Real-time Data Pipeline Optimization for Enhanced Customer Insights

As a burgeoning startup in the Software Development industry, our primary objective is to deliver exceptional, data-driven insights to our clients. However, our current data infrastructure lacks the capacity to handle real-time analytics effectively, which impedes our ability to provide timely recommendations and insights. This project aims to design and implement an optimized real-time data pipeline utilizing technologies such as Apache Kafka for event streaming, Spark for real-time processing, and Airflow for orchestrating workflows. Additionally, we'll integrate with data warehousing solutions like BigQuery or Snowflake to ensure scalability and efficiency in data management. Implementing a data mesh approach will enable distributed data ownership and enhance collaboration across teams. The deliverable includes a comprehensive pipeline that aligns with our MLOps strategy, ensuring data observability and consistent model performance monitoring. By completing this project, we anticipate improved customer satisfaction through faster, more accurate insights.