Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.

Part 1.Foundational ethical principles. -- 1. The truth about AI bias / Cassie Kozyrkov -- 2. Introducing ethicize, the fully AI-driven cloud-based ethics solution! / Brian T. O'Neill -- 3. "Ethical" is not a binary concept / Tim Wilson -- 4. Cautionary ethics tales : phrenology, eugenics, ... and data science? / Sherrill Hayes -- 5. Leadership for the future : how to approach ethical transparency / Rado Kotorov -- 6. Rules and rationality / Christof Wolf Brenner -- 7. Understanding passive versus proactive ethics / Bill Schmarzo -- 8. Be careful with "decisions of the heart" / Hugh Watson -- 9. Fairness in the age of algorithms -- 10. Data science ethics : what is the foundational standard? / Mario Vela -- 11. Understand who your leaders serve / Hassen Masum -- Part 2. Data science and society. -- 12. Unbiased [is not] fair : for data science, it cannot be just about the math / Doug Hague -- 13. Trust, data science, and Stephen Covey / James Taylor -- 14. Ethics must be a cornerstone of the data science curriculum / Linda Burtch -- 15. Data storytelling : the tipping point between fact and fiction / Brent Dykes -- 16. Informed consent and data literacy education are crucial to ethics / Sherrill Hayes -- 17. First, do no harm / Eric Schmidt -- 18. Why research should be reproducible / Stuart Buck -- 19. Build multiperspective AI / Hassan Masum and Sébastien Paquet -- 20. Ethics as a competitive advantage / Dave Mathias -- 21. Algorithmic bias : are you a bystander or an upstander? / Jitendra Mudhol and Heidi Livingston Eisips -- 22. Data science and deliberative justice : the ethics of the voice of "the other" / Robert J. McGrath -- 23. Spam. Are you going to miss it? / John Thuma -- 24. Is it wrong to be right? / Marty Ellingsworth -- 25. We're not yet ready for a trustmark for technology / Hannah Kitcher and Laura James -- Part 3. The ethics of data. -- 26. How to ask for customers' data with transparency and trust / Rasmus Wegener -- 27. Data ethics and the lemming effect / Bob Gladden -- 28. Perceptions of personal data / Irina Raicu -- 29. Should data have rights? / Jennifer Lewis Priestley.