Scalable Interactive Visualization
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Scalable Interactive Visualization
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Author : Achim Ebert
language : en
Publisher: MDPI
Release Date : 2018-05-08
Scalable Interactive Visualization written by Achim Ebert and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-08 with Technology & Engineering categories.
This book is a printed edition of the Special Issue "Scalable Interactive Visualization" that was published in Informatics
Interactive Web Based Data Visualization With R Plotly And Shiny
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Author : Carson Sievert
language : en
Publisher: CRC Press
Release Date : 2020-01-30
Interactive Web Based Data Visualization With R Plotly And Shiny written by Carson Sievert and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-30 with Business & Economics categories.
The richly illustrated Interactive Web-Based Data Visualization with R, plotly, and shiny focuses on the process of programming interactive web graphics for multidimensional data analysis. It is written for the data analyst who wants to leverage the capabilities of interactive web graphics without having to learn web programming. Through many R code examples, you will learn how to tap the extensive functionality of these tools to enhance the presentation and exploration of data. By mastering these concepts and tools, you will impress your colleagues with your ability to quickly generate more informative, engaging, and reproducible interactive graphics using free and open source software that you can share over email, export to pdf, and more. Key Features: Convert static ggplot2 graphics to an interactive web-based form Link, animate, and arrange multiple plots in standalone HTML from R Embed, modify, and respond to plotly graphics in a shiny app Learn best practices for visualizing continuous, discrete, and multivariate data Learn numerous ways to visualize geo-spatial data This book makes heavy use of plotly for graphical rendering, but you will also learn about other R packages that support different phases of a data science workflow, such as tidyr, dplyr, and tidyverse. Along the way, you will gain insight into best practices for visualization of high-dimensional data, statistical graphics, and graphical perception. The printed book is complemented by an interactive website where readers can view movies demonstrating the examples and interact with graphics.
Essential Pyspark For Scalable Data Analytics
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Author : Sreeram Nudurupati
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-10-29
Essential Pyspark For Scalable Data Analytics written by Sreeram Nudurupati and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-29 with Computers categories.
Get started with distributed computing using PySpark, a single unified framework to solve end-to-end data analytics at scale Key FeaturesDiscover how to convert huge amounts of raw data into meaningful and actionable insightsUse Spark's unified analytics engine for end-to-end analytics, from data preparation to predictive analyticsPerform data ingestion, cleansing, and integration for ML, data analytics, and data visualizationBook Description Apache Spark is a unified data analytics engine designed to process huge volumes of data quickly and efficiently. PySpark is Apache Spark's Python language API, which offers Python developers an easy-to-use scalable data analytics framework. Essential PySpark for Scalable Data Analytics starts by exploring the distributed computing paradigm and provides a high-level overview of Apache Spark. You'll begin your analytics journey with the data engineering process, learning how to perform data ingestion, cleansing, and integration at scale. This book helps you build real-time analytics pipelines that help you gain insights faster. You'll then discover methods for building cloud-based data lakes, and explore Delta Lake, which brings reliability to data lakes. The book also covers Data Lakehouse, an emerging paradigm, which combines the structure and performance of a data warehouse with the scalability of cloud-based data lakes. Later, you'll perform scalable data science and machine learning tasks using PySpark, such as data preparation, feature engineering, and model training and productionization. Finally, you'll learn ways to scale out standard Python ML libraries along with a new pandas API on top of PySpark called Koalas. By the end of this PySpark book, you'll be able to harness the power of PySpark to solve business problems. What you will learnUnderstand the role of distributed computing in the world of big dataGain an appreciation for Apache Spark as the de facto go-to for big data processingScale out your data analytics process using Apache SparkBuild data pipelines using data lakes, and perform data visualization with PySpark and Spark SQLLeverage the cloud to build truly scalable and real-time data analytics applicationsExplore the applications of data science and scalable machine learning with PySparkIntegrate your clean and curated data with BI and SQL analysis toolsWho this book is for This book is for practicing data engineers, data scientists, data analysts, and data enthusiasts who are already using data analytics to explore distributed and scalable data analytics. Basic to intermediate knowledge of the disciplines of data engineering, data science, and SQL analytics is expected. General proficiency in using any programming language, especially Python, and working knowledge of performing data analytics using frameworks such as pandas and SQL will help you to get the most out of this book.
