Dark Data (eBook)

Why What You Don't Know Matters

David J. Hand (Autor)

eBook Download: PDF

2020
344 Seiten
Princeton University Press (Verlag)
978-0-691-19885-9 (ISBN)

Infos

A practical guide to making good decisions in a world of missing dataIn the era of big data, it is easy to imagine that we have all the information we need to make good decisions. But in fact the data we have are never complete, and may be only the tip of the iceberg. Just as much of the universe is composed of dark matter, invisible to us but nonetheless present, the universe of information is full of dark data that we overlook at our peril. In Dark Data, data expert David Hand takes us on a fascinating and enlightening journey into the world of the data we don't see.Dark Data explores the many ways in which we can be blind to missing data and how that can lead us to conclusions and actions that are mistaken, dangerous, or even disastrous. Examining a wealth of real-life examples, from the Challenger shuttle explosion to complex financial frauds, Hand gives us a practical taxonomy of the types of dark data that exist and the situations in which they can arise, so that we can learn to recognize and control for them. In doing so, he teaches us not only to be alert to the problems presented by the things we don't know, but also shows how dark data can be used to our advantage, leading to greater understanding and better decisions.Today, we all make decisions using data. Dark Data shows us all how to reduce the risk of making bad ones.

Produkt-Details

• Erscheint lt. Verlag: 18.2.2020
• Zusatzinfo: 6 b/w illus. 6 tables.
• Sprache: englisch
• Themenwelt: Informatik ► Datenbanken ► Data Warehouse / Data Mining
• Themenwelt: Naturwissenschaften
• Schlagworte: Accuracy and precision • adverse selection • Ambiguity • Analogy • anonymity • Approximation • arithmetic mean • Astronomer • Autism • average • awareness • Bankruptcy • Benford's Law • Blood pressure • Calculation • clinical trial • confidentiality • Confirmation Bias • credit card • credit score • crime statistics • Customer • Dark Data • Database • Data Science • data set • Decision-Making • detection • Disease • Economics • Effectiveness • estimation • experimental psychology • Explanation • Extrapolation • Financial transaction • Floor effect • Fraud • General Data Protection Regulation • hypothesis • Identifier • Identity Theft • Illustration • Imputation (statistics) • income • Indication (medicine) • inference • Information asymmetry • Insider Trading • insurance • insurance fraud • Investor • Lawsuit • Measurement • Meta-analysis • misinformation • Mismatch • missing data • Observational error • obstacle • percentage • plagiarism • Prediction • Probability • Proportionality (mathematics) • Pseudonymization • Quantity • Randomized Controlled Trial • randomness • Respondent • result • Rounding • salary • Sample Size • Sampling (Statistics) • Science • Scientist • Significant figures • Simulation • Skewness • Social Science • Statistic • Statistical hypothesis testing • statistician • Statistics • Suggestion • Symptom • synthetic data • Tax • tax avoidance • Technology • theory • Thought • Uncertainty • Unemployment • Variable (mathematics) • Wealth • Website • Writing • year
• ISBN-10: 0-691-19885-3 / 0691198853
• ISBN-13: 978-0-691-19885-9 / 9780691198859