Enterprise Data Warehouse

Situation: The organization lacked a centralized, reliable data infrastructure. Data was siloed across multiple systems, causing inconsistent reporting and limiting data-driven decision-making.

Task: Design and implement an enterprise-scale data warehouse to serve the entire company, ensuring scalability, governance, and cross-functional accessibility.

Action:

Architected and built a company-wide data warehouse leveraging Apache Hive as the backbone.

Designed robust ETL pipelines to consolidate disparate data sources into a unified platform.

Applied data governance principles to enforce data quality, consistency, and security.

Established a scalable data architecture to support future growth and advanced analytics.

Result: Delivered a centralized, enterprise-grade data warehouse that provided reliable, timely access to critical business data, improved decision-making efficiency, and enabled scalable analytics across the organization.