Data Modeling Made Simple will provide the business or IT professional with a practical working knowledge of data modeling concepts and best practices. This book is written in a conversational style that encourages you to read it from start to finish and master these ten objectives:

Know when a data model is needed and which type of data model is most effective for each situation

Read a data model of any size and complexity with the same confidence as reading a book

Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at ...

THE DEFINITIVE GUIDE TO DIGITAL FORENSICS-NOW THOROUGHLY UPDATED WITH NEW TECHNIQUES, TOOLS, AND SOLUTIONS Complete, practical coverage of both technical and investigative skills Thoroughly covers modern devices, networks, and the Internet Addresses online and lab investigations, documentation, admissibility, and more Aligns closely with the NSA Knowledge Units and the NICE Cybersecurity Workforce Framework As digital crime soars, so does the need for experts who can recover and evaluate evid...

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 will learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available in the framework of the data engineering lifecycle. Authors Joe Reis and Matt Housley walk you through the data engineering lifecycle and show you how to sti...