Enterprise Data Infrastructure Optimization for Real-Time Analytics

As a leading business consulting firm, we aim to provide our clients with the most accurate and timely insights. Our current data infrastructure struggles to support real-time analytics, limiting our ability to offer prompt decision-making support. This project involves revamping our data architecture using state-of-the-art technologies such as Apache Kafka for event streaming, Spark for large-scale data processing, and Airflow for workflow automation. Additionally, we aim to implement a data mesh approach to decentralize data ownership, enhancing data observability and reducing bottlenecks. By integrating Snowflake and BigQuery, we will ensure seamless data storage and accessibility across our global operations. This initiative will not only improve our internal data processes but also enhance the quality of our consulting services, offering clients real-time data-driven insights. The project is expected to span 16-24 weeks, with a budget of $50,000 - $150,000, reflecting its critical importance to our business strategy.