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"StreamSets Data Integration Architecture and Design"
"StreamSets Data Integration Architecture and Design" is an authoritative resource designed for data engineers, architects, and IT leaders seeking to master robust, agile, and scalable data integration solutions with StreamSets. The book provides a comprehensive view of the modern data integration landscape, covering foundational paradigms such as ETL, ELT, and streaming, alongside the operational challenges of hybrid architectures, big data, and DataOps. Special emphasis is given to the critical role of metadata management, data lineage, and governance, framing StreamSets as a pivotal player within the contemporary ecosystem.
Diving deep into the architecture and capabilities of the StreamSets platform, the book explores architectural fundamentals—from control and execution planes to deployment models, security, and observability—before moving into practical design patterns and technical strategies for building high-performing data pipelines. Detailed sections guide readers through pipeline modeling, schema evolution, error handling, and modular design principles, as well as connectivity to a vast array of data sources, integration layers, and streaming protocols. Coverage extends to advanced processing techniques, including real-time transformation, enrichment, and scalable orchestration with enterprise scheduling, DevOps integration, and self-healing automation.
Recognizing the importance of security and compliance, the book provides actionable guidance on data governance, privacy preservation, regulatory frameworks, and policy-driven management, ensuring end-to-end enterprise readiness. Readers will also benefit from architectural reference solutions and real-world blueprints for data lakes, cloud migration, IoT, and multi-cloud strategies, positioning StreamSets as an extensible and future-proof integration platform. Through in-depth technical insights and actionable best practices, "StreamSets Data Integration Architecture and Design" is an essential guide for unlocking the full potential of scalable, secure, and resilient data integration in the modern enterprise.
© 2025 HiTeX Press (E-bog): 6610000964840
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E-bog: 12. juli 2025
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