Visualizing Streaming Data

Interactive Analysis Beyond Static Limits

Author: Anthony Aragues

Publisher: "O'Reilly Media, Inc."

ISBN: 1492031801

Category: Computers

Page: 200

View: 2335


While tools for analyzing streaming and real-time data are gaining adoption, the ability to visualize these data types has yet to catch up. Dashboards are good at conveying daily or weekly data trends at a glance, though capturing snapshots when data is transforming from moment to moment is more difficult—but not impossible. With this practical guide, application designers, data scientists, and system administrators will explore ways to create visualizations that bring context and a sense of time to streaming text data. Author Anthony Aragues guides you through the concepts and tools you need to build visualizations for analyzing data as it arrives. Determine your company’s goals for visualizing streaming data Identify key data sources and learn how to stream them Learn practical methods for processing streaming data Build a client application for interacting with events, logs, and records Explore common components for visualizing streaming data Consider analysis concepts for developing your visualization Define the dashboard’s layout, flow direction, and component movement Improve visualization quality and productivity through collaboration Explore use cases including security, IoT devices, and application data

Exam Prep for: Visualizing Streaming Data

Author: David Mason

Publisher: Rico Publications


Category: Education

Page: 800

View: 8368


Computer science is the theory, experimentation, and engineering that form the basis for the design and use of computers. This book provides over 2,000 Exam Prep questions and answers to accompany the text Visualizing Streaming Data Items include highly probable exam items: economy, correlation, Column, Stored procedure, Query language, Independence, Entity-relationship model, Microsoft Access, Perl, Communication, probability, Data security, Comparison, motivation, Legacy system, Visualization, and more.

Real-Time Analytics

Techniques to Analyze and Visualize Streaming Data

Author: Byron Ellis

Publisher: John Wiley & Sons

ISBN: 1118838025

Category: Computers

Page: 432

View: 8368


Construct a robust end-to-end solution for analyzing andvisualizing streaming data Real-time analytics is the hottest topic in data analyticstoday. In Real-Time Analytics: Techniques to Analyze andVisualize Streaming Data, expert Byron Ellis teaches dataanalysts technologies to build an effective real-time analyticsplatform. This platform can then be used to make sense of theconstantly changing data that is beginning to outpace traditionalbatch-based analysis platforms. The author is among a very few leading experts in the field. Hehas a prestigious background in research, development, analytics,real-time visualization, and Big Data streaming and is uniquelyqualified to help you explore this revolutionary field. Moving froma description of the overall analytic architecture of real-timeanalytics to using specific tools to obtain targeted results,Real-Time Analytics leverages open source and moderncommercial tools to construct robust, efficient systems that canprovide real-time analysis in a cost-effective manner. The bookincludes: A deep discussion of streaming data systems andarchitectures Instructions for analyzing, storing, and delivering streamingdata Tips on aggregating data and working with sets Information on data warehousing options and techniques Real-Time Analytics includes in-depth case studies forwebsite analytics, Big Data, visualizing streaming and mobile data,and mining and visualizing operational data flows. The book's"recipe" layout lets readers quickly learn and implement differenttechniques. All of the code examples presented in the book, alongwith their related data sets, are available on the companionwebsite.

