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海外のトップ頭脳も予測した！　最新テクノロジーによる2030年の世界　テクノロジーはどこまで進化するのか？人間は駆逐される？AIって結局、わたしたちにどんな影響を与えるの？

ChatGPTと著者が二人三脚で執筆！「今の仕事にAIをどう使うか？　考え方一つで「AIの奴隷になるか、AIを奴隷にするか」くらいの大きな違いが出てくる」

技術書の表も裏も知り尽くした人気作家が、読書を血肉にするコツとテクニックを教えます。大好評の「技術書（コンピュータ書）」の読書術を指南する本のオーディオブック版が登場！

ジブンの得意×AIを操るチカラ＝GPT時代の知的生産術ＣｈａｔＧＰＴ時代のＡＩは「ことばで動く」ので、文系人材でも自由自在に操ることができます。

Author Martin Kleppmann helps you navigate the diverse data landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. 

「ChatGPT」（チャットジーピーティー）は⽂章⽣成AIです。⼈間が⼊⼒した質問に答える形で⽂章を返してくるので「対話型AI」とも呼ばれています。

In a world dazzled by digital promise, the profession of Data Science has acquired an almost mythical glow. Headlines celebrate it, industries chase it, and countless seekers imagine that mastery of this field will open a direct path to success. Yet behind this bright aura lies a more intricate reality—one shaped by discipline, ambiguity, intellectual rigor, and the quiet labour of confronting the unknown. This book invites the reader to step beyond the mirage and encounter the craft as it truly is.

The Sleeping Giant explores the potential of Algorand and the power of staking and compounding in the digital asset economy. In this short, direct book, Carl Aguillard explains how long-term thinking, patience, and disciplined investing can turn a quiet project into a powerful financial opportunity. This is not about hype or speculation. It is about understanding the technology, recognizing long-term potential, and allowing time and compounding to work in your favor.

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.

Data projects are an intrinsic part of an organization's technical ecosystem, but data engineers in many companies continue to work on problems that others have already solved. This hands-on guide shows you how to provide valuable data by focusing on various aspects of data engineering, including data ingestion, data quality, idempotency, and more.

In this comprehensive study guide, you will build a strong foundation in all topics covered on the certification exam, including the Databricks Lakehouse and its tools and benefits.

As data floods into your company, you need to put it to work right away—and SQL is the best tool for the job. With the latest edition of this introductory guide, author Alan Beaulieu helps developers get up to speed with SQL fundamentals for writing database applications, performing administrative tasks, and generating reports. You'll find new chapters on SQL and big data, analytic functions, and working with very large databases.

One key responsibility of product designers and UX practitioners is to conduct formal and informal research to clarify design decisions and business needs. But there’s often mystery around product research, with the feeling that you need to be a research Zen master to gather anything useful. But anyone can conduct product research. With this quick reference guide, you’ll learn a common language and set of tools to help you carry out research in an informed and productive manner. 

As data continues to grow and become more complex, organizations seek innovative solutions to manage their data effectively. Data mesh is one solution that provides a new approach to managing data in complex organizations. This practical guide offers step-by-step guidance on how to implement data mesh in your organization.

When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it's often difficult to understand what each one offers. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals.

Causal Inference provides a brief and nontechnical introduction to randomized experiments, propensity scores, natural experiments, instrumental variables, sensitivity analysis, and quasi-experimental devices. Ideas are illustrated with examples from medicine, epidemiology, economics and business, the social sciences, and public policy.

In Fusion Strategy, world-renowned innovation guru Vijay Govindarajan and digital strategy expert Venkat Venkataraman offer a first-of-its-kind playbook that will help industrial companies combine what they do best-create physical products-with what digitals do best-use algorithms and AI to parse expansive, interconnected datasets-to make strategic connections that would otherwise be impossible.

Excel skills alone are no longer enough. In 2025, the real advantage comes from knowing how to combine Excel with AI. ChatGPT for Excel Beginners shows you how to use ChatGPT as your personal spreadsheet assistant — helping you write formulas, clean messy data, automate tasks, and make better decisions without being an Excel expert.

Between 2012 and 2023, Ian Graham worked as Liverpool FC's Director of Research. His tenure coincided with the club’s greatest period of success since the 1980s, including winning the Premier League in 2020 – Liverpool’s first league title after an agonising 29 years. Here for the first time, Graham reveals the fascinating data that informed some of the club’s most pivotal moments of the past decade, from the appointment of Jurgen Klopp as manager in 2015 to the signing of Mohamed Salah in 2017.

In industry after industry, data, analytics, and AI-driven processes are transforming the nature of work. While we often still treat AI as the domain of a specific skill, business function, or sector, we have entered a new era in which AI is challenging the very concept of the firm. AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value.