Real-Time Data Pipeline Modernization for Enhanced Steel Production Efficiency

In the competitive steel & metals industry, operational efficiency and timely decision-making are paramount. Our enterprise is embarking on a project to transform its data infrastructure by implementing a real-time data processing pipeline. The current batch-based data systems are inadequate for the dynamic demands of our production lines. Utilizing technologies like Apache Kafka for event streaming and Databricks for real-time analytics, we aim to create a seamless data mesh that supports agile and data-driven decision-making. This pipeline will also incorporate MLOps practices, enabling rapid deployment and monitoring of machine learning models for predictive maintenance and production optimization. We intend to utilize Snowflake and BigQuery for centralized data warehousing, ensuring that data is accessible and actionable. The project will also focus on data observability to ensure data quality and reliability. The successful implementation will result in significant cost efficiencies, improved production quality, and a competitive edge in the marketplace.