Real-time Data Pipeline Optimization for Enhanced Inventory Management in Home & Garden Retail

As a growing SME in the Home & Garden sector, we face challenges with managing our inventory effectively. Fluctuating customer demands and seasonal changes often result in stockouts or overstock situations, impacting both revenue and customer experience. To address these challenges, we plan to implement a real-time data pipeline using Apache Kafka for event streaming and Spark for real-time analytics. This initiative will allow us to forecast inventory needs more accurately and respond swiftly to market changes. Additionally, we will leverage dbt and Airflow for data transformation and orchestrating our data workflows, and utilize Snowflake for our data warehousing needs. By improving our data observability and implementing a data mesh architecture, we aim to decentralize data ownership and empower teams with actionable insights. This project will ultimately enhance our operational efficiency, reduce unnecessary inventory costs, and improve customer satisfaction.