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Author : Gerardus Blokdyk
Publisher :
ISBN 13 : 9780655106623
Total Pages : 0 pages
Book Rating : 4.1/5 (66 download)
Download or read book Data Analytics Applications A Clear and Concise Reference written by Gerardus Blokdyk and published by . This book was released on with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Gerardus Blokdyk
Publisher : 5starcooks
ISBN 13 : 9780655156628
Total Pages : 140 pages
Book Rating : 4.1/5 (566 download)
Download or read book Data Analytics Applications a Clear and Concise Reference written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2018-02-27 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do we all define Data Analytics Applications in the same way? How do we go about Securing Data Analytics Applications? Are assumptions made in Data Analytics Applications stated explicitly? What would be the goal or target for a Data Analytics Applications's improvement team? Which individuals, teams or departments will be involved in Data Analytics Applications? This best-selling Data Analytics Applications self-assessment will make you the credible Data Analytics Applications domain visionary by revealing just what you need to know to be fluent and ready for any Data Analytics Applications challenge. How do I reduce the effort in the Data Analytics Applications work to be done to get problems solved? How can I ensure that plans of action include every Data Analytics Applications task and that every Data Analytics Applications outcome is in place? How will I save time investigating strategic and tactical options and ensuring Data Analytics Applications opportunity costs are low? How can I deliver tailored Data Analytics Applications advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Data Analytics Applications essentials are covered, from every angle: the Data Analytics Applications self-assessment shows succinctly and clearly that what needs to be clarified to organize the business/project activities and processes so that Data Analytics Applications outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Data Analytics Applications practitioners. Their mastery, combined with the uncommon elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Data Analytics Applications are maximized with professional results. Your purchase includes access details to the Data Analytics Applications self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. Your exclusive instant access details can be found in your book.
Author : Mohiuddin Ahmed
Publisher : CRC Press
ISBN 13 : 9780367570989
Total Pages : 426 pages
Book Rating : 4.5/5 (79 download)
Download or read book Data Analytics written by Mohiuddin Ahmed and published by CRC Press. This book was released on 2020-06-30 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analytics, Data Analytics: Concepts, Techniques, and Applications compiles the latest trends and issues of the emerging technologies, concepts, and applications that are based on data analytics. The book is for students, researchers, and professionals working in the area of data analytics and is not focused on any specific application. Data Analytics: Concepts, Techniques, and Applications includes chapters covering the fundamental concepts, relevant techniques, and interesting applications of data analysis. The chapters are categorized into three groups with a total of 16 chapters, with contributions from authors around the globe. Section I contains six chapters that cover the fundamental concepts of data analytics. These chapters reflect the important knowledge areas, such as machine learning, regression, clustering, information retrieval, and graph analysis. Section II has six chapters that cover the major techniques of data analytics, such as transition from regular database to big data, big graph analysis tools and techniques, and game theoretical approaches for big data analysis. The rest of the chapters in this section cover topics that lead to newer research domains, including project management, Industry 4.0, and dark data. Section III covers the applications of data analytics in different domains, such as education, traffic offenses, sports data visualization, and, last but not the least, two interesting chapters on cybersecurity for big data analytics with specific focus on the health care sector. Data Analytics: Concepts, Techniques, and Applications is for graduate students, researchers, academics, and industry practitioners working in the areas of data science, machine learning, and other related issues. Book jacket.
