If you are a business user or data professional, this book will give you a solid grounding in the use of TIBCO Spotfire. This book assumes no prior knowledge of Spotfire or even basic data and visualization concepts.

Create innovative informatics solutions with TIBCO Spotfire Key FeaturesGet to grips with a variety of TIBCO Spotfire features to create professional applicationsUse different data and visualization techniques to build interactive analyses.Simplify BI processes and understand data analysis and visualizationBook Description The need for agile business intelligence (BI) is growing daily, and TIBCO Spotfire® combines self-service features with essential enterprise governance and scaling capabilities to provide best-practice analytics solutions. Spotfire is easy and intuitive to use and is a rewarding environment for all BI users and analytics developers. Starting with data and visualization concepts, this book takes you on a journey through increasingly advanced topics to help you work toward becoming a professional analytics solution provider. Examples of analyzing real-world data are used to illustrate how to work with Spotfire. Once you've covered the AI-driven recommendations engine, you'll move on to understanding Spotfire's rich suite of visualizations and when, why and how you should use each of them. In later chapters, you'll work with location analytics, advanced analytics using TIBCO Enterprise Runtime for R®, how to decide whether to use in-database or in-memory analytics, and how to work with streaming (live) data in Spotfire. You'll also explore key product integrations that significantly enhance Spotfire's capabilities.This book will enable you to exploit the advantages of the Spotfire serve topology and learn how to make practical use of scheduling and routing rules. By the end of this book, you will have learned how to build and use powerful analytics dashboards and applications, perform spatial analytics, and be able to administer your Spotfire environment efficiently What you will learnWork with Spotfire on its web, Cloud, PC, Mac and mobile clientsDeploy Spotfire's suite of visualization types effectively and intelligentlyBuild user-friendly analytics frameworks and analytics applicationsExplore Spotfire's predictive analytics capabilitiesUse Spotfire's location analytics capabilities to create interactive spatial analysesWrite IronPython scripts with the Spotfire APILearn the different ways Spotfire can be deployed and administeredWho this book is for If you are a business intelligence or data professional, this book will give you a solid grounding in the use of TIBCO Spotfire. This book requires no prior knowledge of Spotfire or any basic data and visualization concepts.

Business professionals who want to advance their careers need to have a strong understanding of how to utilize business intelligence. This new book provides a comprehensive introduction to the basic business and technical concepts they’ll need to know. It integrates case studies that demonstrate how to apply the material. Business professionals will also find suggested further readings that will develop their knowledge and help them succeed.

This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, graphics, and accompanying tabular listings—for all the methods they cover. Complete R scripts for all examples and figures are provided for readers to use as models for their own analyses. This book can serve as a standalone text for statistics majors at the master’s level and for other quantitatively oriented disciplines at the doctoral level, and as a reference book for researchers. Classical concepts and techniques are illustrated with a variety of case studies using both newer graphical tools and traditional tabular displays. New graphical material includes: an expanded chapter on graphics a section on graphing Likert Scale Data to build on the importance of rating scales in fields from population studies to psychometrics a discussion on design of graphics that will work for readers with color-deficient vision an expanded discussion on the design of multi-panel graphics expanded and new sections in the discrete bivariate statistics capter on the use of mosaic plots for contingency tables including the n×2×2 tables for which the Mantel–Haenszel–Cochran test is appropriate an interactive (using the shiny package) presentation of the graphics for the normal and t-tables that is introduced early and used in many chapters

The third international conference on INformation Systems Design and Intelligent Applications (INDIA – 2016) held in Visakhapatnam, India during January 8-9, 2016. The book covers all aspects of information system design, computer science and technology, general sciences, and educational research. Upon a double blind review process, a number of high quality papers are selected and collected in the book, which is composed of three different volumes, and covers a variety of topics, including natural language processing, artificial intelligence, security and privacy, communications, wireless and sensor networks, microelectronics, circuit and systems, machine learning, soft computing, mobile computing and applications, cloud computing, software engineering, graphics and image processing, rural engineering, e-commerce, e-governance, business computing, molecular computing, nano-computing, chemical computing, intelligent computing for GIS and remote sensing, bio-informatics and bio-computing. These fields are not only limited to computer researchers but also include mathematics, chemistry, biology, bio-chemistry, engineering, statistics, and all others in which computer techniques may assist.

This document brings together a set of latest data points and publicly available information relevant for Energy Industry. We are very excited to share this content and believe that readers will benefit immensely from this periodic publication immensely.

Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces The revised and updated third edition of Data Mining contains in one volume an introduction to a systematic approach to the analysis of large data sets that integrates results from disciplines such as statistics, artificial intelligence, data bases, pattern recognition, and computer visualization. Advances in deep learning technology have opened an entire new spectrum of applications. The author—a noted expert on the topic—explains the basic concepts, models, and methodologies that have been developed in recent years. This new edition introduces and expands on many topics, as well as providing revised sections on software tools and data mining applications. Additional changes include an updated list of references for further study, and an extended list of problems and questions that relate to each chapter.This third edition presents new and expanded information that: • Explores big data and cloud computing • Examines deep learning • Includes information on convolutional neural networks (CNN) • Offers reinforcement learning • Contains semi-supervised learning and S3VM • Reviews model evaluation for unbalanced data Written for graduate students in computer science, computer engineers, and computer information systems professionals, the updated third edition of Data Mining continues to provide an essential guide to the basic principles of the technology and the most recent developments in the field.

Discover what you can do with R! Introducing the R system, covering standard regression methods, then tackling more advanced topics, this book guides users through the practical, powerful tools that the R system provides. The emphasis is on hands-on analysis, graphical display, and interpretation of data. The many worked examples, from real-world research, are accompanied by commentary on what is done and why. The companion website has code and datasets, allowing readers to reproduce all analyses, along with solutions to selected exercises and updates. Assuming basic statistical knowledge and some experience with data analysis (but not R), the book is ideal for research scientists, final-year undergraduate or graduate-level students of applied statistics, and practising statisticians. It is both for learning and for reference. This third edition expands upon topics such as Bayesian inference for regression, errors in variables, generalized linear mixed models, and random forests.

Contains profiles of hundreds of the best, rapidly-growing mid-size employers of 100 to 2,500 employees. These are highly-successful companies, located nationwide, that are of vital importance to job-seekers of all types.