Expert Data Visualization

Author: Jos Dirksen

Publisher: Packt Publishing Ltd

ISBN: 1786466627

Category: Computers

Page: 394

View: 4310


Breathe life into your data by learning how to use D3.js V4 to visualize information About This Book Create complex visualizations powered by D3.js and open data. Provides an extensive set of visualizations that explore all the functionality provided by D3.js V4. Shows how to set up an easy–to-use environment to create stunning visualizations. Who This Book Is For The typical target audience of this book is JavaScript developers, designers, and visual artists who have some basic JavaScript programming knowledge and who now want to master pro-level techniques to create interactive data visualizations using web standards which work on desktop as well as mobile devices. What You Will Learn Learn how D3.js works to declaratively define visualizations. Create charts from scratch by using SVG and the D3.js APIs See how to prepare data for easy visualization using D3.js. Visualize hierarchical data using chart types provided by D3.js Explore the different options provided by D3.js to visualize linked data such as graphs. Spice up your visualizations by adding interactivity and animations. Learn how to use D3.js to visualize and interact with Geo- and Gis-related information sources. Create visualization by streaming data over WebSockets In Detail Do you want to make sense of your data? Do you want to create interactive charts, data trees, info-graphics, geospatial charts, and maps efficiently? This book is your ideal choice to master interactive data visualization with D3.js V4. The book includes a number of extensive examples that to help you hone your skills with data visualization. Throughout nine chapters these examples will help you acquire a clear practical understanding of the various techniques, tools and functionality provided by D3.js. You will first setup your D3.JS development environment and learn the basic patterns needed to visualize your data. After that you will learn techniques to optimize different processes such as working with selections; animating data transitions; creating graps and charts, integrating external resources (static as well as streaming); visualizing information on maps; working with colors and scales; utilizing the different D3.js APIs; and much more. The book will also guide you through creating custom graphs and visualizations, and show you how to go from the raw data to beautiful visualizations. The extensive examples will include working with complex and realtime data streams, such as seismic data, geospatial data, scientific data, and more. Towards the end of the book, you will learn to add more functionality on top of D3.js by using it with other external libraries and integrating it with Ecmascript 6 and Typescript Style and approach This book will have a real–world, case-study approach, where you will be given data sets from different domains. These data sets will have different visualization goals; some might need 2D or 3D charts, some might need automated workflows, others might require interactive maps. While you fulfill these goals, you will learn different techniques and best practices, which will enable you to perform data visualization tasks on your own

The Visual Imperative

Creating a Visual Culture of Data Discovery

Author: Lindy Ryan

Publisher: Morgan Kaufmann

ISBN: 0128039302

Category: Computers

Page: 320

View: 7122


Data is powerful. It separates leaders from laggards and it drives business disruption, transformation, and reinvention. Today’s most progressive companies are using the power of data to propel their industries into new areas of innovation, specialization, and optimization. The horsepower of new tools and technologies have provided more opportunities than ever to harness, integrate, and interact with massive amounts of disparate data for business insights and value – something that will only continue in the era of the Internet of Things. And, as a new breed of tech-savvy and digitally native knowledge workers rise to the ranks of data scientist and visual analyst, the needs and demands of the people working with data are changing, too. The world of data is changing fast. And, it’s becoming more visual. Visual insights are becoming increasingly dominant in information management, and with the reinvigorated role of data visualization, this imperative is a driving force to creating a visual culture of data discovery. The traditional standards of data visualizations are making way for richer, more robust and more advanced visualizations and new ways of seeing and interacting with data. However, while data visualization is a critical tool to exploring and understanding bigger and more diverse and dynamic data, by understanding and embracing our human hardwiring for visual communication and storytelling and properly incorporating key design principles and evolving best practices, we take the next step forward to transform data visualizations from tools into unique visual information assets. Discusses several years of in-depth industry research and presents vendor tools, approaches, and methodologies in discovery, visualization, and visual analytics Provides practicable and use case-based experience from advisory work with Fortune 100 and 500 companies across multiple verticals Presents the next-generation of visual discovery, data storytelling, and the Five Steps to Data Storytelling with Visualization Explains the Convergence of Visual Analytics and Visual discovery, including how to use tools such as R in statistical and analytic modeling Covers emerging technologies such as streaming visualization in the IOT (Internet of Things) and streaming animation

Advances in Visual Computing

6th International Symposium, ISVC 2010, Las Vegas, NV, USA, November 29-December 1, 2010, Proceedings

Author: Richard Boyle,Bahram Parvin,Darko Koracin,Ronald Chung,Hammoud,Muhammad Hussain,Kar-Han Tan,Roger Crawfis,Daniel Thalmann,David Kao,Lisa Avila

Publisher: Springer

ISBN: 3642172741

Category: Computers

Page: 762

View: 3343


It is with great pleasure that we present the proceedings of the 6th Inter- tional, Symposium on Visual Computing (ISVC 2010), which was held in Las Vegas, Nevada. ISVC provides a common umbrella for the four main areas of visual computing including vision, graphics, visualization, and virtual reality. The goal is to provide a forum for researchers, scientists, engineers, and pr- titioners throughout the world to present their latest research ?ndings, ideas, developments, and applications in the broader area of visual computing. This year, the program consisted of 14 oral sessions, one poster session, 7 special tracks, and 6 keynote presentations. The response to the call for papers was very good; we received over 300 submissions for the main symposium from which we accepted 93 papers for oral presentation and 73 papers for poster p- sentation. Special track papers were solicited separately through the Organizing and Program Committees of each track. A total of 44 papers were accepted for oral presentation and 6 papers for poster presentation in the special tracks.

