Real-Time Data Pipeline for Enhanced Supply Chain Visibility in Organic & Natural Foods

As an industry leader in Organic & Natural Foods, our enterprise is committed to leveraging cutting-edge data engineering practices to maintain our competitive edge and ensure product quality. We aim to build a robust real-time data pipeline to provide comprehensive visibility into our supply chain operations. This solution will utilize Apache Kafka for event streaming, Spark for processing large datasets, and Snowflake or BigQuery for data warehousing. Airflow will manage workflows, while dbt will enable data transformation. Our primary objective is to improve real-time analytics capabilities to identify bottlenecks, predict supply chain disruptions, and allow for proactive decision-making. By adopting a data mesh architecture, we seek to democratize access to supply chain data across our organization, improving collaboration and innovation. The project will focus on integrating MLOps practices to ensure scalable and reliable model deployment for predictive analytics. Our company anticipates that this initiative will lead to significant cost savings, enhanced product quality assurance, and a better customer experience.