Transforming eCommerce performance reporting with data lake

Sigmoid helped a multinational CPG company enhance visibility into their eCommerce operations, including real-time sales, inventory, and P&L data, to swiftly respond to dynamic market demands.

Business Scenario

The customer is a multinational CPG company. The global scale of their eCommerce operations demanded more visibility of their sales and inventory data. They wanted a centralized data lake that could enable data products on real-time sales analytics, general ledger, and vendor management dashboards, catering to diverse retailers. An effective monitoring system was crucial to minimize chargebacks resulting from late shipments or incomplete orders, thereby achieving cost savings. They were looking for data-driven insights to enable effective investment decisions for high-performing eCommerce channels.

Sigmoid Solution

We created a centralized data lake that streamlined and consolidated the vast and varied data landscape originating from multiple retailers and brands. Data from diverse sources was stored in Azure Data Lake Storage (ADLS) and APIs from multiple vendors such as eStore, Lett, and Sprinklr were used to provide access to the data scrapped by these vendors. The data underwent meticulous ingestion, transformation, and storage in formats tailored to the specific needs of the business. The refined data was stored in Databricks tables to establish a robust foundation for real-time analytics and reporting.

Business Impact

The centralized data lake provided a consolidated view of sales, inventory, and financial metrics to optimize strategic investments, driving tangible revenue growth. Real-time analytics and meticulously crafted P&L dashboards enhanced visibility into eCommerce operations which enabled proactive responses to changing market dynamics. The solution addressed complex data standardization challenges to establish a unified data ecosystem.


improvement in on shelf availability


reduction in reporting time


higher chargeback reduction opportunities identified

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