Real-Time Audience Insights Platform for Film & Television

As a leading enterprise in the Film & Television industry, we recognize the critical need to harness data for strategic decision-making. Our goal is to develop a Real-Time Audience Insights Platform that collects, processes, and analyzes viewer data from various digital channels. By employing technologies such as Apache Kafka for event streaming and Spark for real-time data processing, we aim to create a dynamic data mesh architecture that centralizes access to actionable analytics. This platform will utilize MLOps to seamlessly integrate machine learning models, enhancing predictive analytics and personalization capabilities. Leveraging tools like Airflow for orchestrating complex workflows and dbt for data transformations, we aim to ensure data pipelines are robust and scalable. The integration with cloud-based data warehouses like Snowflake and BigQuery will support large-scale data storage and querying, enabling in-depth analysis and reporting. The key deliverables include a fully integrated data observability framework to monitor data quality and flow, ensuring precise and reliable insights. Through this initiative, we anticipate a significant improvement in content curation, targeted marketing efforts, and overall viewer satisfaction.