Download or read book Exploding Data written by Michael Chertoff and published by Atlantic Monthly Press. This book was released on 2018-07-10 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: A former Secretary of Homeland Security examines our outdated laws regarding the protection of personal information, and the pressing need for change. Nothing undermines our freedom more than losing control of information about ourselves. And yet, as daily events underscore, we are ever more vulnerable to cyber-attack. In this bracing book, Michael Chertoff makes clear that our laws and policies surrounding the protection of personal information, written for an earlier time, are long overdue for a complete overhaul. On the one hand, the collection of data—more widespread by business than by government, and impossible to stop—should be facilitated as an ultimate protection for society. On the other, standards under which information can be inspected, analyzed, or used must be significantly tightened. In offering his compelling call for action, Chertoff argues that what is at stake is not so much the simple loss of privacy, which is almost impossible to protect, but of individual autonomy—the ability to make personal choices free of manipulation or coercion. Offering vivid stories over many decades that illuminate the three periods of data gathering we have experienced, Chertoff explains the complex legalities surrounding issues of data collection and dissemination today, and charts a path that balances the needs of government, business, and individuals alike. “Surveys the brave new world of data collection and analysis…The world of data as illuminated here would have scared George Orwell.”―Kirkus Reviews “Chertoff has a unique perspective on data security and its implications for citizen rights as he looks at the history of and changes in privacy laws since the founding of the U.S.”—Booklist

Download or read book Exploding Wires written by William G. Chace and published by Springer. This book was released on 2014-07-08 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is presented primarily to record the papers of the Conference on the Exploding Wire Phenomenon conducted by the Air Force Cambridge Research Center in Boston, Massachusetts, on April 2 and 3, 1959. A second and scarcely less important purpose of this book is to serve as a monograph on exploding wires. Nowhere in any language is there a book, or for that matter a section of a book, on electrical wire explosions. The growing interest in and import ance of the phenomenon was indicated by the very gratifying re sponse to the Confe: rence invitations. We hope this book, reaching an even larger audience, will fill a gap in the literature as well as serve as a record of the Conference. A logical arrangement of the papers was extremely difficult to accomplish. On whatever basis they were classified, most papers could have been equally well placed in more than one category. This difficulty was solved by arranging them in three broad classes. If this book is to serve as a monograph, some gene: ral back ground in the exploding wire phenomenon (EWP) is needed. The Introduction was written to serve this purpose. It is, of course, impossible to thank all those without whose help the Conference and this book would not have been possible.

Download or read book Learning Values Lifelong written by Michael M. Kazanjian and published by BRILL. This book was released on 2022-06-08 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book declares that lifelong learning teaches values and wholeness and rejects inert ideas or fragmentation. Education plays a vital role in reorganizing and revitalizing the abundant facts from the information explosion. Specialization works at cross-purposes with liberal arts education, which discloses a holistic vision of each person’s being.

Download or read book Big Data Imperatives written by Soumendra Mohanty and published by Apress. This book was released on 2013-06-24 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Imperatives, focuses on resolving the key questions on everyone's mind: Which data matters? Do you have enough data volume to justify the usage? How you want to process this amount of data? How long do you really need to keep it active for your analysis, marketing, and BI applications? Big data is emerging from the realm of one-off projects to mainstream business adoption; however, the real value of big data is not in the overwhelming size of it, but more in its effective use. Big Data Imperatives describes the complementary nature of traditional data warehouses and big-data analytics platforms and how they feed each other. This book aims to bring the big data and analytics realms together with a greater focus on architectures that leverage the scale and power of big data and the ability to integrate and apply analytics principles to data which earlier was not accessible. This book can also be used as a handbook for practitioners; helping them on methodology,technical architecture, analytics techniques and best practices. At the same time, this book intends to hold the interest of those new to big data and analytics by giving them a deep insight into the realm of big data.

Download or read book Big Data Analytics written by David Loshin and published by Elsevier. This book was released on 2013-08-23 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics will assist managers in providing an overview of the drivers for introducing big data technology into the organization and for understanding the types of business problems best suited to big data analytics solutions, understanding the value drivers and benefits, strategic planning, developing a pilot, and eventually planning to integrate back into production within the enterprise. - Guides the reader in assessing the opportunities and value proposition - Overview of big data hardware and software architectures - Presents a variety of technologies and how they fit into the big data ecosystem

Download or read book Energy information data base written by United States. Dept. of Energy. Technical Information Center and published by . This book was released on 1979 with total page 868 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data as a Service written by Pushpak Sarkar and published by John Wiley & Sons. This book was released on 2015-07-31 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data as a Service shows how organizations can leverage “data as a service” by providing real-life case studies on the various and innovative architectures and related patterns Comprehensive approach to introducing data as a service in any organization A reusable and flexible SOA based architecture framework Roadmap to introduce ‘big data as a service’ for potential clients Presents a thorough description of each component in the DaaS reference architecture so readers can implement solutions

