The Data Flow Map: A Practical Guide to Clear and Creative Analytics in Any Data Environment
暫譯: 數據流圖：在任何數據環境中進行清晰且創意分析的實用指南
Ryberg, Nick
- 出版商: Apress
- 出版日期: 2026-01-03
- 售價: $1,370
- 貴賓價: 9.5 折 $1,302
- 語言: 英文
- 頁數: 204
- 裝訂: Quality Paper - also called trade paper
- ISBN: 9798868818820
- ISBN-13: 9798868818820
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相關分類:
Data-visualization
海外代購書籍(需單獨結帳)
相關主題
商品描述
Unlock the secrets of practical data analysis with the Data Flow Map framework--a game-changing approach that transcends tools and platforms. This book isn't just another programming manual; it's a guide to thinking and communicating about data at a higher level. Whether you're working with spreadsheets, databases, or AI-driven models, you'll learn how to express your analytics in clear, common language that anyone can understand.
In today's data-rich world, clarity is the real challenge. Technical details often obscure insights that could drive real impact. The Data Flow Map framework simplifies complexity into three core motions: source, focus, and build. The first half of the book explores these concepts through illustrations and stories. The second half applies them to real-world datasets using tools like Excel, SQL, and Python, showing how the framework works across platforms and use cases.
A vital resource for analysts at any level, this book offers a practical, tool-agnostic approach to data analysis. With hands-on examples and a universal mental model, you'll gain the confidence to tackle any dataset, align your team, and deliver insights that matter. Whether you're a beginner or a seasoned pro, the Data Flow Map framework will transform how you approach data analytics.
What You Will Learn- Grasp essential elements applicable to every data analysis workflow
- Adapt quickly to any dataset, tool, or platform
- Master analytic thinking at a higher level
- Use analytics patterns to better understand the world
- Break complex analysis into manageable, repeatable steps
- Iterate faster to uncover deeper insights and better solutions
- Communicate findings clearly for better decision-making
商品描述(中文翻譯)
解鎖實用數據分析的秘密，透過數據流圖框架——這是一種超越工具和平台的顛覆性方法。本書不僅僅是另一本程式設計手冊；它是一本關於以更高層次思考和溝通數據的指南。無論您是在使用電子表格、數據庫還是人工智慧驅動的模型，您將學會如何用清晰、通俗的語言表達您的分析，讓任何人都能理解。
在當今數據豐富的世界中，清晰度是真正的挑戰。技術細節往往會掩蓋可能帶來實際影響的見解。數據流圖框架將複雜性簡化為三個核心動作：來源、焦點和構建。本書的前半部分通過插圖和故事探討這些概念。後半部分則使用 Excel、SQL 和 Python 等工具將其應用於現實世界的數據集，展示該框架如何在不同平台和用例中運作。
這本書是任何層級分析師的重要資源，提供了一種實用的、與工具無關的數據分析方法。透過實作範例和通用的思維模型，您將獲得信心來處理任何數據集，協調您的團隊，並提供重要的見解。無論您是初學者還是資深專業人士，數據流圖框架將改變您對數據分析的看法。
您將學到的內容：
- 掌握適用於每個數據分析工作流程的基本要素
- 快速適應任何數據集、工具或平台
- 在更高層次上掌握分析思維
- 使用分析模式更好地理解世界
- 將複雜的分析分解為可管理、可重複的步驟
- 更快地迭代以發現更深層的見解和更好的解決方案
- 清晰地傳達發現，以促進更好的決策
本書適合對象：
有志於成為數據專業人士和經驗豐富的分析師，從初學者到資深數據工程師，專注於數據收集、分析和決策。
作者簡介
Nick Ryberg has developed analytics across platforms, from Microsoft Excel and Access to more complex systems such as Postgres, Hadoop, and Spark SQL. Whether working on personal computers, Linux servers, mainframes, or even a Raspberry Pi, Nick thrives with a keyboard and a table or two of data.
As tools have improved, becoming more user-friendly and capable of handling larger datasets, Nick has observed that how we think and share our processes hasn't evolved much. At best, it's a messy whiteboard with bubbles and arrows; at worst, it's raw code left behind by a developer who departed years ago.
Throughout Nick's career, the focus has been on solving challenging analytic problems using these tools. The most complex problems encountered aren't related to sourcing, cleaning data, or mastering specific tools. Instead, the most difficult aspects involve thinking differently about solutions, sharing and brainstorming ideas, switching platforms, and documenting processes for future users.
作者簡介(中文翻譯)
Nick Ryberg 在多個平台上開發了分析工具，從 Microsoft Excel 和 Access 到更複雜的系統，如 Postgres、Hadoop 和 Spark SQL。無論是在個人電腦、Linux 伺服器、大型主機，甚至是 Raspberry Pi 上，Nick 都能在鍵盤和一兩張數據表中茁壯成長。
隨著工具的改進，變得更加使用者友好並能處理更大的數據集，Nick 觀察到我們思考和分享過程的方式並沒有太大變化。充其量，它只是一個雜亂的白板，上面有氣泡和箭頭；最糟糕的情況是，留下的原始代碼是多年前離開的開發者所遺留下來的。
在 Nick 的職業生涯中，重點一直是使用這些工具解決具有挑戰性的分析問題。所遇到的最複雜問題並不涉及數據的來源、清理或掌握特定工具。相反，最困難的方面在於以不同的方式思考解決方案、分享和集思廣益、切換平台，以及為未來的使用者記錄過程。
