Showing titles in Data Science

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. 

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.

The data your company generates is enormously valuable. But without the right strategy, you’ll never unlock that value - and you might even put your company at risk. Data Leverage is the first comprehensive book on the exploding opportunity of corporate data partnerships. The authors, Christian and Jay Ward, are experts - a business strategist and a lawyer who, together, have executed hundreds of deals.

Until very recently, if you were to ask most doctors, they would tell you there were only two kinds of medicine: the quack kind, and the evidence-based kind. The former is baseless, and the latter based on the best information human effort could buy. Well, Eric Topol isn't most doctors, and he suggests you entertain the notion of a third kind of medicine, one that will make the evidence-based state-of-the-art stuff look scarcely better than an alchemist trying to animate a homunculus in a jar.

Go in Action is for any intermediate-level developer who has experience with other programming languages and wants a jump-start in learning Go or a more thorough understanding of the language and its internals. This book provides an intensive, comprehensive, and idiomatic view of Go. It focuses on the specification and implementation of the language, including topics like language syntax, Go's type system, concurrency, channels, and testing.

Work with data like a pro using this guide that breaks down how to organize, apply, and most importantly, understand what you are analyzing in order to become a true data ninja.

Data analytics offer an incredible opportunity to predict the future, engage with new technological advancements, and gain valuable insights about your business. But unless you're staying on top of the cutting edge of analytics, your company is wasting that potential-and your competitors will be gaining speed while you fall behind. These articles by experts and consultants will help you understand today's essential thinking about what data analytics are capable of and how to adopt their use in your organization.

R is an open-source statistical environment and programming language that has grown in popularity for data management and analysis in various industries. “R” Programming teaches you all the R you'll ever need in a rapid and painless manner. Learn how to use R to transform raw data into knowledge, understanding, and insight. This book introduces you to R, RStudio, and the tidyverse, a set of R tools that work together to make data research simple, fluent, and enjoyable. 

In today's data-driven world, information is a powerful asset. But how do you ensure this information is reliable, secure, and usable? The CompTIA Data+ certification equips you with the foundational knowledge and skills to navigate the exciting realm of data storage, management, and analysis. This comprehensive guidebook serves as your roadmap to CompTIA Data+ mastery.

This new edition - more than 50 percent new and revised - is a significant update from the previous one and reveals how to harness the newest data mining methods and techniques to solve common business problems. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk. In addition, they cover more advanced topics, such as preparing data for analysis and creating the necessary infrastructure for data mining at your company.

Getting the most from your data requires winning the Enrichment game. Learn the game rules and fit the “pieces,” processes, and people together to achieve a high score in data quality and data useability. First, demonstrate the value of the data our organizations gather, protect, and, in some cases, share. Second, enrich the available data by providing more context on the meaning of the data. Chief data officers, data strategists, data architects, data managers, data scientists, business analysts, and data governance and business intelligence professionals all play the game, and ...

Veteran data and analytics professional delivers a practical and hands-on discussion on how to accelerate business results using high-quality data.

Graph-Powered Machine Learning teaches to use graph-based algorithms and data organization strategies to develop superior machine learning applications. You’ll dive into the role of graphs in machine learning and big data platforms, and take an in-depth look at data source modeling, algorithm design, recommendations, and fraud detection. Explore end-to-end projects that illustrate architectures and help you optimize with best design practices.

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.

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.

The Real Business of Blockchain is one of the first audiobooks on this transformative technology written for business leaders. Authors David Furlonger and Christophe Uzureau - both of Gartner, the world-renowned research and advisory company - will help you: assess how blockchain will impact your business by cutting through the hype and finding the real story; explore the value proposition that blockchain technologies offer; make smart near- and mid-term investments in your blockchain strategy; and position you and your organization in a new competitive landscape in the future.

To succeed in today's transforming business world, organizations need business intelligence capabilities to make smarter decisions faster than ever before. This updated second edition of Learn Power BI takes you on a journey of data exploration and discovery.

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.

Master the concepts and strategies underlying success and progress in data science. From the author of the bestsellers, Data Scientist and Julia for Data Science, this book covers four foundational areas of data science. The first area is the data science pipeline including methodologies and the data scientist's toolbox. The second are essential practices needed in understanding the data including questions and hypotheses. The third are pitfalls to avoid in the data science process. The fourth is an awareness of future trends and how modern technologies like Artificial Intelligence (AI) fit...