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Introduction To Data Technologies
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Book Synopsis Introduction to Data Technologies by : Paul Murrell
Download or read book Introduction to Data Technologies written by Paul Murrell and published by CRC Press. This book was released on 2009-02-23 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing key information on how to work with research data, Introduction to Data Technologies presents ideas and techniques for performing critical, behind-the-scenes tasks that take up so much time and effort yet typically receive little attention in formal education. With a focus on computational tools, the book shows readers how to improve thei
Book Synopsis An Introduction to Data by : Francesco Corea
Download or read book An Introduction to Data written by Francesco Corea and published by Springer. This book was released on 2018-11-27 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reflects the author’s years of hands-on experience as an academic and practitioner. It is primarily intended for executives, managers and practitioners who want to redefine the way they think about artificial intelligence (AI) and other exponential technologies. Accordingly the book, which is structured as a collection of largely self-contained articles, includes both general strategic reflections and detailed sector-specific information. More concretely, it shares insights into what it means to work with AI and how to do it more efficiently; what it means to hire a data scientist and what new roles there are in the field; how to use AI in specific industries such as finance or insurance; how AI interacts with other technologies such as blockchain; and, in closing, a review of the use of AI in venture capital, as well as a snapshot of acceleration programs for AI companies.
Book Synopsis Introduction to Data Systems by : Thomas Bressoud
Download or read book Introduction to Data Systems written by Thomas Bressoud and published by Springer Nature. This book was released on 2020-12-04 with total page 828 pages. Available in PDF, EPUB and Kindle. Book excerpt: Encompassing a broad range of forms and sources of data, this textbook introduces data systems through a progressive presentation. Introduction to Data Systems covers data acquisition starting with local files, then progresses to data acquired from relational databases, from REST APIs and through web scraping. It teaches data forms/formats from tidy data to relationally defined sets of tables to hierarchical structure like XML and JSON using data models to convey the structure, operations, and constraints of each data form. The starting point of the book is a foundation in Python programming found in introductory computer science classes or short courses on the language, and so does not require prerequisites of data structures, algorithms, or other courses. This makes the material accessible to students early in their educational career and equips them with understanding and skills that can be applied in computer science, data science/data analytics, and information technology programs as well as for internships and research experiences. This book is accessible to a wide variety of students. By drawing together content normally spread across upper level computer science courses, it offers a single source providing the essentials for data science practitioners. In our increasingly data-centric world, students from all domains will benefit from the “data-aptitude” built by the material in this book.
Book Synopsis A General Introduction to Data Analytics by : João Moreira
Download or read book A General Introduction to Data Analytics written by João Moreira and published by John Wiley & Sons. This book was released on 2018-07-18 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming A General Introduction to Data Analytics is an essential guide to understand and use data analytics. This book is written using easy-to-understand terms and does not require familiarity with statistics or programming. The authors—noted experts in the field—highlight an explanation of the intuition behind the basic data analytics techniques. The text also contains exercises and illustrative examples. Thought to be easily accessible to non-experts, the book provides motivation to the necessity of analyzing data. It explains how to visualize and summarize data, and how to find natural groups and frequent patterns in a dataset. The book also explores predictive tasks, be them classification or regression. Finally, the book discusses popular data analytic applications, like mining the web, information retrieval, social network analysis, working with text, and recommender systems. The learning resources offer: A guide to the reasoning behind data mining techniques A unique illustrative example that extends throughout all the chapters Exercises at the end of each chapter and larger projects at the end of each of the text’s two main parts Together with these learning resources, the book can be used in a 13-week course guide, one chapter per course topic. The book was written in a format that allows the understanding of the main data analytics concepts by non-mathematicians, non-statisticians and non-computer scientists interested in getting an introduction to data science. A General Introduction to Data Analytics is a basic guide to data analytics written in highly accessible terms.
Book Synopsis A Hands-On Introduction to Data Science by : Chirag Shah
Download or read book A Hands-On Introduction to Data Science written by Chirag Shah and published by Cambridge University Press. This book was released on 2020-04-02 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introductory textbook offering a low barrier entry to data science; the hands-on approach will appeal to students from a range of disciplines.
Download or read book Data Science written by John D. Kelleher and published by MIT Press. This book was released on 2018-04-13 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues, and ethical challenges. The goal of data science is to improve decision making through the analysis of data. Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges. It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets. It is closely related to the fields of data mining and machine learning, but broader in scope. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. It considers data infrastructure and the challenges posed by integrating data from multiple sources, introduces the basics of machine learning, and discusses how to link machine learning expertise with real-world problems. The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. Finally, it considers the future impact of data science and offers principles for success in data science projects.
Download or read book Group Privacy written by Linnet Taylor and published by Springer. This book was released on 2016-12-28 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of the book is to present the latest research on the new challenges of data technologies. It will offer an overview of the social, ethical and legal problems posed by group profiling, big data and predictive analysis and of the different approaches and methods that can be used to address them. In doing so, it will help the reader to gain a better grasp of the ethical and legal conundrums posed by group profiling. The volume first maps the current and emerging uses of new data technologies and clarifies the promises and dangers of group profiling in real life situations. It then balances this with an analysis of how far the current legal paradigm grants group rights to privacy and data protection, and discusses possible routes to addressing these problems. Finally, an afterword gathers the conclusions reached by the different authors and discuss future perspectives on regulating new data technologies.
