Isbn: 9798258831453 - scalable data architecture: the engineer’s guide to building maintainable systems that slash technical debt and eliminate on-call burnout: 3 (6 risultati)

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  • Lingua: Inglese

    Editore: Independently Published, 2026

    9798258831453

    Serie: Libro 3 di 5 - The AI Systems Architect Series

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    Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK

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    EUR 21,50

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    PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

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    Taschenbuch. Condizione: Neu. Neuware - Scalable Data Architecture: The Engineer's Guide to Building Maintainable Systems that Slash Technical Debt and Eliminate On-Call BurnoutAre your data pipelines fast enough to impress stakeholders, but fragile enough to wake engineers at 3:00 AM Modern data teams are drowning in schema drift, runaway cloud costs, broken dashboards, silent failures, messy transformations, and on-call pressure that never seems to end.Scalable Data Architecture gives data engineers, platform architects, analytics engineers, and technical leaders a practical playbook for building maintainable data systems that scale without turning teams into permanent firefighters. This book shows how to move beyond brittle scripts and reactive fixes by applying software engineering discipline to modern data platforms: data contracts, idempotent ingestion, partitioned storage, CI/CD, observability, governance, FinOps, real-time processing, and AI-ready vector infrastructure.Inside, readers will learn how to: - Build resilient ingestion pipelines that handle retries, schema drift, malformed records, and large files.- Design scalable data lakes with Parquet, Iceberg, partitioning, compaction, and lifecycle policies.- Reduce technical debt with modular SQL, dbt-style transformations, reusable macros, and documentation-as-code.- Control cloud data costs through query optimization, tagging, deduplication, and automated cost guards.- Monitor latency, freshness, volume, and quality before silent failures reach business users.- Deploy data changes safely with unit tests, blue-green deployment, rollback strategies, and automated governance.- Support real-time pipelines, vector data, RAG systems, and AI infrastructure without unnecessary complexity.If you want data systems that are easier to operate, safer to change, cheaper to run, and kinder to the engineers who maintain them, this book gives you the blueprint.

  • Lingua: Inglese

    Editore: Independently Published, 2026

    9798258831453

    Serie: Libro 3 di 5 - The AI Systems Architect Series

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    Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail

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    EUR 22,42

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    Paperback. Condizione: new. Paperback. Scalable Data Architecture: The Engineer's Guide to Building Maintainable Systems that Slash Technical Debt and Eliminate On-Call BurnoutAre your data pipelines fast enough to impress stakeholders, but fragile enough to wake engineers at 3:00 AM? Modern data teams are drowning in schema drift, runaway cloud costs, broken dashboards, silent failures, messy transformations, and on-call pressure that never seems to end.Scalable Data Architecture gives data engineers, platform architects, analytics engineers, and technical leaders a practical playbook for building maintainable data systems that scale without turning teams into permanent firefighters. This book shows how to move beyond brittle scripts and reactive fixes by applying software engineering discipline to modern data platforms: data contracts, idempotent ingestion, partitioned storage, CI/CD, observability, governance, FinOps, real-time processing, and AI-ready vector infrastructure.Inside, readers will learn how to: Build resilient ingestion pipelines that handle retries, schema drift, malformed records, and large files.Design scalable data lakes with Parquet, Iceberg, partitioning, compaction, and lifecycle policies.Reduce technical debt with modular SQL, dbt-style transformations, reusable macros, and documentation-as-code.Control cloud data costs through query optimization, tagging, deduplication, and automated cost guards.Monitor latency, freshness, volume, and quality before silent failures reach business users.Deploy data changes safely with unit tests, blue-green deployment, rollback strategies, and automated governance.Support real-time pipelines, vector data, RAG systems, and AI infrastructure without unnecessary complexity.If you want data systems that are easier to operate, safer to change, cheaper to run, and kinder to the engineers who maintain them, this book gives you the blueprint. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

  • Condizione: Nuovo

    EUR 22,43

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    Spedito in U.S.A.

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    Condizione: New. Print on Demand.

  • Lingua: Inglese

    Editore: Independently Published, 2026

    9798258831453

    Serie: Libro 3 di 5 - The AI Systems Architect Series

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    Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US

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    EUR 2286,39

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    PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

  • Lingua: Inglese

    Editore: Independently Published, 2026

    9798258831453

    Serie: Libro 3 di 5 - The AI Systems Architect Series

    • Brossura
    • Print on Demand

    Da: CitiRetail, Stevenage, Regno UnitoCitiRetail

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    Condizione: Nuovo

    EUR 25,22

    EUR 43,16 spedizione 
    Spedito da Regno Unito a U.S.A.

    Quantità: 1 disponibili

    Paperback. Condizione: new. Paperback. Scalable Data Architecture: The Engineer's Guide to Building Maintainable Systems that Slash Technical Debt and Eliminate On-Call BurnoutAre your data pipelines fast enough to impress stakeholders, but fragile enough to wake engineers at 3:00 AM? Modern data teams are drowning in schema drift, runaway cloud costs, broken dashboards, silent failures, messy transformations, and on-call pressure that never seems to end.Scalable Data Architecture gives data engineers, platform architects, analytics engineers, and technical leaders a practical playbook for building maintainable data systems that scale without turning teams into permanent firefighters. This book shows how to move beyond brittle scripts and reactive fixes by applying software engineering discipline to modern data platforms: data contracts, idempotent ingestion, partitioned storage, CI/CD, observability, governance, FinOps, real-time processing, and AI-ready vector infrastructure.Inside, readers will learn how to: Build resilient ingestion pipelines that handle retries, schema drift, malformed records, and large files.Design scalable data lakes with Parquet, Iceberg, partitioning, compaction, and lifecycle policies.Reduce technical debt with modular SQL, dbt-style transformations, reusable macros, and documentation-as-code.Control cloud data costs through query optimization, tagging, deduplication, and automated cost guards.Monitor latency, freshness, volume, and quality before silent failures reach business users.Deploy data changes safely with unit tests, blue-green deployment, rollback strategies, and automated governance.Support real-time pipelines, vector data, RAG systems, and AI infrastructure without unnecessary complexity.If you want data systems that are easier to operate, safer to change, cheaper to run, and kinder to the engineers who maintain them, this book gives you the blueprint. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.