Blockchain Basics: A Non-Technical Introduction in 25 Steps

Drescher, Daniel

ISBN 10: 1484226038 / ISBN 13: 9781484226032

Published by Apress, 2017

About this Item

Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

Seller Inventory # 002121245U

Bibliographic Details

• Title: Blockchain Basics: A Non-Technical Introduction in 25 Steps
• Publisher: Apress
• Publication Date: 2017
• Language: English
• ISBN 10: 1484226038
• ISBN 13: 9781484226032
• Binding: paperback
• Edition: 1st ed.
• Condition: Good

About this title

Synopsis

In 25 concise steps, you will learn the basics of blockchain technology. No mathematical formulas, program code, or computer science jargon are used. No previous knowledge in computer science, mathematics, programming, or cryptography is required. Terminology is explained through pictures, analogies, and metaphors.

This book bridges the gap that exists between purely technical books about the blockchain and purely business-focused books. It does so by explaining both the technical concepts that make up the blockchain and their role in business-relevant applications.

What You'll Learn

• What the blockchain is
  
• Why it is needed and what problem it solves
  
• Why there is so much excitement about the blockchain and its potential
  
• Major components and their purpose
  
• How various components of the blockchain work and interact
  
• Limitations, why they exist, and what has been done to overcome them
  
• Major application scenarios

Who This Book Is For

Everyone who wants to get a general idea of what blockchain technology is, how it works, and how it will potentially change the financial system as we know it

About the Author

Daniel Drescher is an experienced banking professional who has held positions in electronic security trading in a range of banks. His recent activities have focused on automation, machine learning and big data in the context of security trading. Amongst others, Daniel holds a Doctorate in Econometrics from the Technical University of Berlin and an MSc in Software Engineering from the University of Oxford.