Download or read book Interactive Visualization of Big Data Leveraging Databases for Scalable Computation written by Leilani Marie Battle and published by . This book was released on 2013 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern database management systems (DBMS) have been designed to efficiently store, manage and perform computations on massive amounts of data. In contrast, many existing visualization systems do not scale seamlessly from small data sets to enormous ones. We have designed a three-tiered visualization system called ScalaR to deal with this issue. ScalaR dynamically performs resolution reduction when the expected result of a DBMS query is too large to be effectively rendered on existing screen real estate. Instead of running the original query, ScalaR inserts aggregation, sampling or filtering operations to reduce the size of the result. This thesis presents the design and implementation of ScalaR, and shows results for two example applications, visualizing earthquake records and satellite imagery data, stored in SciDB as the back-end DBMS.

Download or read book Image Based Visualization written by Christophe Hurter and published by Morgan & Claypool Publishers. This book was released on 2015-12-01 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our society has entered a data-driven era, one in which not only are enormous amounts of data being generated daily but there are also growing expectations placed on the analysis of this data. Some data have become simply too large to be displayed and some have too short a lifespan to be handled properly with classical visualization or analysis methods. In order to address these issues, this book explores the potential solutions where we not only visualize data, but also allow users to be able to interact with it. Therefore, this book will focus on two main topics: large dataset visualization and interaction. Graphic cards and their image processing power can leverage large data visualization but they can also be of great interest to support interaction. Therefore, this book will show how to take advantage of graphic card computation power with techniques called GPGPUs (general-purpose computing on graphics processing units). As specific examples, this book details GPGPU usages to produce fast enough visualization to be interactive with improved brushing techniques, fast animations between different data representations, and view simplifications (i.e. static and dynamic bundling techniques). Since data storage and memory limitation is less and less of an issue, we will also present techniques to reduce computation time by using memory as a new tool to solve computationally challenging problems. We will investigate innovative data processing techniques: while classical algorithms are expressed in data space (e.g. computation on geographic locations), we will express them in graphic space (e.g., raster map like a screen composed of pixels). This consists of two steps: (1) a data representation is built using straightforward visualization techniques; and (2) the resulting image undergoes purely graphical transformations using image processing techniques. This type of technique is called image-based visualization. The goal of this book is to explore new computing techniques using image-based techniques to provide efficient visualizations and user interfaces for the exploration of large datasets. This book concentrates on the areas of information visualization, visual analytics, computer graphics, and human-computer interaction. This book opens up a whole field of study, including the scientific validation of these techniques, their limitations, and their generalizations to different types of datasets.

Download or read book Distributed Computing in Big Data Analytics written by Sourav Mazumder and published by Springer. This book was released on 2017-08-29 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data technologies are used to achieve any type of analytics in a fast and predictable way, thus enabling better human and machine level decision making. Principles of distributed computing are the keys to big data technologies and analytics. The mechanisms related to data storage, data access, data transfer, visualization and predictive modeling using distributed processing in multiple low cost machines are the key considerations that make big data analytics possible within stipulated cost and time practical for consumption by human and machines. However, the current literature available in big data analytics needs a holistic perspective to highlight the relation between big data analytics and distributed processing for ease of understanding and practitioner use. This book fills the literature gap by addressing key aspects of distributed processing in big data analytics. The chapters tackle the essential concepts and patterns of distributed computing widely used in big data analytics. This book discusses also covers the main technologies which support distributed processing. Finally, this book provides insight into applications of big data analytics, highlighting how principles of distributed computing are used in those situations. Practitioners and researchers alike will find this book a valuable tool for their work, helping them to select the appropriate technologies, while understanding the inherent strengths and drawbacks of those technologies.

