Implementation of a Real-Time Data Pipeline for Enhanced Customer Insights

We are an SME in the fast-evolving Data Analytics & Science industry, looking to build a state-of-the-art real-time data pipeline. Our goal is to enhance our ability to provide immediate, actionable insights that drive customer satisfaction and business growth. The project involves designing and implementing a real-time data pipeline using Apache Kafka for event streaming, Spark for data processing, and Snowflake for data warehousing. Additionally, tools like dbt and Airflow will be utilized for data transformations and orchestration. Our current batch processing system limits our capacity to respond swiftly to dynamic market demands and customer behaviors. By transitioning to a real-time analytics framework, we aim to significantly reduce decision latency and improve data observability across our operations. This project will involve close collaboration with our data science and IT teams to ensure a seamless integration with existing systems, ultimately enabling a data mesh architecture that supports decentralized data ownership and governance.