Development Methodologies For Big Data Analytics Systems

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Development Methodologies for Big Data Analytics Systems

Manuel Mora,Fen Wang,Jorge Marx Gomez,Hector Duran-Limon
Development Methodologies for Big Data Analytics Systems Book PDF

Author : Manuel Mora,Fen Wang,Jorge Marx Gomez,Hector Duran-Limon
Publisher : Springer Nature
Page : 289 pages
File Size : 49,9 Mb
Release : 2023-11-03
Category : Technology & Engineering
ISBN : 9783031409561

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Development Methodologies for Big Data Analytics Systems by Manuel Mora,Fen Wang,Jorge Marx Gomez,Hector Duran-Limon Pdf

This book presents research in big data analytics (BDA) for business of all sizes. The authors analyze problems presented in the application of BDA in some businesses through the study of development methodologies based on the three approaches – 1) plan-driven, 2) agile and 3) hybrid lightweight. The authors first describe BDA systems and how they emerged with the convergence of Statistics, Computer Science, and Business Intelligent Analytics with the practical aim to provide concepts, models, methods and tools required for exploiting the wide variety, volume, and velocity of available business internal and external data - i.e. Big Data – and provide decision-making value to decision-makers. The book presents high-quality conceptual and empirical research-oriented chapters on plan-driven, agile, and hybrid lightweight development methodologies and relevant supporting topics for BDA systems suitable to be used for large-, medium-, and small-sized business organizations.

Big Data Analytics: Systems, Algorithms, Applications

C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,Aditya Mogadala,Rohit Ghosh,L.M. Jenila Livingston
Big Data Analytics Systems Algorithms Applications Book PDF

Author : C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,Aditya Mogadala,Rohit Ghosh,L.M. Jenila Livingston
Publisher : Springer Nature
Page : 412 pages
File Size : 43,5 Mb
Release : 2019-10-14
Category : Computers
ISBN : 9789811500947

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Big Data Analytics: Systems, Algorithms, Applications by C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,Aditya Mogadala,Rohit Ghosh,L.M. Jenila Livingston Pdf

This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy. With regard to machine learning techniques, the book presents all the standard algorithms for learning – including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered. In turn, the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition. Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.

Cognitive Computing and Big Data Analytics

Judith S. Hurwitz,Marcia Kaufman,Adrian Bowles
Cognitive Computing and Big Data Analytics Book PDF

Author : Judith S. Hurwitz,Marcia Kaufman,Adrian Bowles
Publisher : John Wiley & Sons
Page : 288 pages
File Size : 40,9 Mb
Release : 2015-02-12
Category : Computers
ISBN : 9781118896631

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Cognitive Computing and Big Data Analytics by Judith S. Hurwitz,Marcia Kaufman,Adrian Bowles Pdf

A comprehensive guide to learning technologies that unlock the value in big data Cognitive Computing provides detailed guidance toward building a new class of systems that learn from experience and derive insights to unlock the value of big data. This book helps technologists understand cognitive computing's underlying technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches based on accumulated evidence, rather than reprogramming. Detailed case examples from the financial, healthcare, and manufacturing walk readers step-by-step through the design and testing of cognitive systems, and expert perspectives from organizations such as Cleveland Clinic, Memorial Sloan-Kettering, as well as commercial vendors that are creating solutions. These organizations provide insight into the real-world implementation of cognitive computing systems. The IBM Watson cognitive computing platform is described in a detailed chapter because of its significance in helping to define this emerging market. In addition, the book includes implementations of emerging projects from Qualcomm, Hitachi, Google and Amazon. Today's cognitive computing solutions build on established concepts from artificial intelligence, natural language processing, ontologies, and leverage advances in big data management and analytics. They foreshadow an intelligent infrastructure that enables a new generation of customer and context-aware smart applications in all industries. Cognitive Computing is a comprehensive guide to the subject, providing both the theoretical and practical guidance technologists need. Discover how cognitive computing evolved from promise to reality Learn the elements that make up a cognitive computing system Understand the groundbreaking hardware and software technologies behind cognitive computing Learn to evaluate your own application portfolio to find the best candidates for pilot projects Leverage cognitive computing capabilities to transform the organization Cognitive systems are rightly being hailed as the new era of computing. Learn how these technologies enable emerging firms to compete with entrenched giants, and forward-thinking established firms to disrupt their industries. Professionals who currently work with big data and analytics will see how cognitive computing builds on their foundation, and creates new opportunities. Cognitive Computing provides complete guidance to this new level of human-machine interaction.

