Real-Time Data Pipeline for Intellectual Property Portfolio Management

Our company, an SME specializing in managing intellectual property portfolios, seeks to revolutionize how we handle and analyze our data. We manage a diverse range of IP assets, including patents, trademarks, and copyrights, each generating large volumes of data across various stages of their lifecycle. The current infrastructure struggles with data delays and siloed information, leading to inefficiencies and missed opportunities. We aim to build a robust data pipeline leveraging Apache Kafka for event streaming, Spark for real-time analytics, and Airflow for orchestrating complex workflows. The integration of dbt for data transformation and Snowflake for scalable storage will support our need for agile, data-driven decision-making. This project is crucial for maintaining competitive advantage, ensuring compliance, and optimizing IP asset management. Implementing real-time data observability will enhance our ability to predict market trends and make informed strategic decisions. The solution must be scalable, secure, and capable of integrating seamlessly with existing systems.