Building a Modern Azure Data Foundation for an Outdoor Lifestyle Company

As organizations accelerate digital transformation for AI enablement, the ability to harness data at scale has become critical to operational efficiency, customer engagement, and business performance. BICP recently partnered with a leading Outdoor Lifestyle client to support the development of a modern Azure-based data foundation designed to power advanced analytics and enterprise-wide decision-making.

As a highly data-driven organization operating across wholesale and retail channels, the client integrates data from numerous line-of-business systems to manage sales, supply chain operations, inventory, and customer engagement. However, its legacy ETL and analytics infrastructure struggled to support both batch and real-time workloads at scale. Data pipelines were slow and complex to maintain, and legacy platforms were costly and difficult to scale as demand for enterprise data continued to grow.

To address these challenges, the client moved its analytics platform to Microsoft Azure, adopting Azure Databricks and Delta Lake to modernize data processing and enable a scalable, cloud-based architecture. BICP supported this effort by deploying experienced thought leadership and tactical data & visualization engineers through our Resource Capacity Services (RCS) model, helping the client build and expand its Azure data foundation and analytics capabilities while allowing internal teams to scale gradually and efficiently.

With Azure Databricks, we helped build high-performance ETL pipelines capable of supporting both batch and real-time workloads. Delta Lake provides a secure repository for curated data, enabling reliable pipelines, consistent datasets, and improved performance through features such as ACID transactions, caching, and optimized indexing.

Once ingested and processed, data can be delivered to multiple endpoints depending on the use case. Business analysts can connect directly to Power BI for near real-time reporting, data scientists can leverage Databricks notebooks to explore and train models, and other teams can access curated datasets for enterprise reporting and operational analytics.

The overall impact of this modernization has been significant. The new platform reduced ETL pipeline creation time by 70% and accelerated ETL processing from four hours to just five minutes, dramatically shortening time-to-insight and enabling broader self-service access to enterprise data.

Through close collaboration and the flexibility of BICP’s Resource Capacity Services (RCS) model, the client was able to modernize its analytics infrastructure while controlling costs and scaling expertise as needed. The result is a modern Azure-based data foundation that empowers teams across the organization to access trusted data faster and make smarter, more informed business decisions.