Book Synopsis Data Science for Business by : Foster Provost
Download or read book Data Science for Business written by Foster Provost and published by "O'Reilly Media, Inc.". This book was released on 2013-07-27 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates
Book Synopsis XML and Web Technologies for Data Sciences with R by : Deborah Nolan
Download or read book XML and Web Technologies for Data Sciences with R written by Deborah Nolan and published by . This book was released on 2013-12-31 with total page 688 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Enterprise Big Data Lake by : Alex Gorelik
Download or read book The Enterprise Big Data Lake written by Alex Gorelik and published by "O'Reilly Media, Inc.". This book was released on 2019-02-21 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: The data lake is a daring new approach for harnessing the power of big data technology and providing convenient self-service capabilities. But is it right for your company? This book is based on discussions with practitioners and executives from more than a hundred organizations, ranging from data-driven companies such as Google, LinkedIn, and Facebook, to governments and traditional corporate enterprises. You’ll learn what a data lake is, why enterprises need one, and how to build one successfully with the best practices in this book. Alex Gorelik, CTO and founder of Waterline Data, explains why old systems and processes can no longer support data needs in the enterprise. Then, in a collection of essays about data lake implementation, you’ll examine data lake initiatives, analytic projects, experiences, and best practices from data experts working in various industries. Get a succinct introduction to data warehousing, big data, and data science Learn various paths enterprises take to build a data lake Explore how to build a self-service model and best practices for providing analysts access to the data Use different methods for architecting your data lake Discover ways to implement a data lake from experts in different industries
Book Synopsis Big Data Technologies and Applications by : Borko Furht
Download or read book Big Data Technologies and Applications written by Borko Furht and published by Springer. This book was released on 2016-09-16 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this book is to introduce the basic concepts of big data computing and then to describe the total solution of big data problems using HPCC, an open-source computing platform. The book comprises 15 chapters broken into three parts. The first part, Big Data Technologies, includes introductions to big data concepts and techniques; big data analytics; and visualization and learning techniques. The second part, LexisNexis Risk Solution to Big Data, focuses on specific technologies and techniques developed at LexisNexis to solve critical problems that use big data analytics. It covers the open source High Performance Computing Cluster (HPCC Systems®) platform and its architecture, as well as parallel data languages ECL and KEL, developed to effectively solve big data problems. The third part, Big Data Applications, describes various data intensive applications solved on HPCC Systems. It includes applications such as cyber security, social network analytics including fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification. The book is intended for a wide variety of people including researchers, scientists, programmers, engineers, designers, developers, educators, and students. This book can also be beneficial for business managers, entrepreneurs, and investors.
Book Synopsis Introduction to Data Platforms by : Anthony David Giordano
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.
Book Synopsis Data Just Right by : Michael Manoochehri
Download or read book Data Just Right written by Michael Manoochehri and published by Pearson Education. This book was released on 2014 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Making Big Data Work: Real-World Use Cases and Examples, Practical Code, Detailed Solutions Large-scale data analysis is now vitally important to virtually every business. Mobile and social technologies are generating massive datasets; distributed cloud computing offers the resources to store and analyze them; and professionals have radically new technologies at their command, including NoSQL databases. Until now, however, most books on "Big Data" have been little more than business polemics or product catalogs. Data Just Right is different: It's a completely practical and indispensable guide for every Big Data decision-maker, implementer, and strategist. Michael Manoochehri, a former Google engineer and data hacker, writes for professionals who need practical solutions that can be implemented with limited resources and time. Drawing on his extensive experience, he helps you focus on building applications, rather than infrastructure, because that's where you can derive the most value. Manoochehri shows how to address each of today's key Big Data use cases in a cost-effective way by combining technologies in hybrid solutions. You'll find expert approaches to managing massive datasets, visualizing data, building data pipelines and dashboards, choosing tools for statistical analysis, and more. Throughout, the author demonstrates techniques using many of today's leading data analysis tools, including Hadoop, Hive, Shark, R, Apache Pig, Mahout, and Google BigQuery. Coverage includes Mastering the four guiding principles of Big Data success--and avoiding common pitfalls Emphasizing collaboration and avoiding problems with siloed data Hosting and sharing multi-terabyte datasets efficiently and economically "Building for infinity" to support rapid growth Developing a NoSQL Web app with Redis to collect crowd-sourced data Running distributed queries over massive datasets with Hadoop, Hive, and Shark Building a data dashboard with Google BigQuery Exploring large datasets with advanced visualization Implementing efficient pipelines for transforming immense amounts of data Automating complex processing with Apache Pig and the Cascading Java library Applying machine learning to classify, recommend, and predict incoming information Using R to perform statistical analysis on massive datasets Building highly efficient analytics workflows with Python and Pandas Establishing sensible purchasing strategies: when to build, buy, or outsource Previewing emerging trends and convergences in scalable data technologies and the evolving role of the Data Scientist
Book Synopsis Encyclopedia of Big Data Technologies by : Sherif Sakr
Download or read book Encyclopedia of Big Data Technologies written by Sherif Sakr and published by Springer. This book was released on 2019-03-01 with total page 1820 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Encyclopedia of Big Data Technologies provides researchers, educators, students and industry professionals with a comprehensive authority over the most relevant Big Data Technology concepts. With over 300 articles written by worldwide subject matter experts from both industry and academia, the encyclopedia covers topics such as big data storage systems, NoSQL database, cloud computing, distributed systems, data processing, data management, machine learning and social technologies, data science. Each peer-reviewed, highly structured entry provides the reader with basic terminology, subject overviews, key research results, application examples, future directions, cross references and a bibliography. The entries are expository and tutorial, making this reference a practical resource for students, academics, or professionals. In addition, the distinguished, international editorial board of the encyclopedia consists of well-respected scholars, each developing topics based upon their expertise.
