Real-Time Data Pipeline for Enhanced Cleaning Operations Efficiency

As a growing company in the Cleaning & Maintenance industry, we are experiencing challenges in optimizing our operations due to the lack of real-time data insights. We are looking to build a robust data pipeline that will allow us to gather, process, and analyze data from various sources, such as IoT-enabled cleaning devices and workforce management systems, in real time. This project involves setting up a data mesh architecture that integrates with our existing systems, utilizing Apache Kafka for event streaming, and processing data with Spark and Airflow. The transformed data will be stored in Snowflake and made accessible through BigQuery for analytics. Additionally, implementing MLOps practices will facilitate the deployment of predictive models, enhancing our ability to anticipate maintenance needs and allocate resources efficiently. The successful completion of this project will empower our teams with actionable insights, reduce downtime, and increase customer satisfaction.