Big Data Sas Ibm Oracle And Microsoft Tools
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Application Of Big Data Blockchain And Internet Of Things For Education Informatization
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Author : Mian Ahmad Jan
language : en
Publisher: Springer Nature
Release Date : 2021-10-12
Application Of Big Data Blockchain And Internet Of Things For Education Informatization written by Mian Ahmad Jan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-12 with Computers categories.
This two-volume set constitutes the refereed proceedings of the First International Conference International Conference on Application of Big Data, Blockchain, and Internet of Things for Education Informatization. The conference was held in August 2021 and due to COVID-19 pandemic virtually. The 99 revised full papers and 45 short papers have been selected from 503 submissions. The papers describe research fields such as “big data” and “information education”. The aim of the conference is to provide international cooperation and exchange platforms for big data and information education experts, scholars and enterprise developers to share research results, discuss existing problems and challenges, and explore cutting-edge science and technology.
Big Data For Big Decisions
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Author : Krishna Pera
language : en
Publisher: CRC Press
Release Date : 2022-12-30
Big Data For Big Decisions written by Krishna Pera and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-30 with Business & Economics categories.
Building a data-driven organization (DDO) is an enterprise-wide initiative that may consume and lock up resources for the long term. Understandably, any organization considering such an initiative would insist on a roadmap and business case to be prepared and evaluated prior to approval. This book presents a step-by-step methodology in order to create a roadmap and business case, and provides a narration of the constraints and experiences of managers who have attempted the setting up of DDOs. The emphasis is on the big decisions – the key decisions that influence 90% of business outcomes – starting from decision first and reengineering the data to the decisions process-chain and data governance, so as to ensure the right data are available at the right time, every time. Investing in artificial intelligence and data-driven decision making are now being considered a survival necessity for organizations to stay competitive. While every enterprise aspires to become 100% data-driven and every Chief Information Officer (CIO) has a budget, Gartner estimates over 80% of all analytics projects fail to deliver intended value. Most CIOs think a data-driven organization is a distant dream, especially while they are still struggling to explain the value from analytics. They know a few isolated successes, or a one-time leveraging of big data for decision making does not make an organization data-driven. As of now, there is no precise definition for data-driven organization or what qualifies an organization to call itself data-driven. Given the hype in the market for big data, analytics and AI, every CIO has a budget for analytics, but very little clarity on where to begin or how to choose and prioritize the analytics projects. Most end up investing in a visualization platform like Tableau or QlikView, which in essence is an improved version of their BI dashboard that the organization had invested into not too long ago. The most important stakeholders, the decision-makers, are rarely kept in the loop while choosing analytics projects. This book provides a fail-safe methodology for assured success in deriving intended value from investments into analytics. It is a practitioners’ handbook for creating a step-by-step transformational roadmap prioritizing the big data for the big decisions, the 10% of decisions that influence 90% of business outcomes, and delivering material improvements in the quality of decisions, as well as measurable value from analytics investments. The acid test for a data-driven organization is when all the big decisions, especially top-level strategic decisions, are taken based on data and not on the collective gut feeling of the decision makers in the organization.
Strat Gie
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Author : Dr. Anupama Rajesh
language : en
Publisher: Partridge Publishing
Release Date : 2017-07-06
Strat Gie written by Dr. Anupama Rajesh and has been published by Partridge Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-06 with Business & Economics categories.
Business Intelligence and Analytics (BI&A) has been one of the leading technological trends in recent years and is one of the top most priority technology investments. Enterprises require the support of extensive data processing and analytical techniques to bolster their processes. The book comes at an opportune time to provide a holistic overview of BI&A along with its associated concepts, components, infrastructure etc. It also details its applications in various verticals of management such as Marketing, Finance and HR. This book also discusses relevant software such as Excel, SPSS, R and Eviews. STRATGIE can be an invaluable resource for students, instructors, and practitioners alike.
Big Data Bootcamp
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Author : David Feinleib
language : en
Publisher: Apress
Release Date : 2014-09-26
Big Data Bootcamp written by David Feinleib and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-26 with Business & Economics categories.