Big Data In Action From Algorithms To Scalable Product Solutions 2025 Author 1 Dr Mehraj Ali Usman Ali
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Author : AUTHOR:1-Dr. Mehraj Ali Usman Ali, AUTHOR:2 -Dr. Shakeb Khan
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :
Big Data In Action From Algorithms To Scalable Product Solutions 2025 Author 1 Dr Mehraj Ali Usman Ali written by AUTHOR:1-Dr. Mehraj Ali Usman Ali, AUTHOR:2 -Dr. Shakeb Khan and has been published by YASHITA PRAKASHAN PRIVATE LIMITED this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
PREFACE In an era dominated by technological advancements, the ability to extract meaningful insights from the ever-expanding volume of data has become a competitive advantage for organizations worldwide. Big Data, with its vast scope, provides companies with unprecedented opportunities to understand consumer behavior, optimize operations, and forecast future trends. Yet, despite its potential, raw data alone is insufficient; it needs to be processed, analyzed, and interpreted in a way that yields actionable insights. This is where Predictive Analytics comes into play. Predictive analytics is the practice of using historical data, machine learning algorithms, and statistical models to forecast future outcomes and trends. By leveraging Big Data, predictive analytics allows organizations to anticipate future behaviors, market shifts, and operational needs with remarkable accuracy. This predictive power is transforming industries, from retail and healthcare to finance and manufacturing, by providing businesses with tools to make data-driven decisions rather than relying solely on intuition or past experience. The goal of this book is to explore the intersection of Big Data and Predictive Analytics, providing readers with both theoretical insights and practical approaches to harnessing predictive models in Big Data environments. Throughout the chapters, we will cover the various types of predictive models, including regression analysis, time-series forecasting, decision trees, and neural networks, highlighting how these models can be applied to Big Data to solve real-world challenges. These methodologies are essential for applications ranging from demand forecasting and fraud detection to personalized marketing and healthcare diagnostics. Data preparation plays a pivotal role in predictive analytics, and this book will delve into the critical process of cleaning, transforming, and normalizing Big Data to ensure accurate and reliable predictions. Additionally, we will explore the implementation of machine learning algorithms, such as supervised and unsupervised learning, which form the backbone of many predictive models used in modern business applications. One of the core themes of this book is to demonstrate how predictive analytics is not just a tool for data scientists but a crucial component of decision support systems, helping organizations make informed choices across various departments, including marketing, operations, and finance. The book will also address the challenges that come with predictive analytics, such as data quality, overfitting, and model interpretability, providing solutions to these common obstacles. Through detailed case studies, particularly in the financial, retail, and healthcare sectors, this book highlights the transformative impact of predictive analytics in Big Data. By the end of this book, readers will not only gain an understanding of the core principles of predictive analytics but will also be equipped with the knowledge to apply these techniques in their own organizations to drive meaningful business outcomes. We hope this book serves as both an academic resource and a practical guide, empowering professionals, researchers, and students to fully leverage predictive analytics in the context of Big Data. Authors Dr. Mehraj Ali Usman Ali Dr. Shakeb Khan
Handbook Of Data Visualization
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Author : Chun-houh Chen
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-12-18
Handbook Of Data Visualization written by Chun-houh Chen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-12-18 with Computers categories.
Visualizing the data is an essential part of any data analysis. Modern computing developments have led to big improvements in graphic capabilities and there are many new possibilities for data displays. This book gives an overview of modern data visualization methods, both in theory and practice. It details modern graphical tools such as mosaic plots, parallel coordinate plots, and linked views. Coverage also examines graphical methodology for particular areas of statistics, for example Bayesian analysis, genomic data and cluster analysis, as well software for graphics.
Data Visualization With Javascript
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Author : Stephen A. Thomas
language : en
Publisher: No Starch Press
Release Date : 2015
Data Visualization With Javascript written by Stephen A. Thomas and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Computers categories.
You've got data to communicate. But what kind of visualization do you choose, how do you build it, and how do you ensure that it's up to the demands of the Web? In Data Visualization with JavaScript, you'll learn how to use JavaScript, HTML, and CSS to build the most practical visualizations for your data. Step-by-step examples walk you through creating, integrating, and debugging different types of visualizations and will have you building basic visualizations, like bar, line, and scatter graphs, in no time. Then you'll move on to more advanced topics, including how to: Create tree maps, heat maps, network graphs, word clouds, and timelines Map geographic data, and build sparklines and composite charts Add interactivity and retrieve data with AJAX Manage data in the browser and build data-driven web applications Harness the power of the Flotr2, Flot, Chronoline.js, D3.js, Underscore.js, and Backbone.js libraries If you already know your way around building a web page but aren't quite sure how to build a good visualization, Data Visualization with JavaScript will help you get your feet wet without throwing you into the deep end. Before you know it, you'll be well on your way to creating simple, powerful data visualizations.
Ict Policy Research And Innovation
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Author : Svetlana Klessova
language : en
Publisher: John Wiley & Sons
Release Date : 2020-10-30
Ict Policy Research And Innovation written by Svetlana Klessova and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-30 with Technology & Engineering categories.
A comprehensive discussion of the findings of the PICASSO initiative on ICT policy ICT Policy, Research, and Innovation: Perspectives and Prospects for EU-US Collaboration provides a clearly readable overview of selected information and communication technology (ICT) and policy topics. Rather than deluge the reader with technical details, the distinguished authors provide just enough technical background to make sense of the underlying policy discussions. The book covers policy, research, and innovation topics on technologies as wide-ranging as: Internet of Things Cyber physical systems 5G Big data ICT Policy, Research, and Innovation compares and contrasts the policy approaches taken by the EU and the US in a variety of areas. The potential for future cooperation is outlined as well. Later chapters provide policy perspectives about some major issues affecting EU/US development cooperation, while the book closes with a discussion of how the development of these new technologies is changing our conceptions of fundamental aspects of society.
