Word count: 3500 words
Objectives to cover:
Introduction to Metadata-Driven Data Engineering: Introduces the concept and significance of metadata-driven approaches in modern data systems.
Overview of Big Data in the Automotive Industry: Highlights the scale, sources, and impact of data generated across the automotive sector.
Role of Metadata in Scalable Data Pipelines: Explains how metadata enables automation, reusability, and adaptability in data workflows.
Architectural Framework for Metadata-Driven Systems: Presents a high-level structure for implementing metadata-oriented data platforms.
Integration of Heterogeneous Data Sources: Discusses methods for unifying diverse data formats and systems within automotive environments.
Real-Time Analytics and Performance Optimization: Focuses on techniques to enhance processing speed and insights delivery using metadata.
Use Cases in Automotive Manufacturing and Telematics: Showcases practical applications of the framework in production and vehicle data.
Scalability Challenges and Solutions: Identifies key bottlenecks and proposes solutions to scale metadata-driven systems effectively.
Conclusion and Recommendations: Summarizes key insights and outlines strategic recommendations for future automotive data initiatives.
Reference: IEEE style