Author : Suliman Hawamdeh
Publisher : CRC Press
ISBN 13 : 1351807005
Total Pages : 446 pages
Book Rating : 4.3/5 (518 download)
Download or read book Analytics and Knowledge Management written by Suliman Hawamdeh and published by CRC Press. This book was released on 2018-08-06 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics technique. Analytics and Knowledge Management examines the role of analytics in knowledge management and the integration of big data theories, methods, and techniques into an organizational knowledge management framework. Its chapters written by researchers and professionals provide insight into theories, models, techniques, and applications with case studies examining the use of analytics in organizations. The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics techniques. Analytics, on the other hand, is the examination, interpretation, and discovery of meaningful patterns, trends, and knowledge from data and textual information. It provides the basis for knowledge discovery and completes the cycle in which knowledge management and knowledge utilization happen. Organizations should develop knowledge focuses on data quality, application domain, selecting analytics techniques, and on how to take actions based on patterns and insights derived from analytics. Case studies in the book explore how to perform analytics on social networking and user-based data to develop knowledge. One case explores analyze data from Twitter feeds. Another examines the analysis of data obtained through user feedback. One chapter introduces the definitions and processes of social media analytics from different perspectives as well as focuses on techniques and tools used for social media analytics. Data visualization has a critical role in the advancement of modern data analytics, particularly in the field of business intelligence and analytics. It can guide managers in understanding market trends and customer purchasing patterns over time. The book illustrates various data visualization tools that can support answering different types of business questions to improve profits and customer relationships. This insightful reference concludes with a chapter on the critical issue of cybersecurity. It examines the process of collecting and organizing data as well as reviewing various tools for text analysis and data analytics and discusses dealing with collections of large datasets and a great deal of diverse data types from legacy system to social networks platforms.
Author : Mohammed M. Alani
Publisher : Springer
ISBN 13 : 3319764721
Total Pages : 219 pages
Book Rating : 4.3/5 (197 download)
Download or read book Applications of Big Data Analytics written by Mohammed M. Alani and published by Springer. This book was released on 2018-07-23 with total page 219 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.
Author : Gerardus Blokdyk
Publisher : 5starcooks
ISBN 13 : 9780655416746
Total Pages : 288 pages
Book Rating : 4.4/5 (167 download)
Download or read book Data Management for Analytics a Clear and Concise Reference written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2018-09-23 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: What are your most important goals for the strategic Data Management for Analytics objectives? Is Data Management for Analytics currently on schedule according to the plan? What vendors make products that address the Data Management for Analytics needs? Who are the Data Management for Analytics improvement team members, including Management Leads and Coaches? Is the Data Management for Analytics scope manageable? This valuable Data Management for Analytics self-assessment will make you the reliable Data Management for Analytics domain adviser by revealing just what you need to know to be fluent and ready for any Data Management for Analytics challenge. How do I reduce the effort in the Data Management for Analytics work to be done to get problems solved? How can I ensure that plans of action include every Data Management for Analytics task and that every Data Management for Analytics outcome is in place? How will I save time investigating strategic and tactical options and ensuring Data Management for Analytics costs are low? How can I deliver tailored Data Management for Analytics advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Data Management for Analytics essentials are covered, from every angle: the Data Management for Analytics self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Data Management for Analytics outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Data Management for Analytics practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Data Management for Analytics are maximized with professional results. Your purchase includes access details to the Data Management for Analytics self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard, and... - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation ...plus an extra, special, resource that helps you with project managing. INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
Author : Eric Siegel
Publisher : John Wiley & Sons
ISBN 13 : 1119153654
Total Pages : 368 pages
Book Rating : 4.1/5 (191 download)
Download or read book Predictive Analytics written by Eric Siegel and published by John Wiley & Sons. This book was released on 2016-01-12 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Mesmerizing & fascinating..." —The Seattle Post-Intelligencer "The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com Award-winning | Used by over 30 universities | Translated into 9 languages An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive analytics (aka machine learning) unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death — including one health insurance company. How U.S. Bank and Obama for America calculated the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 182 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more. How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more. A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a
Author : Lesley S. J. Farmer
Publisher : ALA Neal-Schuman
ISBN 13 : 9780838914250
Total Pages : 0 pages
Book Rating : 4.9/5 (142 download)
Download or read book Library Improvement through Data Analytics written by Lesley S. J. Farmer and published by ALA Neal-Schuman. This book was released on 2016-05-26 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book's clear, concise coverage will enable readers of every experience level to gain a better understanding of statistics in order to facilitate library improvement.