Download or read book Big Data and Visual Analytics written by Sang C. Suh and published by Springer. This book was released on 2018-01-15 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Big Data for beginners written by Cybellium Ltd and published by Cybellium Ltd. This book was released on 2023-09-26 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the Power of Big Data Analytics in the Modern World Are you ready to dive into the fascinating world of big data analytics? "Big Data for Beginners" is your essential guide to understanding and harnessing the potential of big data in the modern era. Whether you're new to the concept or looking to expand your knowledge, this comprehensive book equips you with the foundational knowledge and tools to navigate the complexities of big data and make informed decisions. Key Features: 1. Introduction to Big Data: Dive deep into the fundamental concepts of big data, from its definition to its significance in today's data-driven landscape. Build a strong foundation that empowers you to navigate the vast world of big data. 2. Understanding Data Sources: Navigate the diverse sources of big data, including structured, semi-structured, and unstructured data. Learn how to gather, process, and manage data from various sources to extract valuable insights. 3. Big Data Technologies: Discover the technologies that power big data analytics. Explore tools like Hadoop, Spark, and NoSQL databases, understanding their role in processing and analyzing massive datasets. 4. Data Storage and Processing: Master the art of storing and processing big data effectively. Learn about distributed file systems, data warehouses, and batch and real-time processing to ensure scalability and efficiency. 5. Data Analysis and Visualization: Uncover strategies for analyzing and visualizing big data. Explore techniques for data exploration, pattern recognition, and creating compelling visual representations that convey insights effectively. 6. Machine Learning and Predictive Analytics: Delve into the world of machine learning and predictive analytics using big data. Learn how to build models that make accurate predictions and informed decisions based on massive datasets. 7. Big Data Security and Privacy: Explore the challenges of securing and preserving privacy in the realm of big data. Learn how to implement encryption, access controls, and anonymization techniques to protect sensitive information. 8. Real-World Applications: Discover the myriad applications of big data across industries. From healthcare to finance, retail to marketing, explore how big data is transforming business operations and decision-making. 9. Challenges and Future Trends: Gain insights into the challenges posed by big data, such as data quality and scalability issues. Explore the future trends and advancements that are shaping the evolution of big data analytics. 10. Ethical Considerations: Delve into the ethical considerations surrounding big data. Learn about responsible data usage, addressing bias, and maintaining transparency in the collection and analysis of data. Who This Book Is For: "Big Data for Beginners" is an indispensable resource for individuals, students, professionals, and enthusiasts who are eager to grasp the fundamentals of big data analytics. Whether you're a beginner curious about the world of data or an experienced professional seeking to enhance your skills, this book will guide you through the intricacies and empower you to harness the potential of big data.

Download or read book Big Data Visualization written by James D. Miller and published by Packt Publishing Ltd. This book was released on 2017-02-28 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Handbook of Research on Big Data Storage and Visualization Techniques written by Segall, Richard S. and published by IGI Global. This book was released on 2018-01-05 with total page 1078 pages. Available in PDF, EPUB and Kindle. Book excerpt: The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject.

Download or read book Scalable Big Data Architecture written by Bahaaldine Azarmi and published by Apress. This book was released on 2015-12-31 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance. Scalable Big Data Architecture covers real-world, concrete industry use cases that leverage complex distributed applications , which involve web applications, RESTful API, and high throughput of large amount of data stored in highly scalable No-SQL data stores such as Couchbase and Elasticsearch. This book demonstrates how data processing can be done at scale from the usage of NoSQL datastores to the combination of Big Data distribution. When the data processing is too complex and involves different processing topology like long running jobs, stream processing, multiple data sources correlation, and machine learning, it’s often necessary to delegate the load to Hadoop or Spark and use the No-SQL to serve processed data in real time. This book shows you how to choose a relevant combination of big data technologies available within the Hadoop ecosystem. It focuses on processing long jobs, architecture, stream data patterns, log analysis, and real time analytics. Every pattern is illustrated with practical examples, which use the different open sourceprojects such as Logstash, Spark, Kafka, and so on. Traditional data infrastructures are built for digesting and rendering data synthesis and analytics from large amount of data. This book helps you to understand why you should consider using machine learning algorithms early on in the project, before being overwhelmed by constraints imposed by dealing with the high throughput of Big data. Scalable Big Data Architecture is for developers, data architects, and data scientists looking for a better understanding of how to choose the most relevant pattern for a Big Data project and which tools to integrate into that pattern.

Download or read book The Visual Organization written by Phil Simon and published by John Wiley & Sons. This book was released on 2014-02-19 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: The era of Big Data as arrived, and most organizations are woefully unprepared. Slowly, many are discovering that stalwarts like Excel spreadsheets, KPIs, standard reports, and even traditional business intelligence tools aren't sufficient. These old standbys can't begin to handle today's increasing streams, volumes, and types of data. Amidst all of the chaos, though, a new type of organization is emerging. In The Visual Organization, award-winning author and technology expert Phil Simon looks at how an increasingly number of organizations are embracing new dataviz tools and, more important, a new mind-set based upon data discovery and exploration. Simon adroitly shows how Amazon, Apple, Facebook, Google, Twitter, and other tech heavyweights use powerful data visualization tools to garner fascinating insights into their businesses. But make no mistake: these companies are hardly alone. Organizations of all types, industries, sizes are representing their data in new and amazing ways. As a result, they are asking better questions and making better business decisions. Rife with real-world examples and case studies, The Visual Organization is a full-color tour-de-force.

