Название: Data for All (Final Release)Автор: John K. Thompson
Издательство: Manning Publications
Год: 2023
Страниц: 192
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB
Do you know what happens to your personal data when you are browsing, buying, or using apps? Discover how your data is harvested and exploited, and what you can do to access, delete, and monetize it.
Data for All empowers everyone—from tech experts to the general public—to control how third parties use personal data. Read this eye-opening book to learn:
The types of data you generate with every action, every day
Where your data is stored, who controls it, and how much money they make from it
How you can manage access and monetization of your own data
Restricting data access to only companies and organizations you want to support
The history of how we think about data, and why that is changing
The new data ecosystem being built right now for your benefit
The data you generate every day is the lifeblood of many large companies—and they make billions of dollars using it. In Data for All, bestselling author John K. Thompson outlines how this one-sided data economy is about to undergo a dramatic change. Thompson pulls back the curtain to reveal the true nature of data ownership, and how you can turn your data from a revenue stream for companies into a financial asset for your benefit.
Descriptive statistics are the statistical methods that we learned in high school and college. These are statistical techniques like averages—means, modes, and Gaussian distributions. Data scientists use these tools to create an exploratory data analysis (EDA). Data scientists use the results of the EDA phase of a project to illustrate to executives, senior managers, subject matter experts (SMEs) and others the state of the business operations as seen through data.
Predictive analytics uses historical data to illustrate patterns of actions, behaviors, and transactions to understand how businesses operate, how people interact, how supply chains work, and how price affects behavior. Data scientists bring together multiple sources of related data to create one or more models that produce results that are as close as possible to how the world actually works. That is the primary objective of predictive analytics: to build a model or a stream of models that take data and predict as accurately as possible what the future of that business process or business environment will look like.
Data scientists bring these data sets together and create features that feed into models. Features can be raw or natural data, aggregated data, derived data, synthetic data, or any combination of the varying types of data we have discussed. The goal of predictive analytics is to predict what will happen in the future with the best possible accuracy.
about the technology
Do you know what happens to your personal data when you’re browsing and buying? New global laws are turning the tide on companies who make billions from your clicks, searches, and likes. This eye-opening book provides an inspiring vision of how you can take back control of the data you generate every day.
about the book
Data for All gives you a step-by-step plan to transform your relationship with data and start earning a “data dividend”—hundreds or thousands of dollars paid out simply for your online activities. You’ll learn how to oversee who accesses your data, how much different types of data are worth, and how to keep private details private.
what's inside:
The types of data you generate with every action, every day
How you can manage access and monetization of your own data
The history of how we think about data, and why that is changing
The new data ecosystem being built right now for your benefit
about the reader
For anyone who is curious or concerned about how their data is used. No technical knowledge required.
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