Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory but made accessible through numerous real-world examples - ready for immediate application to your next graph or presentation.

Advancement in technology and the resulting shifts in everyday practice have brought about a fast-growing "parallel world" with new material, new data, and new sources. Irrespective of how anyone describes it, the data trend is becoming increasingly real, increasingly prevalent, and far more significant. 

From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you'll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.

Today we think statistics are the enemy, numbers used to mislead and confuse us. That’s a mistake, Tim Harford says in The Data Detective. We shouldn’t be suspicious of statistics - we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often “the only way of grasping much of what is going on around us”.

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. 

Data Driven Business Transformation is the practical guide to harnessing your data to compete and thrive in today's dynamic marketplace. This essential resource provides the insight, knowledge and focus you require to transform your business - unlocking the power of data and revealing its hidden value. Delivering step-by-step instructions to every stage of data transformation, this book enables you to strengthen your data literacy and make effective data-driven decisions. 

You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. 

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. 

Learning Agile is a comprehensive guide to the most popular agile methods, written in a light and engaging style that makes it easy for you to learn. Agile has revolutionized the way teams approach software development, but with dozens of agile methodologies to choose from, the decision to "go agile" can be tricky. This practical book helps you sort it out, first by grounding you in agile's underlying principles, then by describing four specific - and well-used - agile methods: Scrum, extreme programming (XP), Lean, and Kanban. 

An algorithm is a set of rules or instructions you provide to a system. The system performs a specific process to answer a question using these instructions. As an amateur or expert, it is important for you to understand what an algorithm is and how you should define it. Once you learn to develop an algorithm, you can easily learn to develop code to execute that algorithm. This three-in-one audio guide will give you the knowledge you need.

As organizations shift from monolithic applications to smaller, self-contained microservices, distributed systems have become more fine-grained. But developing these new systems brings its own host of problems. This expanded second edition takes a holistic view of topics that you need to consider when building, managing, and scaling microservices architectures. Through clear examples and practical advice, author Sam Newman gives everyone from architects and developers to testers and IT operators a firm grounding in the concepts.

Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence - and even more so if we hope to participate in the future, rather than being simple bystanders.

From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of human memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.

Irrespective of how anyone describes it, the data trend is becoming increasingly real, increasingly prevalent, and far more significant. Collating and gathering data is one thing while processing it is an entirely separate issue. If you are hoping to derive reasonable insights from the data generated, you must understand the data you are gathering, the approaches that are required, and the appropriate techniques to use when analyzing this data. How exactly can all this be achieved - well, this is exactly where this audiobook comes in.

Whether you're new to the world of programming and are looking for clarity on what direction to take, or you're simply curious about what machine learning, AI, and big data has in store for the future and want to prepare for it, this guide makes it easy to actually understand implement machine learning and data analytics effectively.