Investors and technology gurus have called big data one of the most important trends to come along in decades. Big Data Bootcamp explains what big data is and how you can use it in your company to become one of tomorrow’s market leaders. Along the way, it explains the very latest technologies, companies, and advancements. Big data holds the keys to delivering better customer service, offering more attractive products, and unlocking innovation. That’s why, to remain competitive, every organization should become a big data company. It’s also why every manager and technology professional should become knowledgeable about big data and how it is transforming not just their own industries but the global economy. And that knowledge is just what this book delivers. It explains components of big data like Hadoop and NoSQL databases; how big data is compiled, queried, and analyzed; how to create a big data application; and the business sectors ripe for big data-inspired products and services like retail, healthcare, finance, and education. Best of all, your guide is David Feinleib, renowned entrepreneur, venture capitalist, and author of Why Startups Fail. Feinleib’s Big Data Landscape, a market map featured and explained in the book, is an industry benchmark that has been viewed more than 150,000 times and is used as a reference by VMWare, Dell, Intel, the U.S. Government Accountability Office, and many other organizations. Feinleib also explains: • Why every businessperson needs to understand the fundamentals of big data or get run over by those who do • How big data differs from traditional database management systems • How to create and run a big data project • The technical details powering the big data revolution Whether you’re a Fortune 500 executive or the proprietor of a restaurant or web design studio, Big Data Bootcamp will explain how you can take full advantage of new technologies to transform your company and your career.
Digital Geography
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Author : Radomir Bolgov
language : en
Publisher: Springer Nature
Release Date :
Digital Geography written by Radomir Bolgov and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Hadoop Integration In Ibm Microsoft And Sas
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Author : James Braselton
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2014-08-06
Hadoop Integration In Ibm Microsoft And Sas written by James Braselton and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-06 with Apache Hadoop categories.
There are mountains of untapped potential in our information. Until now, it's been too cost prohibitive to analyze these massive volumes. Of course, there's also been a staggering opportunity cost associated with not tapping into this information, as the potential of this yet-to-be-analyzed information is near-limitless. And we're not just talking the ubiquitous "competitive differentiation" marketing slogan here; we're talking innovation, discovery, association, and pretty much any- thing else that could make the way you work tomorrow very different, with even more tangible results and insight, from the way you work today. People and organizations have attempted to tackle this problem from many different angles. Of course, the angle that is currently leading the pack in terms of popularity for massive data analysis is an open source project called Hadoop. Hadoop is shipped as part of IBM tools, SQL Server 2014 and SAS applications. Hadoop is shipped as part of the IBM InfoSphere BigInsights (BigInsights) platform. Quite simply, BigInsights embraces, hardens, and extends the Hadoop open source framework with enterprise-grade security, governance, availability, integration into existing data stores, tooling that simplifies and improves developer productivity, scalability, analytic toolkits, and more. BigInsights is (and will always be) based on the nonforked core Hadoop distribution, and backwards compatibility. Hadoop is also shipped as part of SAS tools. SAS incorporated Hadoop into their applications (SAS Base, SAS Data Integration, Sas Enterpris Guide and SAS Enterprise Miner). Same SAS aplications works in-memory on Hadoop (In-memory Statistics, SAS Visual Analytics and SAS Visual Statistics). Finaly, Hadoop is also shipped as part of Microsoft SQL Server 2014 and HDInsight. SQL Server 2014 works in-memory across Hadoop. HDInsight is a Hadoop-based platform that you can use to process data of all kinds in the cloud. In particular, HDInsight is useful for processing high volumes of structured and unstructured data, which traditional relational database systems typically cannot support for a variety of reasons. HDInsight allows you to quickly establish an infrastructure for big data analysis, whether you want to develop a proof of concept for a big data solution or support ongoing analytical requirements in a production environment. Furthermore, HDInsight integrates with Microsoft's business-intelligence tools to enable users to enhance big data with additional sources and then explore and analyze the results to gain deeper insights. Most functionality within HDInsight and other Hadoop distributions is similar. Consequently, any current experience with Hadoop is largely transferable. Keep in mind that interaction with HDInsight requires you to use Windows Azure PowerShell commands, so a basic knowledge of PowerShell is required to work with the cluster.
Data Mining For Business Analytics
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Author : Galit Shmueli
language : en
Publisher: John Wiley & Sons
Release Date : 2019-10-14
Data Mining For Business Analytics written by Galit Shmueli and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-14 with Mathematics categories.
Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R
Big Data Processing Using Spark In Cloud
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Author : Mamta Mittal
language : en
Publisher: Springer
Release Date : 2018-06-16
Big Data Processing Using Spark In Cloud written by Mamta Mittal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-16 with Computers categories.
The book describes the emergence of big data technologies and the role of Spark in the entire big data stack. It compares Spark and Hadoop and identifies the shortcomings of Hadoop that have been overcome by Spark. The book mainly focuses on the in-depth architecture of Spark and our understanding of Spark RDDs and how RDD complements big data’s immutable nature, and solves it with lazy evaluation, cacheable and type inference. It also addresses advanced topics in Spark, starting with the basics of Scala and the core Spark framework, and exploring Spark data frames, machine learning using Mllib, graph analytics using Graph X and real-time processing with Apache Kafka, AWS Kenisis, and Azure Event Hub. It then goes on to investigate Spark using PySpark and R. Focusing on the current big data stack, the book examines the interaction with current big data tools, with Spark being the core processing layer for all types of data. The book is intended for data engineers and scientists working on massive datasets and big data technologies in the cloud. In addition to industry professionals, it is helpful for aspiring data processing professionals and students working in big data processing and cloud computing environments.
Hospitality Management And Digital Transformation
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Author : Richard Busulwa
language : en
Publisher: Routledge
Release Date : 2020-12-28
Hospitality Management And Digital Transformation written by Richard Busulwa and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-28 with Business & Economics categories.
Hospitality managers are at a critical inflection point. Digital technology advancements are ramping up guest expectations and introducing nontraditional competitors that are beginning to disrupt the whole industry. The hospitality managers whose organizations are to thrive need to get their organizations into a position where they can effectively leverage digital technologies to simultaneously deliver breakthroughs in efficiency, agility, and guest experience. Hospitality Management and Digital Transformation is a much-needed guidebook to digital disruption and transformation for current and prospective hospitality and leisure managers. The book: • Explains digital technology advancements, how they cause disruption, and the implications of this disruption for hospitality and leisure organizations. • Explains the digital business and digital transformation imperative for hospitality and leisure organizations. • Discusses the different digital capabilities required to effectively compete as a digital business. • Discusses the new and/or enhanced roles hospitality and leisure managers need to play in effecting the different digital capabilities, as well as the competencies required to play these roles. • Discusses how hospitality and leisure managers can keep up with digital technology advancements. • Unpacks more than 36 key digital technology advancements, discussing what they are, how they work, and how they can be implemented across the hospitality and leisure industry. This book will be useful for advanced undergraduate and postgraduate students studying strategic management, IT, information systems, or digital business–related courses as part of degrees in hospitality and leisure management; as well as practitioners studying for professional qualifications.
Future Trends Of Hpc In A Disruptive Scenario
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Author : L. Grandinetti
language : en
Publisher: IOS Press
Release Date : 2019-09-27
Future Trends Of Hpc In A Disruptive Scenario written by L. Grandinetti and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-27 with Computers categories.
The realization that the use of components off the shelf (COTS) could reduce costs sparked the evolution of the massive parallel computing systems available today. The main problem with such systems is the development of suitable operating systems, algorithms and application software that can utilise the potential processing power of large numbers of processors. As a result, systems comprising millions of processors are still limited in the applications they can efficiently solve. Two alternative paradigms that may offer a solution to this problem are Quantum Computers (QC) and Brain Inspired Computers (BIC). This book presents papers from the 14th edition of the biennial international conference on High Performance Computing - From Clouds and Big Data to Exascale and Beyond, held in Cetraro, Italy, from 2 - 6 July 2018. It is divided into 4 sections covering data science, quantum computing, high-performance computing, and applications. The papers presented during the workshop covered a wide spectrum of topics on new developments in the rapidly evolving supercomputing field – including QC and BIC – and a selection of contributions presented at the workshop are included in this volume. In addition, two papers presented at a workshop on Brain Inspired Computing in 2017 and an overview of work related to data science executed by a number of universities in the USA, parts of which were presented at the 2018 and previous workshops, are also included. The book will be of interest to all those whose work involves high-performance computing.