Real-time Data Pipeline Implementation for News Analytics

As a growing news organization, we face the challenge of staying ahead in a fast-paced media environment. We are looking to implement a real-time data pipeline that will allow us to analyze user engagement and content performance instantly. Currently, we rely on delayed reporting which hampers our ability to make timely editorial decisions. The desired solution should integrate technologies such as Apache Kafka for event streaming, Spark for data processing, and Snowflake for storing processed data. The project will also involve setting up data orchestration using Airflow and transformation layers with dbt. The solution should ensure scalability and flexibility, enabling us to integrate additional data sources and adapt to evolving business needs. The successful implementation of this project will empower us to provide more personalized content, optimizing user engagement and increasing our competitive edge.