KNIME Workflow Design and Automation: Definitive Reference for Developers and Engineers

"KNIME Workflow Design and Automation"

Unlock the full potential of KNIME with "KNIME Workflow Design and Automation," a comprehensive guide for data professionals, engineers, and enterprise architects seeking to master advanced workflow engineering and automation. This book delves deeply into the architecture and inner workings of the KNIME platform, presenting robust best practices for workflow initialization, structuring projects for maintainability, and integrating with source control systems. From granular explanations of node architecture and execution semantics to sophisticated data modeling and metadata handling, each chapter equips readers with the tools and understanding necessary to design efficient, scalable, and reproducible analytics workflows.

Building on a solid foundation, the book explores the complexities of large-scale data wrangling, encompassing high-performance batch and real-time processing, diverse data source integration, and advanced cleaning and transformation techniques. Readers will discover comprehensive methods for orchestrating and automating workflows, including dynamic control flows, reusable components, robust error handling, and real-time monitoring. Detailed insights into interoperability—covering databases, APIs, cloud storage, and streaming systems—enable seamless enterprise data integration with a strong emphasis on security and governance.

Moving beyond the fundamentals, the book presents cutting-edge material on machine learning workflow patterns, automated feature engineering, model validation, and scalable deployment strategies. Advanced topics such as custom node development, scripting integrations, and enterprise-scale workflow governance ensure that professionals can extend KNIME's capabilities to fit any strategic application. Illustrated with real-world case studies from life sciences, finance, manufacturing, marketing, and MLOps, "KNIME Workflow Design and Automation" serves as an authoritative reference and practical roadmap for delivering high-impact data solutions across industries.

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Udgivelsesdato

E-bog: 16. juni 2025