furthermore, the outdated architecture incurred high maintenance costs, presented integration difficulties with modern analytical tools, and hindered the scalability of data capabilities in alignment with corporate growth. These limitations not only diminished operational efficiency but also eroded the company's competitive standing in adynamic retail landscape.
To address these systemic deficiencies, the retailer engaged Accellor to initiate a strategic data transformation initiative designed to modernize its entire data ecosystem. The core of this transformation was the migration from monolithic legacy systems to a contemporary, cloud-native platform architected on Microsoft Fabric. A Data Domain architectural model was adopted to segment the company’s primary business functions—Product, Distribution Centre, Sales, and Store—into dedicated, domain-specific Lakehouses. This structure optimized data management, enhanced governance protocols, and enabled the direct delivery of domain-relevant data to business stakeholders.
Automated data cleansing and validation mechanisms were implemented utilizing Great Expectations within Microsoft Fabric Notebooks, ensuring a high degree of data quality throughout the pipeline. The architecture incorporated robust role-based access controls and comprehensive metadata management to fortify security and ensure regulatory compliance.
To democratize data access, self-service reporting capabilities were introduced via Microsoft Power BI, empowering business users to independently generate real-time reports and insights without dependence on central IT teams. The new architecture also achieved seamless integration with extant enterprise systems, including WorkJam and OracleXstore, thereby creating a unified operational perspective across the organization.
The initiative fundamentally re-engineered the retailer’s data ecosystem, facilitating faster and more reliable access to business intelligence across all operational domains. Reporting timelines were dramatically reduced from days to near real-time, equipping business teams with the agility to act decisively on emergent trends and operational requirements. The new domain-driven architecture improved data governance, reduced systemic complexity, and yielded a significant reduction in operational expenditures, including a 45% decrease in Microsoft Azure cloud spend.
By consolidating all business-critical data into a single source of truth and empowering teams with self-service analytics, the retailer achieved an unprecedented level of operational agility. This transformation not only resolved long-standing technological pain points but also established a scalable, future-proof data foundation engineered to support sustained innovation and corporate growth.
