Real-time Data Pipeline for Optimized Inventory Management

Our startup in the warehousing and distribution industry is looking to overhaul our inventory management system with a modern real-time data pipeline. As we expand our operations, the current batch processing systems prove inadequate for timely decision-making and dynamic adjustments. We aim to implement a solution that integrates event streaming and real-time analytics to handle data from various sources such as sales reports, supplier updates, and logistics. The project will leverage technologies like Apache Kafka for event streaming, Apache Spark for real-time data processing, and Airflow for orchestrating complex data workflows. Additionally, we will employ tools like dbt for data transformation and Snowflake or BigQuery for scalable data warehousing solutions. The objective is to enable real-time insights into inventory levels, demand forecasting, and supply chain bottlenecks, consequently improving our distribution efficiency and customer satisfaction. This initiative is critical to maintaining our competitive edge and scaling operations efficiently.