Kedro Catalog Essentials: The Complete Guide for Developers and Engineers

"Kedro Catalog Essentials"

Designed as the definitive guide for data engineering professionals and advanced analytics practitioners, "Kedro Catalog Essentials" delivers a comprehensive examination of the Kedro data catalog’s architecture, configuration, and operationalization. The book begins by dissecting Kedro’s modular pipeline design, emphasizing the central role of the catalog as both a unifying abstraction and a flexible interface for managing datasets within scalable, maintainable workflows. Readers are guided through the foundational principles of catalog-driven engineering, learning how to architect resilient, decoupled pipelines that foster reproducibility, traceability, and cross-environment consistency.

Building on these architectural underpinnings, the book explores an array of advanced topics critical for modern data teams, from catalog configuration management with YAML, parameter templating, and secret handling, to meticulous strategies for catalog versioning and secure, enterprise-scale deployments. It provides in-depth coverage of native and custom DataSet types—including integrations for cloud storage, partitioned data, and non-core community offerings—ensuring practitioners can support everything from rapid experimentation to robust production systems. Additional chapters delve into related operational disciplines such as debugging, monitoring, auditability, and compliance, with hands-on advice for integrating catalog observability into CI/CD pipelines, as well as adhering to organizational governance, security, and recovery requirements.

Whether you are seeking to implement advanced runtime catalog generation, orchestrate hybrid or multi-cloud workflows, or future-proof your data platform through extensible architectures and AI-powered catalog insights, "Kedro Catalog Essentials" is an indispensable reference. Featuring actionable guidance, practical patterns, and illustrative case studies, this book equips data and ML engineers, architects, and platform owners with the knowledge and confidence needed to unlock the full potential of Kedro’s data catalog, driving reliability, innovation, and success in complex data-driven organizations.

© 2025 HiTeX Press (E-Book): 6610000965342

Erscheinungsdatum

E-Book: 13. Juli 2025