Data Science for Decision Makers & Data Professionals

Daan van Beek • Boek • hardback

• Samenvatting
  This brand-new Data Science book offers a tantalizing new perspective for anyone who wants want to let the data do the talking and successfully implement AI and Data Science. This unique handbook combines Business Intelligence (BI), Artificial Intelligence (AI), big data analytics, machine learning, and data science in an easy-to-understand package. Make your organization data-driven in 10 steps by logically connecting these concepts. Learn how to use this complete Data Science book to make your organization intelligent and data-driven. Strengthen your organization’s immune system using an AI, BI, and Big Data analytics cocktail.
  
  Data-driven working & data science are the new normal. The tech giants are leading the way, using big data analytics and robots in their everyday activities. For most organizations, managers, decision-makers, and data professionals that’s still a bridge too far, but that future is coming ever closer. This book is for them. In ten clear steps, the author describes the path to creating a mature, intelligent, and data-driven organization. The author shares his novel, refreshing perspective on (big) data, KPIs, dashboards, Artificial Intelligence (AI), and decision-making. He reveals how managers and data professionals can make better and faster decisions using AI and Business Intelligence, leaving their mark on the digital transformation while securing the organization’s future. Embed decision-making based on facts and data into your daily routine and significantly increase the quality of your decisions. Use machine learning to identify patterns and develop your own “8 million dollar insights”. Most AI books read like technical manuals. This book approaches AI from a different angle and with a much wider scope. Under the data science umbrella, the author covers the principles of data-driven working, many kinds of algorithms, and the most important aspects of architecture. He sketches a holistic profile of the intelligent, data-driven organization, a proven success formula applied by tens of thousands of organizations worldwide. Get started now, using a simple report, a cool dashboard, big data, or experiment with a decision tree or neural network. Daan van Beek studied Information Science and attained his Master of Science in AI. He is the founder of Passionned Group, a 100% independent international consulting agency and training institute. Daan hosts AI and BI masterclasses around the world and teaches at various universities.
• Productinformatie
  Binding : Hardback
  Distributievorm : Boek (print, druk)
  Formaat : 175mm x 247mm
  Aantal pagina's : 432
  Uitgeverij : Passionned Publishers
  ISBN : 9789082809169
  Datum publicatie : 01-2021
  
• Inhoudsopgave
  Foreword 9 Acknowledgments 13 Introduction 17 1 The importance and benefits of data science 35 1.1 Introduction 35 1.2 Fundamental developments 37 1.3 The Data-Decision gap 39 1.4 Twenty-five advantages of effective data science 45 2 Data science processes and the intelligent organization 67 2.1 Introduction 67 2.2 The four maturity levels of data science 69 2.3 The three stages of the intelligent organization 73 2.4 The contours of the intelligent organization 75 2.5 Four key concepts 80 3 The senses of the intelligent organization 85 3.1 Introduction 85 3.2 Developing sensors: four approaches 86 3.3 Key Performance Indicators: KPIs 101 3.4 Machine learning models & big data 107 3.5 Valuable insights 112 3.6 The context of sensors and indicators 114 3.7 Criteria of information and indicators 120 3.8 Setting norms and targets for indicators 124 4 The brain of the intelligent organization 135 4.1 Introduction 135 4.2 Processing: turning data into knowledge & action 136 4.3 AI, algorithms, and machine learning 147 4.4 The processors: stakeholders 170 4.5 Requirements of the processing cycle 178 4.6 Business Intelligence frameworks 181 5 The limbs of the intelligent organization 189 5.1 Introduction 189 5.2 Research the necessity of an agile organization 192 5.3 Expertise 194 5.4 The structure of the agile organization 201 5.5 Social infrastructure 215 6 The architecture of the intelligent organization 229 6.1 Introduction 229 6.2 Principles dictate the architecture 232 6.3 The data warehouse and ETL 236 6.4 The data lake 259 6.5 Portals, mobile data science, and reflex BI 266 6.6 Metadata: the glue of the intelligent organization 271 7 Data science instruments and applications 279 7.1 Introduction 279 7.2 Data science instruments 279 7.3 Data science applications 300 8 Data science projects 319 8.1 Introduction 319 8.2 How to approach data science projects 321 8.3 The data science project cycle: approach & steps 322 8.4 Top ten data science risks and obstacles 341 8.5 Data science roles and competencies 347 9 Data science strategy and governance 363 9.1 Introduction 363 9.2 Data science strategy and maturity: the map 365 9.3 Governance of the BI cycle: the compass 373 9.4 The BI Competency Center (BICC) 376 9.5 The data science roadmap 380 9.6 Privacy legislation and ethics 383 10 The future of organizations, society, and data science 391 10.1 Introduction 391 10.2 The future of data science 391 10.3 The social effects of AI and data science 394 Epilogue 401 Reference List 405 Index 421
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