The Real Work of Data Science : Turning Data into Information, Better Decisions, and Stronger Organizations

Intro -- Title Page -- Copyright Page -- Contents -- About the Authors -- Preface -- About the Companion Website -- Chapter 1 A Higher Calling -- The Life-Cycle View -- Problem Elicitation: Understand the Problem -- Goal Formulation: Clarify the Short‐term and Long-term Goals -- Data Collection: Identify Relevant Data Sources and Collect the Data -- Data Analysis: Use Descriptive, Explanatory, and Predictive Methods -- Formulation of Findings: State Results and Recommendations -- Operationalization of Findings: Suggest Who, What, When, and How -- Communication of Findings: Communicate Findings, Decisions, and Their Implications to Stakeholders -- Impact Assessment: Plan and Deploy an Assessment Strategy -- The Organizational Ecosystem -- Organizational Structure -- Organizational Maturity -- Once Again, Our Goal -- Chapter 2 The Difference Between a Good Data Scientist and a Great One -- Implications -- Chapter 3 Learn the Business -- The Annual Report -- SWOTs and Strategic Analysis -- The Balanced Scorecard and Key Performance Indicators -- The Data Lens -- Build Your Network -- Implications -- Chapter 4 Understand the Real Problem -- A Telling Example -- Understanding the Real Problem -- Implications -- Chapter 5 Get Out There -- Understand Context and Soft Data -- Identify Sources of Variability -- Selective Attention -- Memory Bias -- Implications -- Chapter 6 Sorry, but You Can't Trust the Data -- Most Data Is Untrustworthy -- Dealing with Immediate Issues -- Getting in Front of Tomorrow's Data Quality Issues -- Implications -- Chapter 7 Make It Easy for People to Understand Your Insights -- First, Get the Basics Right -- Presentations Get Passed Around -- The Best of the Best -- Implications -- Chapter 8 When the Data Leaves Off and Your Intuition Takes Over -- Modes of Generalization -- Implications.