Download or read book Introduction to Data Platforms written by Anthony David Giordano and published by Fulton Books, Inc.. This book was released on 2022-11-03 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital, cloud, and artificial intelligence (AI) have disrupted how we use data. This disruption has changed the way we need to provision, curate, and publish data for the multiple use cases in today's technology-driven environment. This text will cover how to design, develop, and evolve a data platform for all the uses of enterprise data needed in today's digital organization. This book focuses on explaining what a data platform is, what value it provides, how is it engineered, and how to deploy a data platform and support organization. In this context, Introduction to Data Platforms reviews the current requirements for data in the digital age and quantifies the use cases; discusses the evolution of data over the past twenty years, which is a core driver of the modern data platform; defines what a data platform is and defines the architectural components and layers of a data platform; provides the architectural layers or capabilities of a data platform; reviews cloud- and commercial-software vendors that populate the data-platform space; provides a step-by-step approach to engineering, deploying, supporting, and evolving a data-platform environment; provides a step-by-step approach to migrating legacy data warehouses, data marts, and data lakes/sandboxes to a data platform; and reviews organizational structures for managing data platform environments.

Download or read book Mastering Python Data Visualization written by Kirthi Raman and published by Packt Publishing Ltd. This book was released on 2015-10-27 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generate effective results in a variety of visually appealing charts using the plotting packages in Python About This Book Explore various tools and their strengths while building meaningful representations that can make it easier to understand data Packed with computational methods and algorithms in diverse fields of science Written in an easy-to-follow categorical style, this book discusses some niche techniques that will make your code easier to work with and reuse Who This Book Is For If you are a Python developer who performs data visualization and wants to develop existing knowledge about Python to build analytical results and produce some amazing visual display, then this book is for you. A basic knowledge level and understanding of Python libraries is assumed. What You Will Learn Gather, cleanse, access, and map data to a visual framework Recognize which visualization method is applicable and learn best practices for data visualization Get acquainted with reader-driven narratives and author-driven narratives and the principles of perception Understand why Python is an effective tool to be used for numerical computation much like MATLAB, and explore some interesting data structures that come with it Explore with various visualization choices how Python can be very useful in computation in the field of finance and statistics Get to know why Python is the second choice after Java, and is used frequently in the field of machine learning Compare Python with other visualization approaches using Julia and a JavaScript-based framework such as D3.js Discover how Python can be used in conjunction with NoSQL such as Hive to produce results efficiently in a distributed environment In Detail Python has a handful of open source libraries for numerical computations involving optimization, linear algebra, integration, interpolation, and other special functions using array objects, machine learning, data mining, and plotting. Pandas have a productive environment for data analysis. These libraries have a specific purpose and play an important role in the research into diverse domains including economics, finance, biological sciences, social science, health care, and many more. The variety of tools and approaches available within Python community is stunning, and can bolster and enhance visual story experiences. This book offers practical guidance to help you on the journey to effective data visualization. Commencing with a chapter on the data framework, which explains the transformation of data into information and eventually knowledge, this book subsequently covers the complete visualization process using the most popular Python libraries with working examples. You will learn the usage of Numpy, Scipy, IPython, MatPlotLib, Pandas, Patsy, and Scikit-Learn with a focus on generating results that can be visualized in many different ways. Further chapters are aimed at not only showing advanced techniques such as interactive plotting; numerical, graphical linear, and non-linear regression; clustering and classification, but also in helping you understand the aesthetics and best practices of data visualization. The book concludes with interesting examples such as social networks, directed graph examples in real-life, data structures appropriate for these problems, and network analysis. By the end of this book, you will be able to effectively solve a broad set of data analysis problems. Style and approach The approach of this book is not step by step, but rather categorical. The categories are based on fields such as bioinformatics, statistical and machine learning, financial computation, and linear algebra. This approach is beneficial for the community in many different fields of work and also helps you learn how one approach can make sense across many fields

