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Guerrilla Analytics
A Practical Approach to Working with Data
A cookbook of techniques for analysts that will help you control, reproduce and share their outputs.
Enda Ridge (Author)
9780128002186, Elsevier Science
Paperback, published 24 September 2014
276 pages
22.9 x 15.1 x 1.8 cm, 0.41 kg
"... a very pleasant read…very useful to practitioners and managers who are newly responsible for data analytics or who have had difficulty in previous projects." --Computing Reviews
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
1. Preface Part 1: Principles 2. Introducing Guerrilla Analytics 3. Guerrilla Analytics: Challenges and Risks 4. Guerrilla Analytics Principles Part 2: Practice 5. Stage 1: Data Extraction 6. Step 2: Data Receipt 7. Step 3: Data Load 8. Stage 4: Analytics Coding for Ease of Review 9. Stage 5: Analytics Coding to Maintain Data Provenance 10. Stage 6: Creating Work Products 11. Stage 7: Reporting 12. Stage 8: Consolidating Knowledge in Builds Part 3: Testing 13. Introduction to Testing 14. Testing Data 15. Testing Builds 16. Testing Work Products Part 4: Building Guerrilla Capability 17. People 18. Process 19. Technology 20. Closing Remarks Appendix 21. Data Gymnastics References
Subject Areas: Data capture & analysis [UNC], Database programming [UMT]