Download or read book Interactive Systems for Scalable Visualization and Analysis written by Dominik Moritz and published by . This book was released on 2019 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: While computers can help us manage data, human judgment and domain expertise is what turns it into understanding. Meeting the challenges of increasingly large and complex data requires methods that richly integrate the capabilities of both people and machines. In response to these challenges, this thesis contributes new languages and models for visualization design that power interactive systems for scalable data analysis. In these languages, users can be imprecise about low-level design decisions as the system leverages this ambiguity to optimize the visual design and necessary computation. Vega-Lite is a high-level declarative language for rapidly creating interactive visualizations, while also providing a convenient yet powerful representation for tools that generate visualizations. Vega-Lite uses smart defaults to fill in low-level details to create effective designs. The declarative design facilitates optimization of the required data processing. Draco is a model of visualization design that extends Vega-Lite with shareable design guidelines, formal reasoning over the design space, and visualization recommendation. We show how we can use Draco to construct increasingly sophisticated automated visualization design and recommendation systems, including systems based on weights learned directly from the results of graphical perception experiments. We take a user-centric perspective on systems for scalable exploratory analysis. Considering both the backend and frontend concerns, we present Falcon, an interactive crossfilter application where users can interact with billions of records without latencies that negatively affect their exploration. To scale beyond billions of records, we present Pangloss, a visual analysis system that uses approximate query processing but provides eventual guarantees using Optimistic Visualization. In this concept, we treat approximate query processing as a user experience problem to address users' primary concern: trust in their exploration results. Falcon and Pangloss contribute techniques for scalable interaction and exploration of large data volumes by making principled trade-offs among people's latency tolerance, precomputation, and the level of approximation.

Download or read book Mastering Big Data written by Cybellium Ltd and published by Cybellium Ltd. This book was released on 2023-09-06 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cybellium Ltd is dedicated to empowering individuals and organizations with the knowledge and skills they need to navigate the ever-evolving computer science landscape securely and learn only the latest information available on any subject in the category of computer science including: - Information Technology (IT) - Cyber Security - Information Security - Big Data - Artificial Intelligence (AI) - Engineering - Robotics - Standards and compliance Our mission is to be at the forefront of computer science education, offering a wide and comprehensive range of resources, including books, courses, classes and training programs, tailored to meet the diverse needs of any subject in computer science. Visit https://www.cybellium.com for more books.

Download or read book Advanced Data Analytics with AWS written by Joseph Conley and published by Orange Education Pvt Ltd. This book was released on 2024-04-17 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the Fundamentals of Data Analytics at Scale KEY FEATURES ● Comprehensive guide to constructing data engineering workflows spanning diverse data sources ● Expert techniques for transforming and visualizing data to extract actionable insights ● Advanced methodologies for analyzing data and employing machine learning to uncover intricate patterns DESCRIPTION Embark on a transformative journey into the realm of data analytics with AWS with this practical and incisive handbook. Begin your exploration with an insightful introduction to the fundamentals of data analytics, setting the stage for your AWS adventure. The book then covers collecting data efficiently and effectively on AWS, laying the groundwork for insightful analysis. It will dive deep into processing data, uncovering invaluable techniques to harness the full potential of your datasets. The book will equip you with advanced data analysis skills, unlocking the ability to discern complex patterns and insights. It covers additional use cases for data analysis on AWS, from predictive modeling to sentiment analysis, expanding your analytical horizons. The final section of the book will utilize the power of data virtualization and interaction, revolutionizing the way you engage with and derive value from your data. Gain valuable insights into emerging trends and technologies shaping the future of data analytics, and conclude your journey with actionable next steps, empowering you to continue your data analytics odyssey with confidence. WHAT WILL YOU LEARN ● Construct streamlined data engineering workflows capable of ingesting data from diverse sources and formats. ● Employ data transformation tools to efficiently cleanse and reshape data, priming it for analysis. ● Perform ad-hoc queries for preliminary data exploration, uncovering initial insights. ● Utilize prepared datasets to craft compelling, interactive data visualizations that communicate actionable insights. ● Develop advanced machine learning and Generative AI workflows to delve into intricate aspects of complex datasets, uncovering deeper insights. WHO IS THIS BOOK FOR? This book is ideal for aspiring data engineers, analysts, and data scientists seeking to deepen their understanding and practical skills in data engineering, data transformation, visualization, and advanced analytics. It is also beneficial for professionals and students looking to leverage AWS services for their data-related tasks. TABLE OF CONTENTS 1. Introduction to Data Analytics and AWS 2. Getting Started with AWS 3. Collecting Data with AWS 4. Processing Data on AWS 5. Descriptive Analytics on AWS 6. Advanced Data Analysis on AWS 7. Additional Use Cases for Data Analysis 8. Data Visualization and Interaction on AWS 9. The Future of Data Analytics 10. Conclusion and Next Steps Index

