
Dark Data: Why What You Don’t Know Matters
Audible Audiobook
– Unabridged
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A practical guide to making good decisions in a world of missing data
In 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.
- Listening Length9 hours and 45 minutes
- Audible release dateFeb. 18 2020
- LanguageEnglish
- ASINB07W72WWVB
- VersionUnabridged
- Program TypeAudiobook
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Product details
Listening Length | 9 hours and 45 minutes |
---|---|
Author | David J. Hand |
Narrator | David J. Hand |
Audible.ca Release Date | February 18 2020 |
Publisher | Princeton University Press |
Program Type | Audiobook |
Version | Unabridged |
Language | English |
ASIN | B07W72WWVB |
Best Sellers Rank | #140,703 in Audible Books & Originals (See Top 100 in Audible Books & Originals) #49 in Data Science #163 in Mathematics (Audible Books & Originals) #194 in Data Warehousing |
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