Unifying Business, Data, and Code: Designing Data Products with JSON Schema
Itelman, Ron, Viotti, Juan Cruz
- 出版商: O'Reilly
- 出版日期: 2024-03-05
- 定價: $2,300
- 售價: 9.5 折 $2,185
- 貴賓價: 9.0 折 $2,070
- 語言: 英文
- 頁數: 354
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1098145003
- ISBN-13: 9781098145002
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相關分類:
JavaScript
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商品描述
In the modern symphony of business, each section-from the technical to the managerial-must play in harmony. Authors Ron Itelman and Juan Cruz Viotti introduce a bold methodology to synchronize your business and technical teams, transforming them into a single, high-performing unit.
Misalignment between business and technical teams halts innovation. You'll learn how to transcend the root causes of project failure-the ambiguity, knowledge gaps, and blind spots that lead to wasted efforts.
The unifying methodology in this book will teach you these alignment tools and more:
- The four facets of data products: A simple blueprint that encapsulates data and business logic helps eliminate the most common causes of wasted time and misunderstanding
- The concept compass: An easy way to identify the biggest sources of misalignment
- Success spectrums: Define the required knowledge and road map your team needs to achieve success
- JSON Schema: Leverage JSON and JSON Schema to technically implement the strategy at scale, including extending JSON Schema with custom keywords, understanding JSON Schema annotations, and hosting your own schema registry
- Data hygiene: Learn how to design high-quality datasets aligned with creating real business value, and protect your organization from the most common sources of pain
商品描述(中文翻譯)
在現代商業交響樂中,從技術到管理的每個部門都必須和諧共奏。作者Ron Itelman和Juan Cruz Viotti介紹了一種大膽的方法論,將您的業務和技術團隊同步,將它們轉變為一個高效的整體。
業務和技術團隊之間的不協調會阻礙創新。您將學習如何超越專案失敗的根本原因-模糊性、知識差距和盲點,這些原因導致了浪費的努力。
本書中的統一方法將教您這些協調工具和更多內容:
- 數據產品的四個方面:一個簡單的藍圖,將數據和業務邏輯封裝起來,有助於消除浪費時間和誤解的最常見原因。
- 概念指南針:一種簡單的方法來識別不協調的最大來源。
- 成功光譜:定義團隊實現成功所需的知識和路線圖。
- JSON Schema:利用JSON和JSON Schema在技術上實施策略,包括使用自定義關鍵字擴展JSON Schema,理解JSON Schema註釋,以及託管自己的模式註冊表。
- 數據衛生:學習如何設計與創造真正商業價值相一致的高質量數據集,並保護您的組織免受最常見的痛點。