Isbn: 9781032897158 - test-driven data analysis (chapman & hall/crc data science series) (23 resultados)

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  • Idioma: Inglés

    Editorial: Chapman and Hall/CRC, 2026

    1032897155 / 9781032897158

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    HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.

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    Editorial: Chapman and Hall/CRC, 2026

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    hardcover. Condición: New.

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    Editorial: Chapman and Hall/CRC, 2026

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    Editorial: Chapman and Hall/CRC, 2026

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    Editorial: Chapman and Hall/CRC, 2026

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  • Idioma: Inglés

    Editorial: Chapman and Hall/CRC, 2026

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    Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.

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    Condición: New. 2026. 1st Edition. hardcover. . . . . .

  • Idioma: Inglés

    Editorial: Chapman and Hall/CRC, 2026

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    Librería: Books Puddle, Woodside, NY, Estados Unidos de AmericaBooks Puddle

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  • Idioma: Inglés

    Editorial: Chapman and Hall/CRC, 2026

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    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

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  • Idioma: Inglés

    Editorial: Taylor and Francis Ltd, GB, 2026

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    Hardback. Condición: New. Test-driven data analysis is the synthesis of ideas from test-driven development of software to data-intensive work including data science, data analysis, and data engineering. It is a methodology for improving the quality of data and of analytical pipelines and processes. It can be thought of as data analysis as if the answers actually matter.Test-driven data analysis can be thought of as a sibling to reproducible research, with similar concerns, but greater emphasis on automated testing, and less requirement for a human to reproduce results. Extensive checklists are provided that can be used to improve quality before,during, and after analysis.Key Features:Prevents costly errors in analytical processes before they reach production through automated data validation and reference testing of data pipelines. Provides actionable checklists for issues beyond the reach of automated testing. Equips readers with open-source Python tools and language-agnostic command-line interfaces. Addresses testing challenges for modern LLM-based systems including chat-bots and coding assistants. Instills in analysts an inner voice that is always asking: "How is this misleading data misleading me?". …

  • Idioma: Inglés

    Editorial: Chapman and Hall/CRC, 2026

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  • Idioma: Inglés

    Editorial: CRC Press, 2026

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    Condición: New. Nicholas Radcliffe is the Founder and Director of Stochastic Solutions Limited, a Scottish company specializing in consulting in data science, data analysis, and data engineering. He has also, since 1995, been a Visiting Professor in the Operat.

  • Idioma: Inglés

    Editorial: Chapman and Hall/CRC, 2026

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    Librería: Kennys Bookstore, Olney, MD, Estados Unidos de AmericaKennys Bookstore

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    Condición: New. 2026. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.

  • Idioma: Inglés

    Editorial: CRC Press, 2026

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    Buch. Condición: Neu. Test-Driven Data Analysis | Nicholas J Radcliffe | Buch | Einband - fest (Hardcover) | Englisch | 2026 | CRC Press | EAN 9781032897158 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

  • Idioma: Inglés

    Editorial: Chapman & Hall, 2026

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    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

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    Hardcover. Condición: Brand New. 432 pages. 9.18x6.12x9.45 inches. In Stock.

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    Editorial: Taylor and Francis Ltd, GB, 2026

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    Hardback. Condición: New. Test-driven data analysis is the synthesis of ideas from test-driven development of software to data-intensive work including data science, data analysis, and data engineering. It is a methodology for improving the quality of data and of analytical pipelines and processes. It can be thought of as data analysis as if the answers actually matter.Test-driven data analysis can be thought of as a sibling to reproducible research, with similar concerns, but greater emphasis on automated testing, and less requirement for a human to reproduce results. Extensive checklists are provided that can be used to improve quality before,during, and after analysis.Key Features:Prevents costly errors in analytical processes before they reach production through automated data validation and reference testing of data pipelines. Provides actionable checklists for issues beyond the reach of automated testing. Equips readers with open-source Python tools and language-agnostic command-line interfaces. Addresses testing challenges for modern LLM-based systems including chat-bots and coding assistants. Instills in analysts an inner voice that is always asking: "How is this misleading data misleading me?". …

