A leading global retail company operated multiple brands, eCommerce platforms, and physical stores across North America, Europe, and Asia-Pacific. The business managed millions of products across diverse categories, including apparel, electronics, home goods, and consumer products.
As the organization expanded, product performance data became increasingly distributed across ERP systems, inventory platforms, point-of-sale applications, eCommerce channels, supplier networks, and marketing systems. Different business units maintained separate datasets and reporting standards, making it difficult to establish a consistent view of product performance across regions and brands.
The organization wanted to build a centralized Product Performance Analytics Platform to provide a trusted, governed view of product sales, profitability, inventory movement, and customer demand across the enterprise.
The objective was to standardize product performance metrics, strengthen data governance, improve inventory and assortment decisions, enable self-service analytics, and create a scalable foundation to support advanced analytics and future AI initiatives.
eCommerce/Retail
Databricks & Unity Catalog
Data Governance Modernization
Product-related information was spread across multiple operational systems, including ERP platforms, inventory applications, eCommerce channels, POS systems, supplier networks, and marketing tools. The absence of a centralized analytics platform made it difficult to obtain a complete and consistent view of product performance.
Different regions and business units used varying definitions for key performance indicators such as revenue, margin, inventory turnover, product availability, and sell-through rates. This created reporting inconsistencies and reduced confidence in business decisions.
Product datasets were duplicated across multiple environments with limited transparency into ownership, usage, and lineage. Business users often relied on different versions of the same data, leading to governance challenges and inconsistent reporting outcomes.
Different business teams required varying levels of access to product, supplier, pricing, and inventory information. Existing access controls were managed manually, making governance difficult to scale across the organization.
Product performance reporting relied on manual data extraction and reconciliation processes, delaying insights and limiting the organization's ability to respond quickly to changing market conditions.
We can build governed analytics platforms using Databricks and Unity Catalog to unlock trusted insights, improve data governance, and accelerate analytics adoption.
Talk to a Data & Analytics ExpertOur Databricks experts designed and implemented a modern Product Analytics Platform using Databricks Lakehouse Architecture. The platform centralized product, sales, inventory, pricing, promotion, and customer engagement data into a single governed environment that supported enterprise-wide analytics and reporting.
To establish trust and control across product data assets, Unity Catalog was implemented as the enterprise governance layer. This provided centralized metadata management, role-based access controls, data discovery, lineage tracking, and governance policies, ensuring secure and compliant access to trusted product information.
A unified product analytics model was developed to standardize reporting across all brands and regions. Consistent definitions were established for key metrics, enabling business users to analyze product performance using trusted enterprise-wide KPIs.
The platform provided complete visibility into how product data moved across ingestion, transformation, and consumption layers. Business and technical teams gained improved transparency, faster issue resolution, and greater confidence in analytical outputs.
Governed analytics datasets were published for merchandising, supply chain, finance, marketing, and executive teams. Business users could discover and consume trusted data ilndependently, reducing reliance on engineering teams and accelerating reporting initiatives.
The governed platform established a scalable foundation for advanced analytics and future AI use cases, including demand forecasting, inventory optimization, recommendation engines, dynamic pricing strategies, and assortment planning.
The organization gained a centralized and trusted platform for managing product performance, inventory, pricing, and sales analytics across all brands and regions.
Unity Catalog provided complete visibility into data ownership, lineage, access controls, and usage patterns, significantly improving governance and reducing operational risk.
Business users gained near real-time access to trusted product performance data, enabling faster reporting cycles and more informed decision-making.
Enhanced visibility into inventory and sales trends enabled more effective stock planning, reduced excess inventory, and improved product availability.
Self-service access to governed datasets reduced dependency on technical teams and empowered business users to generate insights more efficiently.
The platform established a secure and scalable foundation that supports machine learning, forecasting, personalization, pricing optimization, and next-generation retail analytics.
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