Real-Time Data Pipeline Development for Enhanced Content Personalization

As a growing scale-up in the Publishing & Printing industry, we are focused on leveraging data to revolutionize how we engage with our readers. The project involves designing and implementing a robust, real-time data pipeline using state-of-the-art technologies like Apache Kafka, Spark, and Databricks. By integrating these tools, we aim to provide personalized content recommendations, thereby enhancing user experience and increasing engagement. Our current system lacks the capability to process data efficiently at scale and in real-time. Additionally, we aim to adopt a data mesh approach to decentralize data ownership and improve data quality across departments. This project will not only streamline our data processing capabilities but also enable us to utilize machine learning models for predictive analytics. The successful completion of this project will provide a strategic advantage in a competitive market, allowing us to tailor our offerings more precisely to individual reader preferences and drive higher revenue through increased subscriptions.