Edosa Odaro is a cross-industry AI and data transformation leader who has helped over 35 international organizations deliver significant impact through data analytics, transformation strategy implementation and intelligent interventions. Based in London, UK and with over 20 years of industry experience, he is currently the Chief Data and Analytics Officer at Tawuniya and is on the board for the UK's National Institute for Health Data Science (HDR UK). Edosa Odaro has been named a Financial Times Top 100 Most Influential Leader and one of the UK's 30 Most Influential Black Leaders in FinTech.
Inhaltsangabe
Chapter 00: Introduction Section ONE: Vision: Discovering and capturing data value opportunities Chapter 01: What is data vision? Chapter 02: Capturing data visions Chapter 03: Why data visions of all size matter Chapter 04: The destructive impact of data vision misalignment Chapter 05: Simplifying data vision misalignments Section TWO: Obstacle: The things that stand between data visions and data value realisation Chapter 06: Obstacles of the past Chapter 07: Obstacles of the future Chapter 08: Obstacles of the present Section THREE: Value: Identifying, capturing and communicating data value Chapter 09: Capturing data value propositions Chapter 10: Measuring data value for business case and operational assurance Chapter 11: The data value measurement lifecycle Chapter 12: A data value account for data profits and losses Chapter 13: Presenting data value to the CXO, EXCO and the board Chapter 14: Conclusion: Bringing it all together
Chapter 00: Introduction Section ONE: Vision: Discovering and capturing data value opportunities Chapter 01: What is data vision? Chapter 02: Capturing data visions Chapter 03: Why data visions of all size matter Chapter 04: The destructive impact of data vision misalignment Chapter 05: Simplifying data vision misalignments Section TWO: Obstacle: The things that stand between data visions and data value realisation Chapter 06: Obstacles of the past Chapter 07: Obstacles of the future Chapter 08: Obstacles of the present Section THREE: Value: Identifying, capturing and communicating data value Chapter 09: Capturing data value propositions Chapter 10: Measuring data value for business case and operational assurance Chapter 11: The data value measurement lifecycle Chapter 12: A data value account for data profits and losses Chapter 13: Presenting data value to the CXO, EXCO and the board Chapter 14: Conclusion: Bringing it all together
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