Real-Time Data Pipeline Implementation for Enhanced Publishing Analytics

In the competitive world of publishing, having timely insights into publication performance is crucial. Our SME publishing house has been experiencing challenges in obtaining real-time analytics from our diverse publishing platforms, including digital and print. The current batch processing approach results in data lags, inhibiting our ability to react quickly to market trends and reader preferences. To address this, we aim to develop a robust real-time data pipeline leveraging technologies such as Apache Kafka for event streaming, Spark for data processing, and Snowflake for storage and analytics. The successful freelancer will be tasked with designing a data mesh architecture that allows seamless integration of data across departments, ensuring data quality and observability using tools like Airflow and dbt. The project will also incorporate real-time dashboards to visualize key metrics, empowering our editorial and marketing teams to make data-driven decisions swiftly. This transformation is expected to position us at the forefront of the industry by enhancing our agility and responsiveness in a fast-paced market.