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Technology is constantly changing, and new technologies are regularly being introduced. Business has been revolutionized by various technologies over the past few decades-namely, data science/artifical intelligence (AI) and blockchain. New technologies bring many opportunities with them, but they can also pose challenges for businesses, such as creating new and updated business models and finding the best adoption and digital transformation strategies. This books offers a guide to data science/AI and blockchain, two of the most relevant and important technologies for businesses today. Various topics are covered, including data science processes, AI-based businesses, and types of blockchain. Simple, straighforward descriptions of the technologies are provided along with more thorough explanations on how to effectively use them. By utilizing data science/AI and blockchain, businesses can stay competitive and be a catalyst for positive change. Chapter 1 describes the concept of emerging technologies, which includes any technology old or new that has unrealized potential. Through development or application, emerging technologies have the capability to change society. A brief history of technological disruption is provided, along with a description of the current "Fourth Industrial Revolution." Emergining technologies of the Fourth Industrial Revolution include data science/AI, blockchain, the Internet of Things (IoT), 3D printing, 5G technology, quantum computing, and robotics. Descriptions of all these technologies, as well as ways they can transform business, are offered. Ultimately, data science/AI and blockchain are two of the biggest emerging technologies right now and therefore are what decision makers need to know about. If businesses don't adopt these technologies, those businesses will eventually become obsolete.

Technology is constantly changing, and new technologies are regularly being introduced. Business has been revolutionized by various technologies over the past few decades-namely, data science/artifical intelligence (AI) and blockchain. New technologies bring many opportunities with them, but they can also pose challenges for businesses, such as creating new and updated business models and finding the best adoption and digital transformation strategies. This books offers a guide to data science/AI and blockchain, two of the most relevant and important technologies for businesses today. Various topics are covered, including data science processes, AI-based businesses, and types of blockchain. Simple, straighforward descriptions of the technologies are provided along with more thorough explanations on how to effectively use them. By utilizing data science/AI and blockchain, businesses can stay competitive and be a catalyst for positive change. Chapter 2 offers a brief overview of what data science is, how it can be useful, and how it can be applied. A short history of data science is provided. There are three core fields of data science: AI, machine learning (ML), and statistics; each of these fields and how they are part of data science is described. Machine learning is particularly essential to data science, and there are three main ML types: supervised learning, unsupervised learning, and reinforcement learning. These approaches are discussed along with other types of ML and how decision makers can use ML to their benefit. A thorough introduction to statistics is also given, including a description of different types of statistics and the benefits, applications, and potential problems of statistics-such as bias-for business. Case examples are offered, highlighting how data science can impact business.

Technology is constantly changing, and new technologies are regularly being introduced. Business has been revolutionized by various technologies over the past few decades-namely, data science/artifical intelligence (AI) and blockchain. New technologies bring many opportunities with them, but they can also pose challenges for businesses, such as creating new and updated business models and finding the best adoption and digital transformation strategies. This books offers a guide to data science/AI and blockchain, two of the most relevant and important technologies for businesses today. Various topics are covered, including data science processes, AI-based businesses, and types of blockchain. Simple, straighforward descriptions of the technologies are provided along with more thorough explanations on how to effectively use them. By utilizing data science/AI and blockchain, businesses can stay competitive and be a catalyst for positive change. Chapter 3 builds on the previous chapter and explores data strategies. A data strategy should be constantly updated, cover technical and organizational aspects, and ultimately point toward and work with the business strategy. Data strategies can offer additional revenue and a competitive advantage to companies. Guidelines for how to create a data strategy are provided, including starting with the business strategy, building data use cases, understanding data architecture and data governance, and managing AI projects. The data science hierarchy of needs model is described. CRISP-DM is a process used for planning data science projects; its six main phases are business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Tesseract Academy's 2-actor process is another popular process in data science and focuses on the problem definition, data management, the solution to the problem, and creating value through actionable insights. Several case studies are offered throughout the chapter.

Technology is constantly changing, and new technologies are regularly being introduced. Business has been revolutionized by various technologies over the past few decades-namely, data science/artifical intelligence (AI) and blockchain. New technologies bring many opportunities with them, but they can also pose challenges for businesses, such as creating new and updated business models and finding the best adoption and digital transformation strategies. This books offers a guide to data science/AI and blockchain, two of the most relevant and important technologies for businesses today. Various topics are covered, including data science processes, AI-based businesses, and types of blockchain. Simple, straighforward descriptions of the technologies are provided along with more thorough explanations on how to effectively use them. By utilizing data science/AI and blockchain, businesses can stay competitive and be a catalyst for positive change. Chapter 4 discusses data scientists-characteristics of good data scientists, skills they should have, their motivations, and how to effectively manage them. Essential skills for a data scientist include hacking skills, math and statistics knowledge, and substantive expertise. Data scientists tend to be curious, proactive, and innovative; many need to be mentally engaged, stimulated, and challenged. When hiring a data scientist, make sure to capitalize on these traits and their skill set. Ways for a company to attract data scientists are offered. Data scientists can be categorized into six groups: computer scientists, statisticians, quantitative specialists, self-taught data scientists, software platform users, and domain specialists. Each of these is described. The idea of a data-centric organization is also explored as well as how to build a data science culture and overcome resistance to change.

