Real-Time Analytics Pipeline for Jewelry & Watches E-commerce

As a burgeoning startup in the Jewelry & Watches industry, we face challenges in efficiently tracking and analyzing customer interactions and sales data in real-time. Our current system relies heavily on batch processing, which delays insights and decision-making. We require a robust data engineering solution that can integrate with our existing e-commerce platform to deliver real-time analytics. This project will involve setting up an event streaming architecture using Apache Kafka, coupled with a data mesh approach to ensure scalable and flexible data management. We'll employ Apache Spark for real-time data processing and Airflow for orchestration. The solution should integrate with our data warehousing solutions such as Snowflake or BigQuery for storage, with analytics processed through Databricks. This pipeline will empower our team to perform real-time monitoring, gain actionable insights, and make quick adjustments to enhance customer experience and drive sales. The successful implementation of this project is expected to substantially reduce time-to-insight, improve inventory turnover, and increase sales conversion rates.