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This volume investigates, explores and describes approaches and methods to facilitate data understanding through analytics solutions based on principles, concepts and applications. But analysing data is also about involving the use of software. For this, and in order to cover some aspect of data analytics, this book uses software (Excel, SPSS, Python, etc) which can help readers to better understand the analytics process in simple terms and supporting useful methods in its application.

Principles of Big Data helps readers avoid the common mistakes that endanger all Big Data projects. By stressing simple, fundamental concepts, this book teaches readers how to organize large volumes of complex data, and how to achieve data permanence when the content of the data is constantly changing. General methods for data verification and validation, as specifically applied to Big Data resources, are stressed throughout the book. The book demonstrates how adept analysts can find relationships among data objects held in disparate Big Data resources, when the data objects are endowed with semantic support (i.e., organized in classes of uniquely identified data objects). Readers will learn how their data can be integrated with data from other resources, and how the data extracted from Big Data resources can be used for purposes beyond those imagined by the data creators. . Learn general methods for specifying Big Data in a way that is understandable to humans and to computers. . Avoid the pitfalls in Big Data design and analysis. . Understand how to create and use Big Data safely and responsibly with a set of laws, regulations and ethical standards that apply to the acquisition, distribution and integration of Big Data resources.

The authors provide an understanding of big data and MapReduce by clearly presenting the basic terminologies and concepts. They have employed over 100 illustrations and many worked-out examples to convey the concepts and methods used in big data, the inner workings of MapReduce, and single node/multi-node installation on physical/virtual machines. This book covers almost all the necessary information on Hadoop MapReduce for most online certification exams. Upon completing this book, readers will find it easy to understand other big data processing tools such as Spark, Storm, etc.. Ultimately, readers will be able to: understand what big data is and the factors that are involved understand the inner workings of MapReduce, which is essential for certification exams learn the features and weaknesses of MapReduce set up Hadoop clusters with 100s of physical/virtual machines create a virtual machine in AWS write MapReduce with Eclipse in a simple way understand other big data processing tools and their applications

RDF Database Systems is a cutting-edge guide that distills everything you need to know to effectively use or design an RDF database.This book starts with the basics of linked open data and covers the most recent research, practice, and technologies to help you leverage semantic technology.

PostgreSQL is a powerful open source database management system, now recognized as the experts' choice for a wide range of applications. This book contains useful administration recipes for improving the performance, security, and stability of your PostgreSQL solution.

As part of the best selling Pocket Primer series, this book is an effort to give programmers sufficient knowledge of data cleaning to be able to work on their own projects. It is designed as a practical introduction to using flexible, powerful (and free) Unix / Linux shell commands to perform common data cleaning tasks. The book is packed with realistic examples and numerous commands that illustrate both the syntax and how the commands work together. Companion files with source code are available for downloading from the publisher.Features:- A practical introduction to using flexible, powerful (and free) Unix / Linux shell commands to perform common data cleaning tasks- Includes the concept of piping data between commands, regular expression substitution, and the sed and awk commands- Packed with realistic examples and numerous commands that illustrate both the syntax and how the commands work together- Assumes the reader has no prior experience, but the topic is covered comprehensively enough to teach a pro some new tricks- Includes companion files with all of the source code examples (download from the publisher).

PostgreSQL is increasingly utilized in all kind of applications, starting from desktop to web and mobile applications. In this book, you will find the best ways to design, monitor and maintain your PostgreSQL solution, with suggestions and tips for high performance, troubleshooting and high availability.

Just Enough R! An Interactive Approach to Machine Learning and Analytics presents just enough of the R language, machine learning algorithms, statistical methodology, and analytics for the reader to learn how to find interesting structure in data. The approach might be called \"seeing then doing\" as it first gives step-by-step explanations using simple, understandable examples of how the various machine learning algorithms work independent of any programming language. This is followed by detailed scripts written in R that apply the algorithms to solve nontrivial problems with real data. The script code is provided allowing the reader to execute the scripts as they study the explanations given in the text. Features Gets you quickly using R as a problem-solving tool. Uses RStudio's integrated development environment. Shows how to interface R with SQLite. Includes examples using R's Rattle graphical user interface. Requires no prior knowledge of R, machine learning, or computer programming. Offers over 50 scripts written in R. Several of the scripts are problem-solving templates that with slight modification, can be used again and again. Covers the most popular machine learning techniques including ensemble-based methods and logistic regression. Includes end-of-chapter exercises many of which can be solved by modifying existing scripts. Includes datasets from several areas including business, health and medicine, and science.