Technology is constantly changing, and new technologies are regularly being introduced. Business has been revolutionized by various technologies over the past few decades-namely, data science/artifical intelligence (AI) and blockchain. New technologies bring many opportunities with them, but they can also pose challenges for businesses, such as creating new and updated business models and finding the best adoption and digital transformation strategies. This books offers a guide to data science/AI and blockchain, two of the most relevant and important technologies for businesses today. Various topics are covered, including data science processes, AI-based businesses, and types of blockchain. Simple, straighforward descriptions of the technologies are provided along with more thorough explanations on how to effectively use them. By utilizing data science/AI and blockchain, businesses can stay competitive and be a catalyst for positive change. Chapter 5 explores blockchain, specifically what a nontechnical decision maker needs to know about it. A brief history of money and payment systems is offered, including the rise of blockchain. Blockchain is a decentralized ledger of records, a distributed database stored on multiple computers. Advantages of blockchain and differences between it and traditional databases are described. The elements of blockchain are explained, specifically blocks (containing data, nonces, and hashes), nodes, and miners. The relationship between cryptography and blockchain is discussed. The four main types of blockchain networks-public, private, hybrid, and consortium or federated-are explored, including their advantages, disadvantages, and uses. There are many applications of blockchain, several of which are described, including Bitcoin, nonfungible tokens (NFTs), and decentralized finance.

Technology is constantly changing, and new technologies are regularly being introduced. Business has been revolutionized by various technologies over the past few decades-namely, data science/artifical intelligence (AI) and blockchain. New technologies bring many opportunities with them, but they can also pose challenges for businesses, such as creating new and updated business models and finding the best adoption and digital transformation strategies. This books offers a guide to data science/AI and blockchain, two of the most relevant and important technologies for businesses today. Various topics are covered, including data science processes, AI-based businesses, and types of blockchain. Simple, straighforward descriptions of the technologies are provided along with more thorough explanations on how to effectively use them. By utilizing data science/AI and blockchain, businesses can stay competitive and be a catalyst for positive change. Chapter 6 explores how blockchain can be applied to and improve several industries, such as finance, cybersecurity, shipping, and the metaverse. All capital market participants will benefit from blockchain, including issuers, fund managers, investors, and regulators. Blockchain can improve supply chains as well, especially with development sourcing, production logistics, information systems management, and coordination. The likelihood of fraud regarding the authenticity of legal documents could be eliminated with blockchain; the shipping industry could increase efficiency while decreasing costs; cybersecurity could be enhanced; and file sharing could become decentralized. Blockchain could also assist in building the metaverse through providing proof of ownership, offering safe value transfer, and ensuring fair and transparent governance. Case examples are given throughout the chapter.

Technology is constantly changing, and new technologies are regularly being introduced. Business has been revolutionized by various technologies over the past few decades-namely, data science/artifical intelligence (AI) and blockchain. New technologies bring many opportunities with them, but they can also pose challenges for businesses, such as creating new and updated business models and finding the best adoption and digital transformation strategies. This books offers a guide to data science/AI and blockchain, two of the most relevant and important technologies for businesses today. Various topics are covered, including data science processes, AI-based businesses, and types of blockchain. Simple, straighforward descriptions of the technologies are provided along with more thorough explanations on how to effectively use them. By utilizing data science/AI and blockchain, businesses can stay competitive and be a catalyst for positive change. Chapter 7 discusses the maturity curve, a framework used to think about a technology's level of adoption within a business. Adopting emerging technologies tends to require a change in mindset. An organization must analyze its capabilities and the industry's potential to be disrupted by AI and blockchain. AI maturity is a concept that refers to various levels of adoption and looks at how much value a company can derive from AI. Four main components are needed to reach full adoption: knowledge, data, culture, and talent. All four of these are discussed. Questions are offered to help organizations find out if blockchain will be beneficial for them; these questions are categorized into business, technology, and legal questions. Businesses must be mindful of and adapt to technological changes in order to be successful in the future.