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Data Pipelines

In the context of smart manufacturing and Industry 4.0, data pipelines are integral to managing the flow of data across various systems and processes. They are designed to efficiently collect, process, and transport large volumes of data generated from diverse sources such as Manufacturing Execution Systems (MES) systems, and Industrial Internet of Things (IIoT) devices. By enabling seamless data integration from sensors and machines on the production floor, data pipelines ensure a continuous flow of information essential for real-time analytics and decision-making. 

Key components of data pipelines include data ingestion, transformation, and storage, often implemented through robust architectures such as data lakes or data warehouses. These pipelines support ETL (Extract, Transform, Load) processes, ensuring data quality and consistency across the board. In the realm of smart manufacturing, data pipelines facilitate the implementation of machine learning models for predictive maintenance, quality control, and the development of digital twins.