Showing results for "Science" in Data Science

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.

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.

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.

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.

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.

Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey, this book presents ninety-seven concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data.

Drawing on years of work interpreting and explaining data about almost anything, renowned data journalist Kiko Llaneras offers practical tools and shortcuts to help you understand the numbers and make better decisions using a quantitative lens. Through a series of compelling examples, he reveals some of the surprising insights that a data-driven perspective can offer.

Celebrated data-driven growth leader Lillian Pierson delivers a masterclass in developing custom strategies to harness the full potential of data and AI within your organization. This book offers a clear, actionable roadmap for leveraging your company's data and technology assets to drive significant, reliable growth.

Slow systems are frustrating. They waste time and money. But making consistently great decisions about performance can be easy, if you understand what's going on. This book explains in a clear and thoughtful voice why systems perform the way they do. It's for anybody who's curious about how computer programs and other processes use their time and about what you can do to improve them. Through a mix of personal vignettes and technical use cases, Cary Millsap reviews the process of improving performance and provides best practices for optimizing systems efficiently.

From technology, media, and retail to sport teams, government agencies, and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety, and so much more. Organized for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved, and the processes put in place to make it practical, as well as the technical details, challenges, and lessons learned from each unique scenario.

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.

In Generative AI: Navigating the Course to the Artificial General Intelligence Future, Martin Musiol delivers an incisive and one-of-a-kind discussion of the current capabilities, future potential, and inner workings of generative artificial intelligence. In the book, you'll explore the short but eventful history of generative artificial intelligence, what it's achieved so far, and how it's likely to evolve in the future. You'll also get a peek at how emerging technologies are converging to create exciting new possibilities in the GenAI space.

Scott Hartley first heard the terms fuzzy and techie while studying political science at Stanford University. If you majored in the humanities or social sciences, you were a fuzzy. If you majored in the computer sciences, you were a techie. This informal division has quietly found its way into a default assumption that has misled the business world for decades: that it's the techies who drive innovation.

A team of dedicated tech executives delivers a business-focused approach based on a deep and engaging exploration of the models and data used in causal AI. The book’s discussions include both accessible and understandable technical detail and business context and concepts that frame causal AI in familiar business settings.

Dark Data explores the many ways in which we can be blind to missing data and how that can lead us to conclusions and actions that are mistaken, dangerous, or even disastrous. Examining a wealth of real-life examples, from the Challenger shuttle explosion to complex financial frauds, Hand gives us a practical taxonomy of the types of dark data that exist and the situations in which they can arise, so that we can learn to recognize and control for them.

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.

xGenius explores the interplay between analysis, tactics, and decision-making. It seeks to put the sport of football under the microscope with the aim of getting closer to the ultimate truth of what makes players, managers and teams successful. What, ultimately, wins football matches. Packed with examples from the Premier League and beyond, xGenius shows how xG and other performance analysis tools are helping answer previously unanswerable questions.

A revolution is under way across the globe, yet very few people understand it. Basic Blockchain explains everything you need to know to understand the technology that will soon disrupt and revolutionise everything from financial and health services to the property market and how we vote.

Neste livro que já se tornou um clássico, David Spiegelhalter — um dos maiores estatísticos da atualidade — combina a visão incomparável de um especialista com o entusiasmo de um aficionado e oferece um verdadeiro guia para explorarmos a arte dessa ciência que é muito mais do que um ramo da matemática. Em A arte da estatística, David Spiegelhalter utiliza a resolução de questões do mundo real como ponto de partida para introduzir conceitos estatísticos, dos simples aos mais complexos, sempre com notório didatismo.