$5B Ecommerce Giant Transforms BigQuery Analytics with InfraHive's ETL layer for AI for Natural Language Querying

InfraHive's Data Layer enables natural language querying of user transactions, finance data, and A/B testing results

This $5B ecommerce giant processes millions of daily transactions across global markets, generating hundreds of GBs of complex data in BigQuery spanning user behavior, financial metrics, and advertising performance. Can't name due to NDA and competitive clause from their side. With critical business decisions requiring insights from user transactions, finance queries, and A/B ad testing results, the company needed their scattered BigQuery data consolidated and optimized for AI-powered natural language analysis.

Previously, the ecommerce company struggled with fragmented BigQuery data silos that made it nearly impossible for business teams to extract actionable insights from user transactions, financial performance, and advertising effectiveness. Without consolidated, AI-ready data architecture, analysts spent weeks manually querying different datasets, creating bottlenecks in decision-making for critical areas like customer behavior analysis, revenue optimization, and marketing campaign performance.

InfraHive's Data Layer implemented a comprehensive BigQuery consolidation ETL pipeline that unified disparate data sources and prepared them for natural language-based AI agent querying taht the team is able to build on top. The system enabled business teams to ask complex questions in plain English about user transactions, finance metrics, and A/B testing results, with the AI agent automatically generating sophisticated BigQuery analyses and delivering instant insights.

With InfraHive, this $5B ecommerce company was able to:

• Transform data operations efficiency through streamlined BigQuery consolidation and accelerated decision-making processes
• Consolidate hundreds of GBs of fragmented BigQuery data into a unified, AI-ready architecture
• Enable natural language querying of complex user transaction patterns, financial metrics, and A/B testing results
• Reduce analytics turnaround time from weeks to minutes through AI-powered automated query generation
• Empower business teams to independently analyze customer behavior, revenue trends, and advertising performance without technical expertise
• Transform scattered ecommerce data silos into a coherent, AI-accessible knowledge base for strategic business intelligence