Real-Time Data Infrastructure for Donor Engagement Optimization

In today's dynamic non-profit environment, timely and accurate data is crucial for engaging donors effectively and optimizing fundraising strategies. Our organization is looking to build a state-of-the-art real-time data infrastructure that can process and analyze large volumes of data from diverse sources swiftly. The goal is to enhance our ability to respond to donor behaviors and preferences in real-time, thereby increasing donor satisfaction and retention. The project will utilize cutting-edge technologies including Apache Kafka for event streaming, Spark for large-scale data processing, and dbt for transforming data. With the integration of Snowflake and BigQuery, our team will create a unified data mesh architecture that ensures data observability and accessibility across the organization. We will also employ MLOps practices to streamline the deployment and monitoring of analytical models. The successful completion of this project will enable our non-profit to make data-driven decisions and tailor engagement strategies to individual donors. This will not only improve donor loyalty but also significantly boost fundraising revenues.