Download or read book Python Data Analytics and Visualization written by Phuong Vo.T.H and published by Packt Publishing Ltd. This book was released on 2017-03-31 with total page 866 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand, evaluate, and visualize data About This Book Learn basic steps of data analysis and how to use Python and its packages A step-by-step guide to predictive modeling including tips, tricks, and best practices Effectively visualize a broad set of analyzed data and generate effective results Who This Book Is For This book is for Python Developers who are keen to get into data analysis and wish to visualize their analyzed data in a more efficient and insightful manner. What You Will Learn Get acquainted with NumPy and use arrays and array-oriented computing in data analysis Process and analyze data using the time-series capabilities of Pandas Understand the statistical and mathematical concepts behind predictive analytics algorithms Data visualization with Matplotlib Interactive plotting with NumPy, Scipy, and MKL functions Build financial models using Monte-Carlo simulations Create directed graphs and multi-graphs Advanced visualization with D3 In Detail You will start the course with an introduction to the principles of data analysis and supported libraries, along with NumPy basics for statistics and data processing. Next, you will overview the Pandas package and use its powerful features to solve data-processing problems. Moving on, you will get a brief overview of the Matplotlib API .Next, you will learn to manipulate time and data structures, and load and store data in a file or database using Python packages. You will learn how to apply powerful packages in Python to process raw data into pure and helpful data using examples. You will also get a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or building helpful products such as recommendations and predictions using Scikit-learn. After this, you will move on to a data analytics specialization—predictive analytics. Social media and IOT have resulted in an avalanche of data. You will get started with predictive analytics using Python. You will see how to create predictive models from data. You will get balanced information on statistical and mathematical concepts, and implement them in Python using libraries such as Pandas, scikit-learn, and NumPy. You'll learn more about the best predictive modeling algorithms such as Linear Regression, Decision Tree, and Logistic Regression. Finally, you will master best practices in predictive modeling. After this, you will get all the practical guidance you need to help you on the journey to effective data visualization. Starting with a chapter on data frameworks, which explains the transformation of data into information and eventually knowledge, this path subsequently cover the complete visualization process using the most popular Python libraries with working examples This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Getting Started with Python Data Analysis, Phuong Vo.T.H &Martin Czygan Learning Predictive Analytics with Python, Ashish Kumar Mastering Python Data Visualization, Kirthi Raman Style and approach The course acts as a step-by-step guide to get you familiar with data analysis and the libraries supported by Python with the help of real-world examples and datasets. It also helps you gain practical insights into predictive modeling by implementing predictive-analytics algorithms on public datasets with Python. The course offers a wealth of practical guidance to help you on this journey to data visualization

Download or read book Measuring the Data Universe written by Reinhold Stahl and published by Springer. This book was released on 2018-05-16 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: This richly illustrated book provides an easy-to-read introduction to the challenges of organizing and integrating modern data worlds, explaining the contribution of public statistics and the ISO standard SDMX (Statistical Data and Metadata Exchange). As such, it is a must for data experts as well those aspiring to become one. Today, exponentially growing data worlds are increasingly determining our professional and private lives. The rapid increase in the amount of globally available data, fueled by search engines and social networks but also by new technical possibilities such as Big Data, offers great opportunities. But whatever the undertaking – driving the block chain revolution or making smart phones even smarter – success will be determined by how well it is possible to integrate, i.e. to collect, link and evaluate, the required data. One crucial factor in this is the introduction of a cross-domain order system in combination with a standardization of the data structure. Using everyday examples, the authors show how the concepts of statistics provide the basis for the universal and standardized presentation of any kind of information. They also introduce the international statistics standard SDMX, describing the profound changes it has made possible and the related order system for the international statistics community.

Download or read book Illustrated Seismic Processing written by Stephen J. Hill and published by SEG Books. This book was released on 2019 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a foundation for understanding the fascinating field of seismic processing. Written for the non-expert, this two-volume introductory text reveals the limitations and potential pitfalls of seismic data, prepares both seismic interpreters and acquisition specialists for working with seismic processing geophysicists, and much more.

Download or read book Big Data Concepts Methodologies Tools and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2016-04-20 with total page 2523 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. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics.

Download or read book Data Algorithms with Spark written by Mahmoud Parsian and published by "O'Reilly Media, Inc.". This book was released on 2022-04-08 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Apache Spark's speed, ease of use, sophisticated analytics, and multilanguage support makes practical knowledge of this cluster-computing framework a required skill for data engineers and data scientists. With this hands-on guide, anyone looking for an introduction to Spark will learn practical algorithms and examples using PySpark. In each chapter, author Mahmoud Parsian shows you how to solve a data problem with a set of Spark transformations and algorithms. You'll learn how to tackle problems involving ETL, design patterns, machine learning algorithms, data partitioning, and genomics analysis. Each detailed recipe includes PySpark algorithms using the PySpark driver and shell script. With this book, you will: Learn how to select Spark transformations for optimized solutions Explore powerful transformations and reductions including reduceByKey(), combineByKey(), and mapPartitions() Understand data partitioning for optimized queries Build and apply a model using PySpark design patterns Apply motif-finding algorithms to graph data Analyze graph data by using the GraphFrames API Apply PySpark algorithms to clinical and genomics data Learn how to use and apply feature engineering in ML algorithms Understand and use practical and pragmatic data design patterns

