Big Data And Visual Analytics
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Big Data And Visual Analytics
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Author : Sang C. Suh
language : en
Publisher: Springer
Release Date : 2018-01-15
Big Data And Visual Analytics written by Sang C. Suh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-15 with Computers categories.
This book provides users with cutting edge methods and technologies in the area of big data and visual analytics, as well as an insight to the big data and data analytics research conducted by world-renowned researchers in this field. The authors present comprehensive educational resources on big data and visual analytics covering state-of-the art techniques on data analytics, data and information visualization, and visual analytics. Each chapter covers specific topics related to big data and data analytics as virtual data machine, security of big data, big data applications, high performance computing cluster, and big data implementation techniques. Every chapter includes a description of an unique contribution to the area of big data and visual analytics. This book is a valuable resource for researchers and professionals working in the area of big data, data analytics, and information visualization. Advanced-level students studying computer science will also find this book helpful as a secondary textbook or reference.
Big Data Visualization
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Author : James D. Miller
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-02-28
Big Data Visualization written by James D. Miller 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 2017-02-28 with Computers categories.
Learn effective tools and techniques to separate big data into manageable and logical components for efficient data visualization About This Book This unique guide teaches you how to visualize your cluttered, huge amounts of big data with ease It is rich with ample options and solid use cases for big data visualization, and is a must-have book for your shelf Improve your decision-making by visualizing your big data the right way Who This Book Is For This book is for data analysts or those with a basic knowledge of big data analysis who want to learn big data visualization in order to make their analysis more useful. You need sufficient knowledge of big data platform tools such as Hadoop and also some experience with programming languages such as R. This book will be great for those who are familiar with conventional data visualizations and now want to widen their horizon by exploring big data visualizations. What You Will Learn Understand how basic analytics is affected by big data Deep dive into effective and efficient ways of visualizing big data Get to know various approaches (using various technologies) to address the challenges of visualizing big data Comprehend the concepts and models used to visualize big data Know how to visualize big data in real time and for different use cases Understand how to integrate popular dashboard visualization tools such as Splunk and Tableau Get to know the value and process of integrating visual big data with BI tools such as Tableau Make sense of the visualization options for big data, based upon the best suited visualization techniques for big data In Detail When it comes to big data, regular data visualization tools with basic features become insufficient. This book covers the concepts and models used to visualize big data, with a focus on efficient visualizations. This book works around big data visualizations and the challenges around visualizing big data and address characteristic challenges of visualizing like speed in accessing, understanding/adding context to, improving the quality of the data, displaying results, outliers, and so on. We focus on the most popular libraries to execute the tasks of big data visualization and explore "big data oriented" tools such as Hadoop and Tableau. We will show you how data changes with different variables and for different use cases with step-through topics such as: importing data to something like Hadoop, basic analytics. The choice of visualizations depends on the most suited techniques for big data, and we will show you the various options for big data visualizations based upon industry-proven techniques. You will then learn how to integrate popular visualization tools with graphing databases to see how huge amounts of certain data. Finally, you will find out how to display the integration of visual big data with BI using Cognos BI. Style and approach With the help of insightful real-world use cases, we'll tackle data in the world of big data. The scalability and hugeness of the data makes big data visualizations different from normal data visualizations, and this book addresses all the difficulties encountered by professionals while visualizing their big data.
Big Data Solutions Sas Visual Analytics
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Author : Perez Lopez Cesar Perez Lopez
language : en
Publisher:
Release Date : 2021
Big Data Solutions Sas Visual Analytics written by Perez Lopez Cesar Perez Lopez and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Big Data With Sas Visual Analytics
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Author : Cesar Lopez Perez
language : en
Publisher: CreateSpace
Release Date : 2014-01
Big Data With Sas Visual Analytics written by Cesar Lopez Perez and has been published by CreateSpace this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01 with Computers categories.
