Titres dans Science des données

Gain a competitive edge in today’s data-driven world and build a rich career as a data professional that drives business success and innovation… Today, data is everywhere… and it has become the essential building block of this modern society. And that’s why now is the perfect time to pursue a career in data. But what does it take to become a competent data professional? This book is your ultimate guide to understanding the fundamentals of data analytics, helping you unlock the expertise of efficiently solving real-world data-related problems.

Data Lake Architecture will explain how to build a useful data lake where data scientists and data analysts can solve business challenges and identify new business opportunities. Learn how to structure data lakes as well as analog, application, and text-based data ponds to provide maximum business value. Understand the role of the raw data pond and when to use an archival data pond. Leverage the four key ingredients for data lake success: metadata, integration mapping, context, and metaprocess.

Imagine a world where your data isn’t controlled by faceless corporations. A world where the internet isn’t a walled garden, but a boundless frontier of freedom, security, and opportunity. Welcome to Decentralizing the Future: The Story of Flux and the Rise of Web3. In this riveting journey, we unravel the story of the internet’s next great leap from the centralized grip of Web2, where a handful of tech giants hold the keys, to the decentralized promise of Web3. At the heart of this revolution is Flux, a trailblazer building the backbone of a new digital world.

Mastering OSINT and Dark Web Investigations: by Eric Waldrep is an advanced guide for professionals navigating the complex worlds of Open Source Intelligence (OSINT) and the Dark Web. The book equips investigators with technical skills, methodologies, and ethical frameworks to handle cases ranging from corporate fraud to national security threats.

Between 1959 and 1989, Soviet scientists and officials made numerous attempts to network their nation - to construct a nationwide computer network. None of these attempts succeeded, and the enterprise had been abandoned by the time the Soviet Union fell apart. Meanwhile, ARPANET, the American precursor to the Internet, went online in 1969. Why did the Soviet network, with top-level scientists and patriotic incentives, fail while the American network succeeded? Find out.

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.

Curious about AI but unsure where to start? AI for Beginners Made Simple breaks down complex concepts into clear, practical insights—no tech background required! Discover how AI can enhance your career, automate tasks, and open new opportunities with easy-to-follow explanations, real-world applications, and hands-on projects. Learn AI basics, navigate ethical concerns, and access free resources—all without the jargon overload.

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.

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.

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.

Businesses own more data than ever before, but it's of no value if you don't know how to use it. Data governance manages the people, processes, and strategy needed for deploying data projects to production. But doing it well is far from easy: Less than one fourth of business leaders say their organizations are data driven. In Designing Data Governance from the Ground Up, you'll build a cross-functional strategy to create roadmaps and stewardship for data-focused projects, embed data governance into your engineering practice, and put processes in place to monitor data after deployment.

Structured query language, or SQL (pronounced "sequel" by many), is the most widely used programming language in database management and is the standard language for relational database management systems (RDBMS). SQL programming allows users to return, analyze, create, manage, and delete data within a database - all within a few commands.

You can be incredibly productive with Azure without mastering every feature, function, and service. Learn Azure in a Month of Lunches, Second Edition gets you up and running quickly, teaching you the most important concepts and tasks in 21 practical bite-sized lessons. As you explore the examples, exercises, and labs, you'll pick up valuable skills immediately and take your first steps to Azure mastery! This fully revised new edition covers core changes to the Azure UI, new Azure features, Azure containers, and the upgraded Azure Kubernetes Service.

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.

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.

Computer science is a field that deals with the study of computers and computational systems. It encompasses both the theoretical and practical aspects of computing, including algorithms, data structures, programming languages, software engineering, and more. It's about understanding how computers work, how they can solve problems, and how they interact with humans and other systems.

Data science is an exciting field and will remain as such for many years to come. With more people than ever studying data science, machine learning & AI, there is an increasing gap between what you learn in the classroom and how data science is done in the real world. Inspired by conversations with nearly 10,000 social media followers, this book aims to close that gap and address some of the common tasks that you will face in your first year as a data scientist.

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.

Docker in Action teaches listeners how to create, deploy, and manage applications hosted in Docker containers. After starting with a clear explanation of the Docker model, you will learn how to package applications in containers, including techniques for testing and distributing applications. You will also learn how to run programs securely and how to manage shared resources. Using carefully designed examples, the book teaches you how to orchestrate containers and applications from installation to removal.

When "metadata" became breaking news, appearing in stories about surveillance by the National Security Agency, many members of the public encountered this once-obscure term from information science for the first time. Should people be reassured that the NSA was "only" collecting metadata about phone calls - information about the caller, the recipient, the time, the duration, the location - and not recordings of the conversations themselves? Or does phone call metadata reveal more than it seems?