Self-Service Data Analytics and Governance for Managers. Nathan E. Myers

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Self-Service Data Analytics and Governance for Managers - Nathan E. Myers

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      Table of Contents

      1  Cover

      2  Title Page

      3  Copyright

      4  Dedication

      5  Preface

      6  Acknowledgments

      7  About the Authors

      8  Introduction

      9  CHAPTER 1: Setting the Stage Impact Emergence of Data Analytics Self-Service Data Analytics Employee/Analyst/Operator Perspective Managers' Perspectives Executives' Strategic Perspectives Arguments for Self-Service Data Analytics Tooling Need for Self-Service Data Analytics Governance

      10  CHAPTER 2: Emerging AI and Data Analytics Tooling and Disciplines Introduction to Data Analytics Tooling Conclusion

      11  CHAPTER 3: Why Governance Is Essential and the Self-Service Data Analytics Governance Gap Governance Is Essential Mature Governance Frameworks Self-Service Data Analytics Governance Gap Structures Needed to Fill the Governance Gap Conclusion Note

      12  CHAPTER 4: Self-Service Data Analytics Project Governance Securing Sponsorship and Establishing the Governance Committee Extending Governance Precepts from Established Frameworks Conclusion Notes

      13  CHAPTER 5: Self-Service Data AnalyticsRisk Governance Setting Risk Appetite in an Environment of Changing Performance Expectations Data Analytics Risk Governance Enhances Value Creation Data Analytics Tool Selection Drives the Level of Partnership with IT Alignment of Finance Function Goals with Digital Transformation Capabilities Data Analytics Risk Governance Assessing Risks in the Analytics and Automation Environment Developing the Portfolio View of Risk Developing Risk Responses and Controls in the Analytics and Automation Environment Conclusion Notes

      14  CHAPTER 6: Self-Service Data Analytics Capabilities in Action with Alteryx Alteryx Functionality Alteryx in Action Conclusion

      15  CHAPTER 7: Process Discovery: Identify Opportunities, Evaluate Feasibility, and Prioritize Business Case for Systems versus Self-Service Data Analytics Process Discovery Phases and Methodology Conclusion Notes

      16  CHAPTER 8: Opportunity Capture and Heatmaps Opportunity Inventory Matrix Project Acceptance Criteria and Organizational Constraints Automation Heatmap and Prioritization Workflow Tooling Use Case Library Conclusion

      17  Glossary

      18  Index

      19  End User License Agreement

      List of Exhibits

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