IBM InfoSphere Streams: Accelerating Deployments with Analytic Accelerators

Author: Chuck Ballard,Oliver Brandt,Bharath Devaraju,Daniel Farrell,Kevin Foster,Chris Howard,Peter Nicholls,Ankit Pasricha,Roger Rea,Norbert Schulz,Tetsuya Shimada,John Thorson,Sandra Tucker,Robert Uleman,IBM Redbooks

Publisher: IBM Redbooks

ISBN: 0738439193

Category: Computers

Page: 556

View: 986


This IBM® Redbooks® publication describes visual development, visualization, adapters, analytics, and accelerators for IBM InfoSphere® Streams (V3), a key component of the IBM Big Data platform. Streams was designed to analyze data in motion, and can perform analysis on incredibly high volumes with high velocity, using a wide variety of analytic functions and data types. The Visual Development environment extends Streams Studio with drag-and-drop development, provides round tripping with existing text editors, and is ideal for rapid prototyping. Adapters facilitate getting data in and out of Streams, and V3 supports WebSphere MQ, Apache Hadoop Distributed File System, and IBM InfoSphere DataStage. Significant analytics include the native Streams Processing Language, SPSS Modeler analytics, Complex Event Processing, TimeSeries Toolkit for machine learning and predictive analytics, Geospatial Toolkit for location-based applications, and Annotation Query Language for natural language processing applications. Accelerators for Social Media Analysis and Telecommunications Event Data Analysis sample programs can be modified to build production level applications. Want to learn how to analyze high volumes of streaming data or implement systems requiring high performance across nodes in a cluster? Then this book is for you.

High Performance Visualization

Enabling Extreme-Scale Scientific Insight

Author: E. Wes Bethel,Hank Childs,Charles Hansen

Publisher: CRC Press

ISBN: 1439875723

Category: Computers

Page: 520

View: 7394


Visualization and analysis tools, techniques, and algorithms have undergone a rapid evolution in recent decades to accommodate explosive growth in data size and complexity and to exploit emerging multi- and many-core computational platforms. High Performance Visualization: Enabling Extreme-Scale Scientific Insight focuses on the subset of scientific visualization concerned with algorithm design, implementation, and optimization for use on today’s largest computational platforms. The book collects some of the most seminal work in the field, including algorithms and implementations running at the highest levels of concurrency and used by scientific researchers worldwide. After introducing the fundamental concepts of parallel visualization, the book explores approaches to accelerate visualization and analysis operations on high performance computing platforms. Looking to the future and anticipating changes to computational platforms in the transition from the petascale to exascale regime, it presents the main research challenges and describes several contemporary, high performance visualization implementations. Reflecting major concepts in high performance visualization, this book unifies a large and diverse body of computer science research, development, and practical applications. It describes the state of the art at the intersection of scientific visualization, large data, and high performance computing trends, giving readers the foundation to apply the concepts and carry out future research in this area.

Visual and Spatial Analysis

Advances in Data Mining, Reasoning, and Problem Solving

Author: Boris Kovalerchuk,James Schwing

Publisher: Springer Science & Business Media

ISBN: 1402029586

Category: Computers

Page: 576

View: 9152


Advanced visual analysis and problem solving has been conducted successfully for millennia. The Pythagorean Theorem was proven using visual means more than 2000 years ago. In the 19th century, John Snow stopped a cholera epidemic in London by proposing that a specific water pump be shut down. He discovered that pump by visually correlating data on a city map. The goal of this book is to present the current trends in visual and spatial analysis for data mining, reasoning, problem solving and decision-making. This is the first book to focus on visual decision making and problem solving in general with specific applications in the geospatial domain - combining theory with real-world practice. The book is unique in its integration of modern symbolic and visual approaches to decision making and problem solving. As such, it ties together much of the monograph and textbook literature in these emerging areas. This book contains 21 chapters that have been grouped into five parts: (1) visual problem solving and decision making, (2) visual and heterogeneous reasoning, (3) visual correlation, (4) visual and spatial data mining, and (5) visual and spatial problem solving in geospatial domains. Each chapter ends with a summary and exercises. The book is intended for professionals and graduate students in computer science, applied mathematics, imaging science and Geospatial Information Systems (GIS). In addition to being a state-of-the-art research compilation, this book can be used a text for advanced courses on the subjects such as modeling, computer graphics, visualization, image processing, data mining, GIS, and algorithm analysis.