Powered by a modern Azure and Snowflake architecture to unify data and deliver scalable, self-service analytics.
Details
Client Company Overview
Overview of the organization:
The client is a Midwest-based wholesale electrical supply distributor with nearly a century of industry experience, serving thousands of customers across industries such as manufacturing, construction, utilities, and food and beverage. As a critical supply chain partner, the organization provides electrical components, equipment, and value-added services to commercial, industrial, and contractor markets. With a complex operating environment driven by large product catalogs, dynamic pricing, and high-volume transactions, the company identified a need to modernize its data and analytics capabilities to better support growth, improve decision-making, and enhance operational efficiency.
Industry & Scale:
The Client has thousands of customers and is a major presence throughout the entire midwest. It supplies equipment and parts to a wide range of industries:
- Agriculture
- Commercial
- Contractor
- Food & Beverage
- Institutional
- Manufacturing
- Mining & Metal
- System Integration
- Water / Wastewater
Business Challenge
The client faced significant barriers to growth due to a fragmented and increasingly complex data environment that limited scalability, efficiency, and decision-making. Critical business data – spanning customers, products, sales, and pricing – was distributed across multiple legacy systems, including ERP, CRM, and product information platforms, all connected through a web of brittle point-to-point integrations.
This lack of cohesion forced teams to manually piece together information, often relying on spreadsheets and ad hoc reporting processes that were time-intensive, inconsistent, and difficult to maintain. As a result, customer support slowed, financial visibility was limited, and confidence in data eroded due to conflicting reports and the absence of a single source of truth. With anticipated growth on the horizon, the organization recognized that its existing architecture could not scale and posed risks to profitability, operational efficiency, and long-term agility.
Technical Challenge
The client’s technical landscape was heavily burdened by legacy architecture and accumulated technical debt, which made data difficult to access, trust, and scale. Core systems, including a heavily customized ERP, were stretched beyond their intended use, resulting in inefficient data structures, inconsistent business logic, and fragmented semantic models across reporting tools.
Performance limitations further compounded the issue, as existing infrastructure struggled to process large datasets and support growing reporting demands. Overloaded systems, duplicated datasets, and multiple customer order applications created ongoing maintenance challenges and made synchronization increasingly unsustainable. At the same time, the absence of centralized, governed data led to security risks, with employees relying on manual file sharing and email-based reporting.
Integration complexity and poor data quality ultimately prevented the organization from achieving a unified view of its operations, reinforcing data distrust and limiting its ability to generate timely, accurate insights.
Our Approach
Zirous took a strategic, cloud-first approach to modernizing the client’s data ecosystem, designing a scalable Modern Data Platform built on Microsoft Azure and Snowflake. At the core of the solution was a Medallion Architecture that structured data into progressive layers, enabling raw data to be systematically refined, validated, and transformed into trusted, business-ready datasets.
To address integration challenges, Zirous replaced fragmented point-to-point connections with a standardized, reusable integration framework to be powered by a modern iPaaS platform. This approach simplified how systems communicate, reduced maintenance overhead, and enabled new data sources to be onboarded more efficiently. A configuration-driven ETL framework was implemented to automate data ingestion, transformation, and quality validation, ensuring consistency while minimizing manual intervention.
Data governance was embedded directly into the architecture through the establishment of a centralized data dictionary, defined stewardship roles, and role-based access controls. This ensured consistent business definitions, improved security, and created a trusted single source of truth.
Zirous executed the engagement using its Catalyst methodology, beginning with a comprehensive assessment of the client’s current state and aligning the solution with business goals and internal capabilities. Development was delivered iteratively with ongoing collaboration, ensuring transparency, adaptability, and long-term sustainability for the client’s internal teams.
Solution Overview
The resulting solution was a scalable, cloud-native Modern Data Platform that unified data across the organization and enabled reliable, self-service analytics. By centralizing data from multiple source systems into Snowflake and structuring it through a Medallion Architecture, Zirous created a consistent and governed foundation for reporting and analysis.
Automated ingestion pipelines and a configuration-driven ETL framework ensured that data was continuously synchronized, validated, and transformed into high-quality datasets. On top of this foundation, Zirous developed dynamic Power BI dashboards that provided business users with real-time visibility into key metrics, including customer pricing and sales performance.
The solution also introduced reusable integration frameworks, DevOps CI/CD pipelines, and robust data traceability capabilities, enabling the platform to scale efficiently as business needs evolve. By standardizing integrations, embedding governance, and automating workflows, the platform replaced manual processes with a streamlined, future-ready data ecosystem.
Results & Impact
The Modern Data Platform transformed the client’s ability to leverage data by eliminating manual reporting processes and establishing a trusted single source of truth. Automated pipelines and standardized integrations improved data accuracy, reduced reporting effort, and enabled multiple daily data refreshes.
Business users now have access to self-service dashboards with timely, reliable insights, accelerating decision-making and improving customer responsiveness. At the same time, the shift to a cloud-based architecture reduced IT overhead, strengthened data security, and created a scalable foundation for continued growth.
With a unified, governed data ecosystem in place, the organization has moved from reactive reporting to proactive, data-driven decision-making—positioning it to operate with greater agility, efficiency, and long-term competitive advantage.
