Real-Time Data Pipeline for Enhanced Cleaning & Maintenance Optimization

As a startup in the Cleaning & Maintenance industry, we face the challenge of efficiently managing resources and ensuring service quality. Our goal is to harness real-time analytics to improve operational agility and customer satisfaction. The proposed project involves designing and implementing a robust data pipeline capable of ingesting, processing, and analyzing data streams from IoT devices, customer feedback platforms, and internal operational systems. Key components include using Apache Kafka for event streaming, Spark for data processing, and Airflow for orchestration. dbt, Snowflake, or BigQuery will be utilized for data warehousing and transformation, while Databricks will aid in machine learning model deployment for predictive analytics. This system will provide real-time dashboards and alerts to streamline our cleaning schedules, reduce downtime, and proactively address maintenance issues. The successful implementation of this project will lead to significant improvements in service efficiency, reduced operational costs, and enhanced customer satisfaction.