Author : K. G. Srinivasa
Publisher : Springer
ISBN 13 : 3319778005
Total Pages : 406 pages
Book Rating : 4.3/5 (197 download)
Download or read book Network Data Analytics written by K. G. Srinivasa and published by Springer. This book was released on 2018-04-26 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order to carry out data analytics, we need powerful and flexible computing software. However the software available for data analytics is often proprietary and can be expensive. This book reviews Apache tools, which are open source and easy to use. After providing an overview of the background of data analytics, covering the different types of analysis and the basics of using Hadoop as a tool, it focuses on different Hadoop ecosystem tools, like Apache Flume, Apache Spark, Apache Storm, Apache Hive, R, and Python, which can be used for different types of analysis. It then examines the different machine learning techniques that are useful for data analytics, and how to visualize data with different graphs and charts. Presenting data analytics from a practice-oriented viewpoint, the book discusses useful tools and approaches for data analytics, supported by concrete code examples. The book is a valuable reference resource for graduate students and professionals in related fields, and is also of interest to general readers with an understanding of data analytics.
Author : Kim H. Pries
Publisher : Auerbach Publications
ISBN 13 : 9781482234510
Total Pages : 0 pages
Book Rating : 4.2/5 (345 download)
Download or read book Big Data Analytics written by Kim H. Pries and published by Auerbach Publications. This book was released on 2015-02-05 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With this book, managers and decision makers are given the tools to make more informed decisions about big data purchasing initiatives. Big Data Analytics: A Practical Guide for Managers not only supplies descriptions of common tools, but also surveys the various products and vendors that supply the big data market. Comparing and contrasting the different types of analysis commonly conducted with big data, this accessible reference presents clear-cut explanations of the general workings of big data tools. Instead of spending time on HOW to install specific packages, it focuses on the reasons WHY readers would install a given package. The book provides authoritative guidance on a range of tools, including open source and proprietary systems. It details the strengths and weaknesses of incorporating big data analysis into decision-making and explains how to leverage the strengths while mitigating the weaknesses. Describes the benefits of distributed computing in simple terms Includes substantial vendor/tool material, especially for open source decisions Covers prominent software packages, including Hadoop and Oracle Endeca Examines GIS and machine learning applications Considers privacy and surveillance issues The book further explores basic statistical concepts that, when misapplied, can be the source of errors. Time and again, big data is treated as an oracle that discovers results nobody would have imagined. While big data can serve this valuable function, all too often these results are incorrect, yet are still reported unquestioningly. The probability of having erroneous results increases as a larger number of variables are compared unless preventative measures are taken. The approach taken by the authors is to explain these concepts so managers can ask better questions of their analysts and vendors as to the appropriateness of the methods used to arrive at a conclusion. Because the world of science and medicine has been grappling with similar issues in the publication of studies, the authors draw on their efforts and apply them to big data.
