Author: Kim H. Pries Publisher: CRC Press ISBN: 1482234521 Category : Computers Languages : en Pages : 576
Book Description
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 dif
Author: Venkatesh Gauri Shankar Publisher: Walnut Publication ISBN: 9781954399679 Category : Languages : en Pages :
Book Description
The book is organized in such a way that it covers the practical approaches and syllabus of Big Data Analytics prescribed by different universities and colleges for B.Tech./BE (Data Science), M.Tech./ME (Data Science), MSc. (Big Data Analytics), B.Tech (CSE), B.Tech (IT) and all other branches related to Big Data, ML and AI. This book offers a deep understanding of the essential practical concept of Big Data Analytics, including Hadoop, Spark and Tableau. This book is primarily designed to introduce some of the fundamental concepts with practical approaches of Big Data Analytics for undergraduate and postgraduate students in Data Science, CSE, and IT. The concepts in each chapter are explained coherently and unequivocally. Hence it enables the students to gain knowledge in the practical field of Big Data concepts with ease.
Author: Raymond N. Johnson Publisher: John Wiley & Sons ISBN: 1119401747 Category : Business & Economics Languages : en Pages : 738
Book Description
The explosion of data analytics in the auditing profession demands a different kind of auditor. Auditing: A Practical Approach with Data Analytics prepares students for the rapidly changing demands of the auditing profession by meeting the data-driven requirements of today's workforce. Because no two audits are alike, this course uses a practical, case-based approach to help students develop professional judgement, think critically about the auditing process, and develop the decision-making skills necessary to perform a real-world audit. To further prepare students for the profession, this course integrates seamless exam review for successful completion of the CPA Exam.
Author: Nataraj Dasgupta Publisher: Packt Publishing Ltd ISBN: 1783554401 Category : Computers Languages : en Pages : 402
Book Description
Get command of your organizational Big Data using the power of data science and analytics Key Features A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Book Description Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. What you will learn - Get a 360-degree view into the world of Big Data, data science and machine learning - Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives - Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R - Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions - Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications - Understand corporate strategies for successful Big Data and data science projects - Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies Who this book is for The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience.
Author: Umesh R Hodeghatta Publisher: Apress ISBN: 1484225147 Category : Computers Languages : en Pages : 291
Book Description
Learn the fundamental aspects of the business statistics, data mining, and machine learning techniques required to understand the huge amount of data generated by your organization. This book explains practical business analytics through examples, covers the steps involved in using it correctly, and shows you the context in which a particular technique does not make sense. Further, Practical Business Analytics using R helps you understand specific issues faced by organizations and how the solutions to these issues can be facilitated by business analytics. This book will discuss and explore the following through examples and case studies: An introduction to R: data management and R functions The architecture, framework, and life cycle of a business analytics project Descriptive analytics using R: descriptive statistics and data cleaning Data mining: classification, association rules, and clustering Predictive analytics: simple regression, multiple regression, and logistic regression This book includes case studies on important business analytic techniques, such as classification, association, clustering, and regression. The R language is the statistical tool used to demonstrate the concepts throughout the book. What You Will Learn • Write R programs to handle data • Build analytical models and draw useful inferences from them • Discover the basic concepts of data mining and machine learning • Carry out predictive modeling • Define a business issue as an analytical problem Who This Book Is For Beginners who want to understand and learn the fundamentals of analytics using R. Students, managers, executives, strategy and planning professionals, software professionals, and BI/DW professionals.
Author: Ian Foster Publisher: CRC Press ISBN: 1498751431 Category : Mathematics Languages : en Pages : 493
Book Description
Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.
Author: Marie Lowman Publisher: John Wiley & Sons ISBN: 1119362822 Category : Business & Economics Languages : en Pages : 224
Book Description
Analytics can make government work better—this book shows you how A Practical Guide to Analytics for Governments provides demonstrations of real-world analytics applications for legislators, policy-makers, and support staff at the federal, state, and local levels. Big data and analytics are transforming industries across the board, and government can reap many of those same benefits by applying analytics to processes and programs already in place. From healthcare delivery and child well-being, to crime and program fraud, analytics can—in fact, already does—transform the way government works. This book shows you how analytics can be implemented in your own milieu: What is the downstream impact of new legislation? How can we make programs more efficient? Is it possible to predict policy outcomes without analytics? How do I get started building analytics into my government organization? The answers are all here, with accessible explanations and useful advice from an expert in the field. Analytics allows you to mine your data to create a holistic picture of your constituents; this model helps you tailor programs, fine-tune legislation, and serve the populace more effectively. This book walks you through analytics as applied to government, and shows you how to reap Big data's benefits at whatever level necessary. Learn how analytics is already transforming government service delivery Delve into the digital healthcare revolution Use analytics to improve education, juvenile justice, and other child-focused areas Apply analytics to transportation, criminal justice, fraud, and much more Legislators and policy makers have plenty of great ideas—but how do they put those ideas into play? Analytics can play a crucial role in getting the job done well. A Practical Guide to Analytics for Governments provides advice, perspective, and real-world guidance for public servants everywhere.
Author: Arshdeep Bahga Publisher: Vpt ISBN: 9780996025546 Category : Computers Languages : en Pages : 544
Book Description
Big data is defined as collections of datasets whose volume, velocity or variety is so large that it is difficult to store, manage, process and analyze the data using traditional databases and data processing tools. We have written this textbook to meet this need at colleges and universities, and also for big data service providers.
Author: Bernard Marr Publisher: John Wiley & Sons ISBN: 1119231396 Category : Business & Economics Languages : en Pages : 320
Book Description
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: Mike Grigsby Publisher: Kogan Page Publishers ISBN: 0749482176 Category : Business & Economics Languages : en Pages : 241
Book Description
Who is most likely to buy and what is the best way to target them? How can businesses improve strategy without identifying the key influencing factors? The second edition of Marketing Analytics enables marketers and business analysts to leverage predictive techniques to measure and improve marketing performance. By exploring real-world marketing challenges, it provides clear, jargon-free explanations on how to apply different analytical models for each purpose. From targeted list creation and data segmentation, to testing campaign effectiveness, pricing structures and forecasting demand, this book offers a welcome handbook on how statistics, consumer analytics and modelling can be put to optimal use. The fully revised second edition of Marketing Analytics includes three new chapters on big data analytics, insights and panel regression, including how to collect, separate and analyze big data. All of the advanced tools and techniques for predictive analytics have been updated, translating models such as tobit analysis for customer lifetime value into everyday use. Whether an experienced practitioner or having no prior knowledge, methodologies are simplified to ensure the more complex aspects of data and analytics are fully accessible for any level of application. Complete with downloadable data sets and test bank resources, this book supplies a concrete foundation to optimize marketing analytics for day-to-day business advantage.
Author: Kim H. Pries
Author: Venkatesh Gauri Shankar
Author: Raymond N. Johnson
Author: Nataraj Dasgupta
Author: Umesh R Hodeghatta
Author: Ian Foster
Author: Marie Lowman
Author: Arshdeep Bahga
Author: Bernard Marr
Author: Mike Grigsby