Real-Time Data Pipeline Development for IoT Device Analytics

In the rapidly evolving smart home market, our startup aims to differentiate itself by leveraging real-time analytics for advanced IoT device performance insights. We are developing a data pipeline to process telemetry data from our devices, enabling real-time monitoring and analytics. The project involves setting up a robust, scalable architecture using Apache Kafka for event streaming, Spark for real-time processing, and dbt for data transformation. The data will be stored in Snowflake, providing a foundation for advanced analytics and machine learning applications. Airflow will automate and orchestrate the data workflows, ensuring a seamless data processing pipeline. Our goal is to achieve high data observability, enabling rapid identification and resolution of device issues, ultimately improving customer satisfaction and product value. The successful completion of this project will empower our marketing and R&D teams with actionable insights, enhancing both customer experience and product innovation.