Real-time Analytics Platform for Enhanced Production Efficiency

In the manufacturing and production industry, the ability to quickly adapt to changes on the production floor is critical. Our enterprise aims to implement a real-time analytics platform that integrates data from machinery, supply chain systems, and production schedules to provide a holistic view of our operations. The platform will utilize Apache Kafka for event streaming, ensuring data from IoT devices and other sources are collected in real-time. Spark will be employed for processing large volumes of streaming data, while Airflow will manage complex data pipelines efficiently. We plan to use dbt for data transformation to ensure data consistency and quality across our systems. The final data will be stored in Snowflake, where it can be queried and analyzed using BigQuery for business insights. By adopting a data mesh architecture, we enable decentralization and scalability across multiple production sites. This project aims to streamline operations, reduce downtime, and improve production efficiency, aligning with our strategic goals to maintain competitiveness in the market.