Real-Time Analytics Pipeline for Art & Collectibles Marketplace

As a scale-up company in the Art & Collectibles industry, we are committed to leveraging data to drive business decisions and improve customer experience. Our current batch processing system lacks the agility needed to provide real-time insights, essential for staying ahead in the dynamic art market. This project involves designing and implementing a real-time analytics pipeline using a data mesh approach. Key components include deploying Apache Kafka for event streaming, Spark for processing data in real time, and integrating with data warehousing solutions like Snowflake or BigQuery for scalable storage. Furthermore, implementing an MLOps framework will facilitate machine learning model deployment and monitoring, ensuring data-driven decisions are timely and accurate. The successful execution of this project will provide our team with actionable insights into emerging art trends, buyer preferences, and sales forecasts, enabling us to optimize inventory, pricing strategies, and marketing efforts.