Architecting Data Science: Using Information Architecture to Make Data Science Predictable

Architecting Data Science: Using Information Architecture to Make Data Science Predictable

Neal Fishman , Cole Stryker
まだ評価がありません
2020 · 英語 · キンドル
棚に追加

この本を評価する


ブックジャーナルをエクスポート

説明

In a world increasingly driven by data, the authors present a compelling framework for transforming data science into a systematic and predictable process. By blending information architecture with data science principles, they illustrate how organizations can effectively harness data for decision-making and strategic initiatives.

Through a methodical approach, the book equips business professionals with the tools to integrate data science seamlessly into their operations. Readers will learn how to establish robust frameworks that foster repeatability and reliability, ultimately enhancing efficiency and driving success in their projects. The insights offered aim to empower teams to approach complex data challenges with confidence.

本の詳細

形式 キンドル
ページ数 350ページ
言語 英語
公開されました 5月 5, 2020
出版社 Wiley
ISBN-10 1119694388
ISBN-13 9781119694380
棚に追加

この本を評価する


ブックジャーナルをエクスポート