Download or read book Data Analytics Principles Tools and Practices written by Gaurav Aroraa and published by BPB Publications. This book was released on 2022-01-24 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Complete Data Analytics Guide for Learners and Professionals. KEY FEATURES ● Learn Big Data, Hadoop Architecture, HBase, Hive and NoSQL Database. ● Dive into Machine Learning, its tools, and applications. ● Coverage of applications of Big Data, Data Analysis, and Business Intelligence. DESCRIPTION These days critical problem solving related to data and data sciences is in demand. Professionals who can solve real data science problems using data science tools are in demand. The book “Data Analytics: Principles, Tools, and Practices” can be considered a handbook or a guide for professionals who want to start their journey in the field of data science. The journey starts with the introduction of DBMS, RDBMS, NoSQL, and DocumentDB. The book introduces the essentials of data science and the modern ecosystem, including the important steps such as data ingestion, data munging, and visualization. The book covers the different types of analysis, different Hadoop ecosystem tools like Apache Spark, Apache Hive, R, MapReduce, and NoSQL Database. It also includes the different machine learning techniques that are useful for data analytics and how to visualize data with different graphs and charts. The book discusses useful tools and approaches for data analytics, supported by concrete code examples. After reading this book, you will be motivated to explore real data analytics and make use of the acquired knowledge on databases, BI/DW, data visualization, Big Data tools, and statistical science. WHAT YOU WILL LEARN ● Familiarize yourself with Apache Spark, Apache Hive, R, MapReduce, and NoSQL Database. ● Learn to manage data warehousing with real time transaction processing. ● Explore various machine learning techniques that apply to data analytics. ● Learn how to visualize data using a variety of graphs and charts using real-world examples from the industry. ● Acquaint yourself with Big Data tools and statistical techniques for machine learning. WHO THIS BOOK IS FOR IT graduates, data engineers and entry-level professionals who have a basic understanding of the tools and techniques but want to learn more about how they fit into a broader context are encouraged to read this book. TABLE OF CONTENTS 1. Database Management System 2. Online Transaction Processing and Data Warehouse 3. Business Intelligence and its deeper dynamics 4. Introduction to Data Visualization 5. Advanced Data Visualization 6. Introduction to Big Data and Hadoop 7. Application of Big Data Real Use Cases 8. Application of Big Data 9. Introduction to Machine Learning 10. Advanced Concepts to Machine Learning 11. Application of Machine Learning

Download or read book Big Data Management And Analytics written by Brij B Gupta and published by World Scientific. This book was released on 2023-12-05 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the proliferation of information, big data management and analysis have become an indispensable part of any system to handle such amounts of data. The amount of data generated by the multitude of interconnected devices increases exponentially, making the storage and processing of these data a real challenge.Big data management and analytics have gained momentum in almost every industry, ranging from finance or healthcare. Big data can reveal key insights if handled and analyzed properly; it has great application potential to improve the working of any industry. This book covers the spectrum aspects of big data; from the preliminary level to specific case studies. It will help readers gain knowledge of the big data landscape.Highlights of the topics covered include description of the Big Data ecosystem; real-world instances of big data issues; how the Vs of Big Data (volume, velocity, variety, veracity, valence, and value) affect data collection, monitoring, storage, analysis, and reporting; structural process to get value out of Big Data and recognize the differences between a standard database management system and a big data management system.Readers will gain insights into choice of data models, data extraction, data integration to solve large data problems, data modelling using machine learning techniques, Spark's scalable machine learning techniques, modeling a big data problem into a graph database and performing scalable analytical operations over the graph and different tools and techniques for processing big data and its applications including in healthcare and finance.

Download or read book Database Design Query Formulation and Administration written by Michael Mannino and published by SAGE Publications. This book was released on 2023-11-30 with total page 1307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Formerly published by Chicago Business Press, now published by Sage Database Design, Query Formulation, and Administration, Eighth Edition, offers a comprehensive understanding of database technology. Author Michael Mannino equips students with the necessary tools to grasp the fundamental concepts of database management, and then guides them in honing their skills to solve both basic and advanced challenges in query formulation, data modeling, and database application development. Features of the Eighth Edition: Unmatched SQL coverage in both breadth and depth Oracle and PostgreSQL coverage Problem-solving guidelines Sample databases and examples Data modeling tools Data warehouse coverage NoSQL coverage Current and cutting-edge topics Comprehensive enough for multiple database courses