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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」

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。

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！

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 today's data-driven world, cloud storage is no longer optional—it is the backbone of modern business, government, and digital life. The Complete Guide to Modern Cloud Storage Systems delivers a clear, comprehensive exploration of how cloud storage works, why it matters, and how to design systems that are secure, scalable, and future-ready. This audiobook takes listeners deep into the architecture of modern storage environments—from foundational infrastructure and distributed systems to advanced security protocols, encryption models, redundancy strategies, and compliance frameworks.

Data is at the center of many challenges in system design today. Difficult issues such as scalability, consistency, reliability, efficiency, and maintainability need to be resolved. In addition, there's an overwhelming variety of systems, including relational databases, NoSQL datastores, data...

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.

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 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.

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.

This audiobook is a summary of the advice I’ve given to software engineers over the years–and then some more. This audiobook follows the structure of a “typical” career path for a software engineer, from starting out as a fresh-faced software developer, through being a role model senior/lead, all the way to the staff/principle/distinguished level. It summarizes what I’ve learned as a developer and how I’ve approached coaching engineers at different stages of their careers.

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 analysis is a must-have skill that becomes more essential as the world becomes more data-driven. And one of the most effective ways to dive into data analysis is by learning a programming language. Python is a great place to start. This book explains everything you need to know to start using Python for data analysis.

“One of my favorite books of the year. It completely reshaped how I think about information and how and why I take notes.” —Daniel Pink, bestselling author of Drive A revolutionary approach to enhancing productivity, creating flow, and vastly increasing your ability to capture, remember...

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.

Millions of data enthusiasts from around the world compete on Kaggle, the most famous data science competition platform of them all. Participating in Kaggle competitions is a surefire way to improve your data analysis skills, network with an amazing community of data scientists, and gain valuable experience to help grow your career. The first audiobook of its kind, The Kaggle Book assembles in one place the techniques and skills you'll need for success in competitions, data science projects, and beyond.

Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. These new architectures have solid benefits, but they're also surrounded by a lot of hyperbole and confusion. This practical book provides a guided tour of these architectures to help data professionals understand the pros and cons of each.

Data science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project's success—and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering, and clearly explains how to apply the best practices from software engineering to data science.

Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you’ll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently bingeable book. Anyone can become a Data Head—an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.