Author : Wes McKinney
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491957611
Total Pages : 553 pages
Book Rating : 4.4/5 (919 download)
Download or read book Python for Data Analysis written by Wes McKinney and published by "O'Reilly Media, Inc.". This book was released on 2017-09-25 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples
Author : Melissa A Hardy
Publisher : SAGE
ISBN 13 : 1446203441
Total Pages : 729 pages
Book Rating : 4.4/5 (462 download)
Download or read book Handbook of Data Analysis written by Melissa A Hardy and published by SAGE. This book was released on 2009-06-17 with total page 729 pages. Available in PDF, EPUB and Kindle. Book excerpt: ′This book provides an excellent reference guide to basic theoretical arguments, practical quantitative techniques and the methodologies that the majority of social science researchers are likely to require for postgraduate study and beyond′ - Environment and Planning ′The book provides researchers with guidance in, and examples of, both quantitative and qualitative modes of analysis, written by leading practitioners in the field. The editors give a persuasive account of the commonalities of purpose that exist across both modes, as well as demonstrating a keen awareness of the different things that each offers the practising researcher′ - Clive Seale, Brunel University ′With the appearance of this handbook, data analysts no longer have to consult dozens of disparate publications to carry out their work. The essential tools for an intelligent telling of the data story are offered here, in thirty chapters written by recognized experts. ′ - Michael Lewis-Beck, F Wendell Miller Distinguished Professor of Political Science, University of Iowa ′This is an excellent guide to current issues in the analysis of social science data. I recommend it to anyone who is looking for authoritative introductions to the state of the art. Each chapter offers a comprehensive review and an extensive bibliography and will be invaluable to researchers wanting to update themselves about modern developments′ - Professor Nigel Gilbert, Pro Vice-Chancellor and Professor of Sociology, University of Surrey This is a book that will rapidly be recognized as the bible for social researchers. It provides a first-class, reliable guide to the basic issues in data analysis, such as the construction of variables, the characterization of distributions and the notions of inference. Scholars and students can turn to it for teaching and applied needs with confidence. The book also seeks to enhance debate in the field by tackling more advanced topics such as models of change, causality, panel models and network analysis. Specialists will find much food for thought in these chapters. A distinctive feature of the book is the breadth of coverage. No other book provides a better one-stop survey of the field of data analysis. In 30 specially commissioned chapters the editors aim to encourage readers to develop an appreciation of the range of analytic options available, so they can choose a research problem and then develop a suitable approach to data analysis.
Author : Subhashish Samaddar
Publisher : CRC Press
ISBN 13 : 1351973401
Total Pages : 218 pages
Book Rating : 4.3/5 (519 download)
Download or read book Data Analytics written by Subhashish Samaddar and published by CRC Press. This book was released on 2019-02-18 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are a manager who receives the results of any data analyst’s work to help with your decision-making, this book is for you. Anyone playing a role in the field of analytics can benefit from this book as well. In the two decades the editors of this book spent teaching and consulting in the field of analytics, they noticed a critical shortcoming in the communication abilities of many analytics professionals. Specifically, analysts have difficulty in articulating in business terms what their analyses showed and what actionable recommendations were made. When analysts made presentations, they tended to lapse into the technicalities of mathematical procedures, rather than focusing on the strategic and tactical impact and meaning of their work. As analytics has become more mainstream and widespread in organizations, this problem has grown more acute. Data Analytics: Effective Methods for Presenting Results tackles this issue. The editors have used their experience as presenters and audience members who have become lost during presentation. Over the years, they experimented with different ways of presenting analytics work to make a more compelling case to top managers. They have discovered tried and true methods for improving presentations, which they share. The book also presents insights from other analysts and managers who share their own experiences. It is truly a collection of experiences and insight from academics and professionals involved with analytics. The book is not a primer on how to draw the most beautiful charts and graphs or about how to perform any specific kind of analysis. Rather, it shares the experiences of professionals in various industries about how they present their analytics results effectively. They tell their stories on how to win over audiences. The book spans multiple functional areas within a business, and in some cases, it discusses how to adapt presentations to the needs of audiences at different levels of management.
