Real-Time Analytics Platform for Enhanced Advertising Campaign Performance

As a mid-sized advertising agency, we handle multiple client accounts with varying campaign requirements. Currently, our data processing and analytics are lagging, resulting in delayed insights that often miss critical market shifts. We seek a data engineering solution that allows us to process, analyze, and act on advertising data in real-time. The project will involve setting up a data pipeline using Apache Kafka for event streaming, leveraging Spark for real-time data processing, and employing Snowflake or BigQuery for scalable data storage. Airflow will be used for orchestrating complex workflows, while dbt will handle data transformations to ensure clean, actionable datasets. By implementing a data mesh architecture, we aim to decentralize our data infrastructure, empowering different teams with access to relevant data streams, thus fostering a culture of data observability and operational excellence across the organization. The ultimate goal is to provide our clients with enhanced campaign performance insights, leading to better allocation of advertising budgets and improved ROI.