Download or read book Big Data written by Balamurugan Balusamy and published by John Wiley & Sons. This book was released on 2021-03-15 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn Big Data from the ground up with this complete and up-to-date resource from leaders in the field Big Data: Concepts, Technology, and Architecture delivers a comprehensive treatment of Big Data tools, terminology, and technology perfectly suited to a wide range of business professionals, academic researchers, and students. Beginning with a fulsome overview of what we mean when we say, “Big Data,” the book moves on to discuss every stage of the lifecycle of Big Data. You’ll learn about the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining. You’ll also discover how specific technologies like Apache Hadoop, SQOOP, and Flume work. Big Data also covers the central topic of big data visualization with Tableau, and you’ll learn how to create scatter plots, histograms, bar, line, and pie charts with that software. Accessibly organized, Big Data includes illuminating case studies throughout the material, showing you how the included concepts have been applied in real-world settings. Some of those concepts include: The common challenges facing big data technology and technologists, like data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns Relational and non-relational databases, like RDBMS, NoSQL, and NewSQL databases Virtualizing Big Data through encapsulation, partitioning, and isolating, as well as big data server virtualization Apache software, including Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive The Big Data analytics lifecycle, including business case evaluation, data preparation, extraction, transformation, analysis, and visualization Perfect for data scientists, data engineers, and database managers, Big Data also belongs on the bookshelves of business intelligence analysts who are required to make decisions based on large volumes of information. Executives and managers who lead teams responsible for keeping or understanding large datasets will also benefit from this book.
Book Synopsis Introduction to Privacy Enhancing Technologies by : Carlisle Adams
Download or read book Introduction to Privacy Enhancing Technologies written by Carlisle Adams and published by Springer Nature. This book was released on 2021-10-30 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a unique lens through which the myriad of existing Privacy Enhancing Technologies (PETs) can be easily comprehended and appreciated. It answers key privacy-centered questions with clear and detailed explanations. Why is privacy important? How and why is your privacy being eroded and what risks can this pose for you? What are some tools for protecting your privacy in online environments? How can these tools be understood, compared, and evaluated? What steps can you take to gain more control over your personal data? This book addresses the above questions by focusing on three fundamental elements: It introduces a simple classification of PETs that allows their similarities and differences to be highlighted and analyzed; It describes several specific PETs in each class, including both foundational technologies and important recent additions to the field; It explains how to use this classification to determine which privacy goals are actually achievable in a given real-world environment. Once the goals are known, this allows the most appropriate PETs to be selected in order to add the desired privacy protection to the target environment. To illustrate, the book examines the use of PETs in conjunction with various security technologies, with the legal infrastructure, and with communication and computing technologies such as Software Defined Networking (SDN) and Machine Learning (ML). Designed as an introductory textbook on PETs, this book is essential reading for graduate-level students in computer science and related fields, prospective PETs researchers, privacy advocates, and anyone interested in technologies to protect privacy in online environments.
Book Synopsis Internet of Things and Big Data Technologies for Next Generation Healthcare by : Chintan Bhatt
Download or read book Internet of Things and Big Data Technologies for Next Generation Healthcare written by Chintan Bhatt and published by Springer. This book was released on 2017-01-01 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive book focuses on better big-data security for healthcare organizations. Following an extensive introduction to the Internet of Things (IoT) in healthcare including challenging topics and scenarios, it offers an in-depth analysis of medical body area networks with the 5th generation of IoT communication technology along with its nanotechnology. It also describes a novel strategic framework and computationally intelligent model to measure possible security vulnerabilities in the context of e-health. Moreover, the book addresses healthcare systems that handle large volumes of data driven by patients’ records and health/personal information, including big-data-based knowledge management systems to support clinical decisions. Several of the issues faced in storing/processing big data are presented along with the available tools, technologies and algorithms to deal with those problems as well as a case study in healthcare analytics. Addressing trust, privacy, and security issues as well as the IoT and big-data challenges, the book highlights the advances in the field to guide engineers developing different IoT devices and evaluating the performance of different IoT techniques. Additionally, it explores the impact of such technologies on public, private, community, and hybrid scenarios in healthcare. This book offers professionals, scientists and engineers the latest technologies, techniques, and strategies for IoT and big data.
