DQLab Store Sales Performance Report With Apache Hive

Unlocking insights from transactions, promotions, and customers In this project, I analyze DQLab Store’s transaction data (2009–2012) using Apache Hive on Cloudera to uncover sales performance trends, evaluate promotion effectiveness, and explore customer behavior. With over 5,500 rows of order details — including order status, sales, discounts, product categories, and subcategories — this analysis demonstrates how Hive can transform raw data into structured business intelligence. Highlights of the video: • Step-by-step sales performance analysis using Hive queries • Insights into finished, returned, and cancelled orders • Evaluation of discounts and promotions to measure impact • Customer-level analysis to identify key drivers of revenue • Clear reporting and aggregation for business decision-making 👉 Subscribe to explore more portfolio projects where Hive, Spark, and R bring data to life with powerful analytics.