Ultimate Apache Superset For Data Visualization And Analytics
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Author : Bragadeesh Sundararajan
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2025-04-07
Ultimate Apache Superset For Data Visualization And Analytics written by Bragadeesh Sundararajan and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-07 with Computers categories.
TAGLINE Apache Superset to Master Data Visualization and Build High-Impact BI Solutions KEY FEATURES ● Learn to install, configure, and use Superset to create visualizations and build interactive dashboards. ● Apply your learning to real-world data scenarios and business use cases, ensuring you can immediately apply these skills in your role. ● Customize Superset with custom visualizations, integrate it with modern data pipelines, and learn how to deploy it in production environments. DESCRIPTION Apache Superset is a powerful open-source data visualization and business intelligence platform that enables professionals to create interactive dashboards effortlessly. With its user-friendly interface and broad compatibility with various data sources, Superset helps users uncover insights and make informed, data-driven decisions in real time. Ultimate Apache Superset for Data Visualization and Analytics offers a structured, hands-on approach to mastering Apache Superset. It begins with installation and configuration, guiding you through building your first visualization and dashboard. As you progress, you’ll explore advanced features such as SQL Lab, custom visualizations, and security management. The book also covers optimizing dashboards, integrating Superset with data pipelines, and deploying it in production environments. Each chapter includes practical examples, best practices, and real-world use cases to reinforce learning. By the end, you’ll have the expertise to build high-impact, interactive dashboards and confidently deploy Apache Superset in production. Whether you're a data analyst, engineer, or business professional, this book equips you with the skills to scale and customize Superset for your organization’s needs. Don't get left behind—unlock the full potential of Apache Superset and take your data visualization to the next level! WHAT WILL YOU LEARN ● Set up and configure Apache Superset for data visualization and BI. ● Design interactive dashboards and compelling data visualizations effortlessly. ● Use SQL Lab to query and explore datasets with precision. ● Develop custom visualizations and extend Superset with plugins. ● Implement role-based access control (RBAC) for secure data governance. ● Deploy, scale, and optimize Superset for enterprise-ready BI solutions. WHO IS THIS BOOK FOR? This book is tailored for Data Analysts, Data Engineers, Business Intelligence Specialists, Data Scientists, IT Professionals, and Business Managers looking to harness Apache Superset for data visualization and BI. A basic understanding of SQL and data analytics will help readers get the most out of this guide. TABLE OF CONTENTS 1. Introduction to Apache Superset 2. Installing and Configuring Apache Superset 3. Getting Started with Data Visualization 4. Data Exploration and SQL Lab 5. Custom Visualizations and Plugins 6. Security and Access Control 7. Building and Optimizing Dashboards 8. Integrating Superset into Data Pipelines 9. Exploratory Data Analysis and Hypothesis Testing 10. Scaling and Deploying Superset in Production 11. Superset for Business Reporting 12. Self-Service BI with Superset 13. Emerging Trends and Innovations in Data Visualization Index
Advanced Intelligent Computing Theories And Applications With Aspects Of Theoretical And Methodological Issues
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Author : De-Shuang Huang
language : en
Publisher: Springer
Release Date : 2007-07-31
Advanced Intelligent Computing Theories And Applications With Aspects Of Theoretical And Methodological Issues written by De-Shuang Huang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-07-31 with Computers categories.
This volume, in conjunction with the two volumes CICS 0002 and LNAI 4682, constitutes the refereed proceedings of the Third International Conference on Intelligent Computing held in Qingdao, China, in August 2007. The 139 full papers published here were carefully reviewed and selected from among 2,875 submissions. Collectively, these papers represent some of the most important findings and insights into the field of intelligent computing.
Trends In Interactive Visualization
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Author : Elena Zudilova-Seinstra
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-12-17
Trends In Interactive Visualization written by Elena Zudilova-Seinstra and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-17 with Computers categories.
II Challenges in Data Mapping Part II deals with one of the most challenging tasks in Interactive Visualization, mapping and teasing out information from large complex datasets and generating visual representations. This section consists of four chapters. Binh Pham, Alex Streit, and Ross Brown provide a comprehensive requirement analysis of information uncertainty visualizations. They examine the sources of uncertainty, review aspects of its complexity, introduce typical models of uncertainty, and analyze major issues in visualization of uncertainty, from various user and task perspectives. Alfred Inselberg examines challenges in the multivariate data analysis. He explains how relations among multiple variables can be mapped uniquely into ?-space subsets having geometrical properties and introduces Parallel Coordinates meth- ology for the unambiguous visualization and exploration of a multidimensional geometry and multivariate relations. Christiaan Gribble describes two alternative approaches to interactive particle visualization: one targeting desktop systems equipped with programmable graphics hardware and the other targeting moderately sized multicore systems using pack- based ray tracing. Finally, Christof Rezk Salama reviews state-of-the-art strategies for the assignment of visual parameters in scientific visualization systems. He explains the process of mapping abstract data values into visual based on transfer functions, clarifies the terms of pre- and postclassification, and introduces the state-of-the-art user int- faces for the design of transfer functions.