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Crimes Against Data: 101 true crime stories of people abusing and misusing data Kindle Edition
Just because there’s data doesn’t necessarily mean it’s the right data or people are using it properly. And as the saying goes, those who do not learn history are doomed to repeat it. Documenting and understanding these stories can prevent them from happening again.
Through a career in data, Merrill sees data problems (data crimes) caused by people treating data improperly. Recognizing data crimes is the first step in getting a resolution. This book details incidents of data crimes and their impact. Although not the person who created the data crime, Merrill can analyze what happened and propose a solution.
For people working in data, understanding data crimes and preventing them is essential to your organization. This book gives you specific stories you can share to explain the importance of getting the data right. For people being potential victims of data crimes, awareness will help you steer clear of data crimes, or interact with the offender to come to a resolution. You might finally understand why companies keep making mistakes.
- LanguageEnglish
- Publication dateJuly 27, 2023
- File size1626 KB
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About the Author
Product details
- ASIN : B0CD2FB1F6
- Publisher : Technics Publications (July 27, 2023)
- Publication date : July 27, 2023
- Language : English
- File size : 1626 KB
- Text-to-Speech : Enabled
- Screen Reader : Supported
- Enhanced typesetting : Enabled
- X-Ray : Not Enabled
- Word Wise : Enabled
- Sticky notes : On Kindle Scribe
- Print length : 130 pages
- Best Sellers Rank: #3,019,013 in Kindle Store (See Top 100 in Kindle Store)
- #347 in Big Data Businesses
- #2,759 in Computer Databases
- #3,051 in Computers & Technology Industry
- Customer Reviews:
About the author
Merrill has had the ultimate career of working in data. Starting with a BMath degree from the University of Waterloo, Merrill has worked consistently with companies across all industries to help them better manage their data to drive value from it. Being exposed to a wide variety of companies, Merrill has been able to see the same problems happening time and again, often caused by people not recognizing the value data brings to an organization and what happens when the data is mismanaged. Through education, coaching, and hands-on work, Merrill has been able to share her knowledge with companies to help them better improve their data infrastructure and prevent creating the next data crime.
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With a critical lens, Merill navigates through scenarios that call out our misguided data behaviors and remind us all that data is too important to take for granted.
From unveiling the repercussions of data misuse to advocating for conscientious data handling, the book is packed with examples presented in a way that both data and non-data people can understand. Merrill's thought-provoking examples urge readers to recognize their role in shaping the digital realm.
As we explore this data-driven era, this book equips us with the knowledge to make informed choices and foster a more ethical and considerate digital environment. If you are in the field of data management or just have an interest, you won't be disappointed with this addition to your toolkit.
We cite “data quality trainwrecks” (I believe the phrase was coined by Daragh O Brien) as cautionary tales for driving the importance of high-quality data. This slim volume by Merrill Albert takes a different tack. In example after example, she cites just how insidious, pervasive, and frustrating data quality errors are. Each is seemingly minor, but taken together, they make all our personal lives more difficult. And they certainly aren’t doing businesses or governments any good either!
Frankly, is time to demand better!
Whereas this book doesn’t dive deep into how to do data management, Merrill summarizes some common problems that lead to data crimes and emphasizes the importance of business and technology collaboration in preventing future issues. A must read if you just can’t figure out why data management is important.