In this book, the reader will discover the history, theory and practice of data-driven decision-making, learning how organisations and individual managers alike can utilise its methods to avoid cognitive biases and improve confidence in their decisions. It argues that value does not come from data, but from acting on data.
In this book, the reader will discover the history, theory and practice of data-driven decision-making, learning how organisations and individual managers alike can utilise its methods to avoid cognitive biases and improve confidence in their decisions. It argues that value does not come from data, but from acting on data.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Claus Grand Bang is Associate Professor at Dania Academy, Denmark. He has more than ten years of business experience developing companies based on data and another ten years in academia teaching students from all over the world. As a lecturer, he has specialized in the fields of applied data analysis, supply chain management, and project management. He created one of the first applied data analytics degrees in Europe. Now, as Head of Data and IT, at a global biotech company he applies what he has taught in academia.
Inhaltsangabe
1. Introduction: What is Data-Driven Decision Making and Why Does It Matter? 2. Data Strategy: How to Align Data Initiatives with Business Goals and Objectives 3. Data Products 4. Data Culture: How to Foster a Data-Driven Mindset (data literacy) and Behaviour 5. Data Sources: How to Find, Collect, and Manage Data for Business Value 6. Data Visualization and Presentation 7. Data Analysis: Understand How Descriptive, Predictive, and Prescriptive Analytics can suppport the organizational Decision Processes 8. Data Infrastructure: How to Build and Manage a Modern Data Stack 9. Data Ethics: How to Ensure The Data Practices Are Responsible, Secure, and Legal 10. Perspectives on Decision Making using generative AI
1. Introduction: What is Data-Driven Decision Making and Why Does It Matter? 2. Data Strategy: How to Align Data Initiatives with Business Goals and Objectives 3. Data Products 4. Data Culture: How to Foster a Data-Driven Mindset (data literacy) and Behaviour 5. Data Sources: How to Find, Collect, and Manage Data for Business Value 6. Data Visualization and Presentation 7. Data Analysis: Understand How Descriptive, Predictive, and Prescriptive Analytics can suppport the organizational Decision Processes 8. Data Infrastructure: How to Build and Manage a Modern Data Stack 9. Data Ethics: How to Ensure The Data Practices Are Responsible, Secure, and Legal 10. Perspectives on Decision Making using generative AI
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