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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.

In our age of accelerating progress in so many fields, it’s easy to lose sight of the underlying innovation that makes the data analytics revolution possible. These 24 lectures introduce you to the key concepts, methods, and accomplishments of this versatile approach to problem solving. You need no expertise in mathematics to follow this exciting story. Tim Chartier, professor of mathematics and computer science, explains the basic computational techniques used in data analytics, but his focus is on how these ideas are applied and the amazing results they achieve.

Data Science for Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, listening to this book will help you understand what technologies, programming languages, and mathematical methods on which to focus.

Data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.

There are two remarkable phenomena that are unfolding almost simultaneously. The first is the emergence of a data-first world, where data has become a central driving force, shaping industries and fueling innovation. The second is the dawn of the AI age, propelled by the advent of Generative AI...

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.

Cybersecurity Essentials provides a comprehensive introduction to the field, with expert coverage of essential topics required for entry-level cybersecurity certifications. An effective defense consists of four distinct challenges: securing the infrastructure, securing devices, securing local networks, and securing the perimeter. Overcoming these challenges requires a detailed understanding of the concepts and practices within each realm.

Author Rashed Haq is a subject matter expert on AI, having developed AI and data science strategies, platforms, and applications for Publicis Sapient's clients for more than 10 years. He shares that expertise in the new audiobook Enterprise Artificial Intelligence Transformation. The first of its kind, this audiobook grants technology leaders the insight to create and scale their AI capabilities and bring their companies into the new generation of technology.

Innovation influences the market and its operators, especially about competition conditions. One of the most significant technological advances relates to the possibility of capturing a huge amount of information and processing them rapidly: two of the main features that make up the phenomenon known as big data. This not only entails the emergence of specialized operators in these activities, but also makes a "data economy" possible.