  • Idioma: Inglés

    Editorial: CRC Press Mai 2026, 2026

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Buch. Condición: Neu. Neuware - Test-driven data analysis is the synthesis of ideas from test-driven development of software to data-intensive work including data science, data analysis, and data engineering. It is a methodology for improving the quality of data and of analytical pipelines and processes. It can be thought of as data analysis as if the answers actually matter.Test-driven data analysis can be thought of as a sibling to reproducible research, with similar concerns, but greater emphasis on automated testing, and less requirement for a human to reproduce results. Extensive checklists are provided that can be used to improve quality before,during, and after analysis.Key Features: - Prevents costly errors in analytical processes before they reach production through automated data validation and reference testing of data pipelines.¿ Provides actionable checklists for issues beyond the reach of automated testing.¿ Equips readers with open-source Python tools and language-agnostic command-line interfaces.¿ Addresses testing challenges for modern LLM-based systems including chat-bots and coding assistants.¿ Instills in analysts an inner voice that is always asking: 'How is this misleading data misleading me '.…

  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd, 2026

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    Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail

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    Hardcover. Condición: new. Hardcover. Test-driven data analysis is the synthesis of ideas from test-driven development of software to data-intensive work including data science, data analysis, and data engineering. It is a methodology for improving the quality of data and of analytical pipelines and processes. It can be thought of as data analysis as if the answers actually matter.Test-driven data analysis can be thought of as a sibling to reproducible research, with similar concerns, but greater emphasis on automated testing, and less requirement for a human to reproduce results. Extensive checklists are provided that can be used to improve quality before,during, and after analysis.Key Features:Prevents costly errors in analytical processes before they reach production through automated data validation and reference testing of data pipelines. Provides actionable checklists for issues beyond the reach of automated testing. Equips readers with open-source Python tools and language-agnostic command-line interfaces. Addresses testing challenges for modern LLM-based systems including chat-bots and coding assistants. Instills in analysts an inner voice that is always asking: How is this misleading data misleading me? Test-driven data analysis is the synthesis of ideas from test-driven development of software to data-intensive work including data science, data analysis, and data engineering. It is a methodology for improving the quality of data and of analytical pipelines and processes. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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    Hardcover. Condición: new. Hardcover. Test-driven data analysis is the synthesis of ideas from test-driven development of software to data-intensive work including data science, data analysis, and data engineering. It is a methodology for improving the quality of data and of analytical pipelines and processes. It can be thought of as data analysis as if the answers actually matter.Test-driven data analysis can be thought of as a sibling to reproducible research, with similar concerns, but greater emphasis on automated testing, and less requirement for a human to reproduce results. Extensive checklists are provided that can be used to improve quality before,during, and after analysis.Key Features:Prevents costly errors in analytical processes before they reach production through automated data validation and reference testing of data pipelines. Provides actionable checklists for issues beyond the reach of automated testing. Equips readers with open-source Python tools and language-agnostic command-line interfaces. Addresses testing challenges for modern LLM-based systems including chat-bots and coding assistants. Instills in analysts an inner voice that is always asking: How is this misleading data misleading me? Test-driven data analysis is the synthesis of ideas from test-driven development of software to data-intensive work including data science, data analysis, and data engineering. It is a methodology for improving the quality of data and of analytical pipelines and processes. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

  • Idioma: Inglés

    Editorial: Chapman & Hall, 2026

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    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

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    EUR 259,76

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    Hardcover. Condición: Brand New. 432 pages. 9.18x6.12x9.45 inches. In Stock. This item is printed on demand.

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    Editorial: Taylor & Francis Ltd, 2026

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    Hardcover. Condición: new. Hardcover. Test-driven data analysis is the synthesis of ideas from test-driven development of software to data-intensive work including data science, data analysis, and data engineering. It is a methodology for improving the quality of data and of analytical pipelines and processes. It can be thought of as data analysis as if the answers actually matter.Test-driven data analysis can be thought of as a sibling to reproducible research, with similar concerns, but greater emphasis on automated testing, and less requirement for a human to reproduce results. Extensive checklists are provided that can be used to improve quality before,during, and after analysis.Key Features:Prevents costly errors in analytical processes before they reach production through automated data validation and reference testing of data pipelines. Provides actionable checklists for issues beyond the reach of automated testing. Equips readers with open-source Python tools and language-agnostic command-line interfaces. Addresses testing challenges for modern LLM-based systems including chat-bots and coding assistants. Instills in analysts an inner voice that is always asking: How is this misleading data misleading me? Test-driven data analysis is the synthesis of ideas from test-driven development of software to data-intensive work including data science, data analysis, and data engineering. It is a methodology for improving the quality of data and of analytical pipelines and processes. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…