Author : Bart Baesens
Publisher : John Wiley & Sons
ISBN 13 : 1118892704
Total Pages : 262 pages
Book Rating : 4.1/5 (188 download)
Download or read book Analytics in a Big Data World written by Bart Baesens and published by John Wiley & Sons. This book was released on 2014-05-19 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: The guide to targeting and leveraging business opportunities using big data & analytics By leveraging big data & analytics, businesses create the potential to better understand, manage, and strategically exploiting the complex dynamics of customer behavior. Analytics in a Big Data World reveals how to tap into the powerful tool of data analytics to create a strategic advantage and identify new business opportunities. Designed to be an accessible resource, this essential book does not include exhaustive coverage of all analytical techniques, instead focusing on analytics techniques that really provide added value in business environments. The book draws on author Bart Baesens' expertise on the topics of big data, analytics and its applications in e.g. credit risk, marketing, and fraud to provide a clear roadmap for organizations that want to use data analytics to their advantage, but need a good starting point. Baesens has conducted extensive research on big data, analytics, customer relationship management, web analytics, fraud detection, and credit risk management, and uses this experience to bring clarity to a complex topic. Includes numerous case studies on risk management, fraud detection, customer relationship management, and web analytics Offers the results of research and the author's personal experience in banking, retail, and government Contains an overview of the visionary ideas and current developments on the strategic use of analytics for business Covers the topic of data analytics in easy-to-understand terms without an undo emphasis on mathematics and the minutiae of statistical analysis For organizations looking to enhance their capabilities via data analytics, this resource is the go-to reference for leveraging data to enhance business capabilities.
Author : Fenio Annansingh
Publisher : Routledge
ISBN 13 : 1000577902
Total Pages : 265 pages
Book Rating : 4.0/5 (5 download)
Download or read book Data Analytics for Business written by Fenio Annansingh and published by Routledge. This book was released on 2022-04-20 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data analytics underpin our modern data-driven economy. This textbook explains the relevance of data analytics at the firm and industry levels, tracing the evolution and key components of the field, and showing how data analytics insights can be leveraged for business results. The first section of the text covers key topics such as data analytics tools, data mining, business intelligence, customer relationship management, and cybersecurity. The chapters then take an industry focus, exploring how data analytics can be used in particular settings to strengthen business decision-making. A range of sectors are examined, including financial services, accounting, marketing, sport, health care, retail, transport, and education. With industry case studies, clear definitions of terminology, and no background knowledge required, this text supports students in gaining a solid understanding of data analytics and its practical applications. PowerPoint slides, a test bank of questions, and an instructor’s manual are also provided as online supplements. This will be a valuable text for undergraduate level courses in data analytics, data mining, business intelligence, and related areas.
Author : Bernard Marr
Publisher : John Wiley & Sons
ISBN 13 : 1119231396
Total Pages : 320 pages
Book Rating : 4.1/5 (192 download)
Download or read book Big Data in Practice written by Bernard Marr and published by John Wiley & Sons. This book was released on 2016-03-22 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: The best-selling author of Big Data is back, this time with a unique and in-depth insight into how specific companies use big data. Big data is on the tip of everyone's tongue. Everyone understands its power and importance, but many fail to grasp the actionable steps and resources required to utilise it effectively. This book fills the knowledge gap by showing how major companies are using big data every day, from an up-close, on-the-ground perspective. From technology, media and retail, to sport teams, government agencies and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety and so much more. Organised for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved and the processes put it place to make it practical, as well as the technical details, challenges and lessons learned from each unique scenario. Learn how predictive analytics helps Amazon, Target, John Deere and Apple understand their customers Discover how big data is behind the success of Walmart, LinkedIn, Microsoft and more Learn how big data is changing medicine, law enforcement, hospitality, fashion, science and banking Develop your own big data strategy by accessing additional reading materials at the end of each chapter
Author : James Warren
Publisher : Simon and Schuster
ISBN 13 : 1638351104
Total Pages : 481 pages
Book Rating : 4.6/5 (383 download)
Download or read book Big Data written by James Warren and published by Simon and Schuster. This book was released on 2015-04-29 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Table of Contents A new paradigm for Big Data PART 1 BATCH LAYER Data model for Big Data Data model for Big Data: Illustration Data storage on the batch layer Data storage on the batch layer: Illustration Batch layer Batch layer: Illustration An example batch layer: Architecture and algorithms An example batch layer: Implementation PART 2 SERVING LAYER Serving layer Serving layer: Illustration PART 3 SPEED LAYER Realtime views Realtime views: Illustration Queuing and stream processing Queuing and stream processing: Illustration Micro-batch stream processing Micro-batch stream processing: Illustration Lambda Architecture in depth
