Titres dans Science des données

The discipline of infonomics takes you beyond thinking and talking about information as an asset to actually valuing and treating it as one. Infonomics provides the foundation and methods for quantifying information asset value and tactics for using information as your competitive edge to drive growth.

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.

Marketing data isn’t a spreadsheet problem. It’s a people problem. In Data Lemonade, digital marketing strategist Malene Jorgensen shows you how to squeeze powerful insights from messy, overwhelming data and turn them into marketing that actually connectsThis isn’t just another analytics book. It’s a guide to making sense of data through the lens of psychology, behaviour, and decision-making. You’ll learn how to go beyond dashboards and dig into the human truths behind your marketing numbers so you can stop guessing and start scaling.

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.

Knowing how to craft SQL queries and navigate your way around a database is an essential skill if are a Database Administrator, System Administrator, or Programmer. This book guides you step-by-step by teaching you how to create databases, populate those databases with data, extract just the data you need, and much more.

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.

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.

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.

Time Series Forecasting in Python teaches you to build powerful predictive models from time-based data. Every model you create is relevant, useful, and easy to implement with Python. You’ll explore interesting real-world datasets like Google’s daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow.

While the world is transfixed by bitcoin mania, your competitors are tuning out the noise and making strategic bets on blockchain. Your rivals are effortlessly tracking every last link in their supply chains. They're making bureaucratic paper trails obsolete while keeping their customers' data safer and discovering new ways to use this next foundational technology to sustain their competitive advantage.

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.

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.

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.

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.

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.

R in Action, Second Edition teaches you how to use the R language by presenting examples relevant to scientific, technical, and business developers. Focusing on practical solutions, the book offers a crash course in statistics, including elegant methods for dealing with messy and incomplete data. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on forecasting, data mining, and dynamic report writing.

The use of analytics in sport is now well embedded. Marginal gains, the bedrock upon which the cycling coach Dave Brailsford built his greatest successes, are cornerstones of most sports nowadays. But, until recently, that did not apply to the biggest sport in the world. Not in soccer. It was as though this simplest of sports is too complicated for statistics. Or that only one statistic counts, the number of times the ball hits the back of the net. "The only statistic that counts", there’s an often used and annoying stock term.

Are you looking for an exciting and dynamic career in the tech industry? Look no further than data centers! Data centers are the backbone of the digital age. And now, with Jumpstart Your Career in Data Centers by Carrie Goetz, you can kickstart your career in this exciting field!

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.

Microsoft Power Platform for Dummies covers the essentials you need to know to get started with Microsoft Power Platform, the suite of business intelligence applications designed to make your enterprise work smarter and more efficiently.