Real-time Data Pipeline for Streaming Viewership Analysis in Film & Television

As a scale-up in the competitive Film & Television industry, we are keen to leverage data to drive our content strategy and boost viewer engagement. The current challenge is processing and analyzing massive datasets from multiple streaming services in real-time to gain actionable insights into viewer behavior. Our goal is to create a robust data pipeline that can ingest, process, and visualize data in real-time, enabling us to make informed decisions quickly. The project will involve setting up event streaming using Apache Kafka for real-time data ingestion, employing Spark for data processing, and using Snowflake or BigQuery for efficient data storage and analytics. We aim to implement MLOps for predictive analytics and Airflow for orchestrating complex workflows. A successful project will result in an agile data infrastructure that provides stakeholders with timely insights to optimize content offerings and marketing strategies, ultimately increasing viewership and customer satisfaction.