Download or read book Applications of Big Data Analytics written by Mohammed M. Alani and published by Springer. This book was released on 2019-02-09 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This timely text/reference reviews the state of the art of big data analytics, with a particular focus on practical applications. An authoritative selection of leading international researchers present detailed analyses of existing trends for storing and analyzing big data, together with valuable insights into the challenges inherent in current approaches and systems. This is further supported by real-world examples drawn from a broad range of application areas, including healthcare, education, and disaster management. The text also covers, typically from an application-oriented perspective, advances in data science in such areas as big data collection, searching, analysis, and knowledge discovery. Topics and features: Discusses a model for data traffic aggregation in 5G cellular networks, and a novel scheme for resource allocation in 5G networks with network slicing Explores methods that use big data in the assessment of flood risks, and apply neural networks techniques to monitor the safety of nuclear power plants Describes a system which leverages big data analytics and the Internet of Things in the application of drones to aid victims in disaster scenarios Proposes a novel deep learning-based health data analytics application for sleep apnea detection, and a novel pathway for diagnostic models of headache disorders Reviews techniques for educational data mining and learning analytics, and introduces a scalable MapReduce graph partitioning approach for high degree vertices Presents a multivariate and dynamic data representation model for the visualization of healthcare data, and big data analytics methods for software reliability assessment This practically-focused volume is an invaluable resource for all researchers, academics, data scientists and business professionals involved in the planning, designing, and implementation of big data analytics projects. Dr. Mohammed M. Alani is an Associate Professor in Computer Engineering and currently is the Provost at Al Khawarizmi International College, Abu Dhabi, UAE. Dr. Hissam Tawfik is a Professor of Computer Science in the School of Computing, Creative Technologies & Engineering at Leeds Beckett University, UK. Dr. Mohammed Saeed is a Professor in Computing and currently is the Vice President for Academic Affairs and Research at the University of Modern Sciences, Dubai, UAE. Dr. Obinna Anya is a Research Staff Member at IBM Research – Almaden, San Jose, CA, USA.

Download or read book AWS Certified Big Data Specialty BDS C01 written by Cybellium and published by Cybellium. This book was released on with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to the forefront of knowledge with Cybellium, your trusted partner in mastering the cutting-edge fields of IT, Artificial Intelligence, Cyber Security, Business, Economics and Science. Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com

Download or read book Big Data Computing written by Tanvir Habib Sardar and published by CRC Press. This book was released on 2024-02-27 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book primarily aims to provide an in-depth understanding of recent advances in big data computing technologies, methodologies, and applications along with introductory details of big data computing models such as Apache Hadoop, MapReduce, Hive, Pig, Mahout in-memory storage systems, NoSQL databases, and big data streaming services such as Apache Spark, Kafka, and so forth. It also covers developments in big data computing applications such as machine learning, deep learning, graph processing, and many others. Features: Provides comprehensive analysis of advanced aspects of big data challenges and enabling technologies. Explains computing models using real-world examples and dataset-based experiments. Includes case studies, quality diagrams, and demonstrations in each chapter. Describes modifications and optimization of existing technologies along with the novel big data computing models. Explores references to machine learning, deep learning, and graph processing. This book is aimed at graduate students and researchers in high-performance computing, data mining, knowledge discovery, and distributed computing.

Download or read book Behavior driven Optimization Techniques for Scalable Data Exploration written by Leilani Marie Battle and published by . This book was released on 2017 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interactive visualizations are a popular medium used by scientists to explore, analyze and generally make sense of their data. However, with the overwhelming amounts of data that scientists collect from various instruments (e.g., telescopes, satellites, gene sequencers and field sensors), they need ways of efficiently transforming their data into interactive visualizations. Though a variety of visualization tools exist to help people make sense of their data, these tools often rely on database management systems (or DBMSs) for data processing and storage; and unfortunately, DBMSs fail to process the data fast enough to support a fluid, interactive visualization experience. This thesis blends optimization techniques from databases and methodology from HCI and visualization in order to support interactive and iterative exploration of large datasets. Our main goal is to reduce latency in visualization systems, i.e., the time these systems spend responding to a user’s actions. We demonstrate through a comprehensive user study that latency has a clear (negative) effect on users’ high-level analysis strategies, which becomes more pronounced as the latency is increased. Furthermore, we find that users are more susceptible to the effects of system latency when they have existing domain knowledge, a common scenario for data scientists. We then developed a visual exploration system called Sculpin that utilizes a suite of optimizations to reduce system latency. Sculpin learns user exploration patterns automatically, and exploits these patterns to pre-fetch data ahead of users as they explore. We then combine data-prefetching with incremental data processing (i.e., incremental materialization) and visualization-focused caching optimizations to further boost performance. With all three of these techniques (pre-fetching, caching, and pre-computation), Sculpin is able to: create visualizations 380% faster and respond to user interactions 88% faster than existing visualization systems, while also using less than one third of the space required by other systems to store materialized query results.

Download or read book Unlocking Insights A Comprehensive Guide to Big Data Analytics written by Mothiram Rajasekaran and published by Leilani Katie Publication. This book was released on 2024-04-26 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mothiram Rajasekaran, Senior Solution Consultant, Cloudera, USA.