Is known as Big Data the treatment and analysis of large amounts of data, whose size makes it impossible to treat them with databases and conventional analytical tools. The proliferation of web pages, applications, image and video, social networks, mobile devices, apps, sensors and other modern devices capable of generating huge amounts of data have necessitated the development of Big Data Tools for analysis. We talk about an absolutely relevant environment for many aspects, from the analysis of phenomena, such as climate or seismographic data, to environments such as health, safety, or, of course, the business field. As for Big Data Tools, there is a growing development. Oracle uses Exadata for these purposes, SAS uses Visual Analytics and open-source Hadoop, a framework that is highly popular in this field that enables applications to work with huge repositories of data and thousands of nodes, inspired by Google tools like MapReduce and Google File System, or NoSQL, non-relational database systems needed to hold and process the enormous complexity of all data generated highlights, and in many cases do not follow the logic of the ACID (atomicity, consistency, isolation, durability) guarantees characteristic of conventional databases. This book delves into the treatment of the techniques of BIG DATA with SAS VISUAL ANALYTICS application
A Closer Look At Big Data Analytics
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Author : R. Anandan
language : en
Publisher: Nova Science Publishers
Release Date : 2021
A Closer Look At Big Data Analytics written by R. Anandan and has been published by Nova Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Computers categories.
"Big Data Analytics is a field that dissects, efficiently extricates data from, or in any case manages informational indexes that are excessively huge or complex to be managed by customary information preparing application programming. Information with numerous cases (lines) offers more noteworthy factual force, while information with higher multifaceted nature may prompt a higher bogus disclosure rate. Enormous information challenges incorporate catching information, information stockpiling, information investigation, search, sharing, move, representation, and questioning, refreshing, data security and data source. Large information was initially connected with three key ideas: volume, variety and velocity. Consequently, huge information regularly incorporates information with sizes that surpass the limit of conventional programming to measure inside a satisfactory time and worth. Current utilization of the term enormous information will in general allude to the utilization of predictive analytics, user behavior analytics, or certain other progressed information investigation techniques that concentrate an incentive from information, and sometimes to a specific size of informational index. There is little uncertainty that the amounts of information now accessible are undoubtedly enormous, however that is not the most important quality of this new information biological system. Investigation of informational indexes can discover new relationships to spot business patterns or models. Researchers, business persons, clinical specialists, promoting and governments consistently meet challenges with huge informational collections in territories including Internet look, fintech, metropolitan informatics, and business informatics. Researchers experience constraints in e-Science work, including meteorology, genomics, connectomics, complex material science reproductions, science and ecological exploration. The main objective of this book is to write about issues, challenges, opportunities, and solutions in novel research projects about big data in various domains. The topics of interest include, but are not limited to: efficient storage, management and sharing large scale of data; novel approaches for analyzing data using big data technologies; implementation of high performance and/or scalable and/or real-time computation algorithms for analyzing big data; usage of various data sources like historical data, social networking media, machine data and crowd-sourcing data; using machine learning, visual analytics, data mining, spatio-temporal data analysis and statistical inference in different domains (with large scale datasets); Legal and ethical issues and solutions for using, sharing and publishing large datasets; and the results of data analytics, security and privacy issues"--
Visual Analytics For Data Scientists
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Author : Natalia Andrienko
language : en
Publisher: Springer Nature
Release Date : 2020-08-30
Visual Analytics For Data Scientists written by Natalia Andrienko and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-30 with Computers categories.
This textbook presents the main principles of visual analytics and describes techniques and approaches that have proven their utility and can be readily reproduced. Special emphasis is placed on various instructive examples of analyses, in which the need for and the use of visualisations are explained in detail. The book begins by introducing the main ideas and concepts of visual analytics and explaining why it should be considered an essential part of data science methodology and practices. It then describes the general principles underlying the visual analytics approaches, including those on appropriate visual representation, the use of interactive techniques, and classes of computational methods. It continues with discussing how to use visualisations for getting aware of data properties that need to be taken into account and for detecting possible data quality issues that may impair the analysis. The second part of the book describes visual analytics methods and workflows, organised by various data types including multidimensional data, data with spatial and temporal components, data describing binary relationships, texts, images and video. For each data type, the specific properties and issues are explained, the relevant analysis tasks are discussed, and appropriate methods and procedures are introduced. The focus here is not on the micro-level details of how the methods work, but on how the methods can be used and how they can be applied to data. The limitations of the methods are also discussed and possible pitfalls are identified. The textbook is intended for students in data science and, more generally, anyone doing or planning to do practical data analysis. It includes numerous examples demonstrating how visual analytics techniques are used and how they can help analysts to understand the properties of data, gain insights into the subject reflected in the data, and build good models that can be trusted. Based on several years of teaching related courses at the City, University of London, the University of Bonn and TU Munich, as well as industry training at the Fraunhofer Institute IAIS and numerous summer schools, the main content is complemented by sample datasets and detailed, illustrated descriptions of exercises to practice applying visual analytics methods and workflows.
