Real-time Data Pipeline Implementation for Enhanced Event Personalization

As a leading enterprise in the Catering & Events industry, we've identified a pressing need to leverage real-time data processing to enhance our service offerings. Our current data architecture does not support the level of immediacy and personalization our clients demand. We are looking to build a robust real-time data pipeline to streamline data ingestion and processing, allowing us to make swift, informed decisions during events. The project involves the integration of Apache Kafka for event streaming, Spark for real-time analytics, and Airflow for orchestrating workflows. We aim to implement a data mesh architecture to promote data democratization across our organization. Further, using Snowflake or BigQuery, we will establish a scalable data warehouse solution, while dbt will be used for data transformation. The outcome will empower our event management teams to tailor experiences on-the-fly, driving client satisfaction and competitive advantage. The initiative will be executed over a 16-24 week period, with a budget allocation of $50,000 to $150,000.