Guerrilla Analytics: A Practical Approach to Working with Data (Paperback)

Doing data science is difficult. Projects are typically very dynamic with requirements that change as data understanding grows. The data itself arrives piecemeal, is added to, replaced, contains undiscovered flaws and comes from a variety of sources. Teams also have mixed skill sets and tooling is often limited. Despite these disruptions, a data science team must get off the ground fast and begin demonstrating value with traceable, tested work products. This is when you need Guerrilla Analytics.

In this book, you will learn about:

• The Guerrilla Analytics Principles: simple rules of thumb for maintaining data provenance across the entire analytics life cycle from data extraction, through analysis to reporting. 
• Reproducible, traceable analytics: how to design and implement work products that are reproducible, testable and stand up to external scrutiny.
• Practice tips and war stories: 90 practice tips and 16 war stories based on real-world project challenges encountered in consulting, pre-sales and research.
• Preparing for battle: how to set up your team's analytics environment in terms of tooling, skill sets, workflows and conventions.
• Data gymnastics: over a dozen analytics patterns that your team will encounter again and again in projects.

進行資料科學是困難的。專案通常非常動態，需求會隨著對資料的理解而改變。資料本身是逐漸到來的，會被添加、替換，可能存在未發現的缺陷，並來自各種來源。團隊的技能組合也各不相同，工具通常也有限。儘管存在這些干擾，資料科學團隊必須快速啟動並開始展示具有可追溯性和經過測試的工作成果的價值。這就是你需要《游擊分析》的時候。

在這本書中，你將學習以下內容：
- 游擊分析原則：在整個分析生命週期中，從資料提取到分析再到報告，維護資料來源的簡單法則。
- 可重複、可追溯的分析：如何設計和實施可重複、可測試且經得起外部檢驗的工作成果。
- 實踐技巧和戰爭故事：基於在咨詢、售前和研究中遇到的真實專案挑戰，提供90個實踐技巧和16個戰爭故事。
- 準備戰鬥：如何在工具、技能組合、工作流程和慣例方面建立團隊的分析環境。
- 資料體操：團隊在專案中一再遇到的十幾種分析模式。