2015 Big Data Visual Analytics Bdva
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Author : Ulrich Engelke
language : en
Publisher:
Release Date : 2015
2015 Big Data Visual Analytics Bdva written by Ulrich Engelke and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Big Data Analytics For Time Critical Mobility Forecasting
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Author : George A. Vouros
language : en
Publisher: Springer Nature
Release Date : 2020-06-23
Big Data Analytics For Time Critical Mobility Forecasting written by George A. Vouros and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-23 with Computers categories.
This book provides detailed descriptions of big data solutions for activity detection and forecasting of very large numbers of moving entities spread across large geographical areas. It presents state-of-the-art methods for processing, managing, detecting and predicting trajectories and important events related to moving entities, together with advanced visual analytics methods, over multiple heterogeneous, voluminous, fluctuating and noisy data streams from moving entities, correlating them with data from archived data sources expressing e.g. entities’ characteristics, geographical information, mobility patterns, mobility regulations and intentional data. The book is divided into six parts: Part I discusses the motivation and background of mobility forecasting supported by trajectory-oriented analytics, and includes specific problems and challenges in the aviation (air-traffic management) and the maritime domains. Part II focuses on big data quality assessment and processing, and presents novel technologies suitable for mobility analytics components. Next, Part III describes solutions toward processing and managing big spatio-temporal data, particularly enriching data streams and integrating streamed and archival data to provide coherent views of mobility, and storing of integrated mobility data in large distributed knowledge graphs for efficient query-answering. Part IV focuses on mobility analytics methods exploiting (online) processed, synopsized and enriched data streams as well as (offline) integrated, archived mobility data, and highlights future location and trajectory prediction methods, distinguishing between short-term and more challenging long-term predictions. Part V examines how methods addressing data management, data processing and mobility analytics are integrated in big data architectures with distinctive characteristics compared to other known big data paradigmatic architectures. Lastly, Part VI covers important ethical issues that research on mobility analytics should address. Providing novel approaches and methodologies related to mobility detection and forecasting needs based on big data exploration, processing, storage, and analysis, this book will appeal to computer scientists and stakeholders in various application domains.
Insightful Data Visualization With Sas Viya
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Author : Falko Schulz
language : en
Publisher: SAS Institute
Release Date : 2020-10-26
Insightful Data Visualization With Sas Viya written by Falko Schulz and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-26 with Computers categories.
Elevate your storytelling with SAS Visual Analytics Data visualization is the gateway to artificial intelligence (AI) and big data. Insightful Data Visualization with SAS Viya shows how the latest SAS Viya tools can be used to create data visualizations in an easier, smarter, and more engaging way than ever before. SAS Visual Analytics combined with human creativity can produce endless possibilities. In this book, you will learn tips and techniques for getting the most from your SAS Visual Analytics investment. From beginners to advanced SAS users, this book has something for everyone. Use AI wizards to create data visualization automatically, learn to use advanced analytics in your dashboards to surface smarter insights, and learn to extend SAS Visual Analytics with advanced integrations and options. Topics covered in this book include: SAS Visual Analytics Data visualization with SAS Reports and dashboards SAS code examples Self-service analytics SAS data access Extending SAS beyond drag and drop
Big Data On Real World Applications
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Author : Sebastian Ventura Soto
language : en
Publisher: BoD – Books on Demand
Release Date : 2016-07-20
Big Data On Real World Applications written by Sebastian Ventura Soto and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-20 with Computers categories.
As technology advances, high volumes of valuable data are generated day by day in modern organizations. The management of such huge volumes of data has become a priority in these organizations, requiring new techniques for data management and data analysis in Big Data environments. These environments encompass many different fields including medicine, education data, and recommender systems. The aim of this book is to provide the reader with a variety of fields and systems where the analysis and management of Big Data are essential. This book describes the importance of the Big Data era and how existing information systems are required to be adapted to face up the problems derived from the management of massive datasets.