Marketing and Big Data Analytics in Tourism and Events

Hashem, Tareq Nael,Albattat, Ahmad,Valeri, Marco,Sharma, Anukrati
Marketing and Big Data Analytics in Tourism and Events Book PDF

Author : Hashem, Tareq Nael,Albattat, Ahmad,Valeri, Marco,Sharma, Anukrati
Publisher : IGI Global
Page : 313 pages
File Size : 50,7 Mb
Release : 2024-05-06
Category : Business & Economics
ISBN : 9798369333112

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Marketing and Big Data Analytics in Tourism and Events by Hashem, Tareq Nael,Albattat, Ahmad,Valeri, Marco,Sharma, Anukrati Pdf

In the digital age, the tourism industry faces the challenge of effectively marketing destinations amidst a sea of competition and information. Marketing Information Systems (MkIS) and Big Data Analytics (BDA) hold immense potential. Yet, many organizations need help harnessing their power efficiently. Marketing and Big Data Analytics in Tourism and Events offer a comprehensive solution, deep-dive into integrating MkIS and BDA as a strategic approach to revolutionizing tourism marketing. The book aims to bridge the gap between theory and practice by examining the complexities and nuances of MkIS and BDA in promoting tourist destinations. It provides actionable insights and practical strategies for leveraging these technologies effectively. Readers will understand how AI-driven MkIS and BDA can enhance marketing campaigns, improve customer experiences, and drive business growth in the tourism sector.

Social Big Data Analytics

Bilal Abu-Salih,Pornpit Wongthongtham,Dengya Zhu,Kit Yan Chan,Amit Rudra
Social Big Data Analytics Book PDF

Author : Bilal Abu-Salih,Pornpit Wongthongtham,Dengya Zhu,Kit Yan Chan,Amit Rudra
Publisher : Springer Nature
Page : 218 pages
File Size : 42,6 Mb
Release : 2021-03-10
Category : Business & Economics
ISBN : 9789813366527

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Social Big Data Analytics by Bilal Abu-Salih,Pornpit Wongthongtham,Dengya Zhu,Kit Yan Chan,Amit Rudra Pdf

This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising. This book identifies how in such applications, social data offers a plethora of benefits to enhance the decision making process. This book highlights that business intelligence applications are more focused on structured data; however, in order to understand and analyse the social big data, there is a need to aggregate data from various sources and to present it in a plausible format. Big Social Data (BSD) exhibit all the typical properties of big data: wide physical distribution, diversity of formats, non-standard data models, independently-managed and heterogeneous semantics but even further valuable with marketing opportunities. The book provides a review of the current state-of-the-art approaches for big social data analytics as well as to present dissimilar methods to infer value from social data. The book further examines several areas of research that benefits from the propagation of the social data. In particular, the book presents various technical approaches that produce data analytics capable of handling big data features and effective in filtering out unsolicited data and inferring a value. These approaches comprise advanced technical solutions able to capture huge amounts of generated data, scrutinise the collected data to eliminate unwanted data, measure the quality of the inferred data, and transform the amended data for further data analysis. Furthermore, the book presents solutions to derive knowledge and sentiments from BSD and to provide social data classification and prediction. The approaches in this book also incorporate several technologies such as semantic discovery, sentiment analysis, affective computing and machine learning. This book has additional special feature enriched with numerous illustrations such as tables, graphs and charts incorporating advanced visualisation tools in accessible an attractive display.

Designing Big Data Platforms

Yusuf Aytas
Designing Big Data Platforms Book PDF

Author : Yusuf Aytas
Publisher : John Wiley & Sons
Page : 338 pages
File Size : 51,9 Mb
Release : 2021-07-27
Category : Mathematics
ISBN : 9781119690924

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Designing Big Data Platforms by Yusuf Aytas Pdf

DESIGNING BIG DATA PLATFORMS Provides expert guidance and valuable insights on getting the most out of Big Data systems An array of tools are currently available for managing and processing data—some are ready-to-go solutions that can be immediately deployed, while others require complex and time-intensive setups. With such a vast range of options, choosing the right tool to build a solution can be complicated, as can determining which tools work well with each other. Designing Big Data Platforms provides clear and authoritative guidance on the critical decisions necessary for successfully deploying, operating, and maintaining Big Data systems. This highly practical guide helps readers understand how to process large amounts of data with well-known Linux tools and database solutions, use effective techniques to collect and manage data from multiple sources, transform data into meaningful business insights, and much more. Author Yusuf Aytas, a software engineer with a vast amount of big data experience, discusses the design of the ideal Big Data platform: one that meets the needs of data analysts, data engineers, data scientists, software engineers, and a spectrum of other stakeholders across an organization. Detailed yet accessible chapters cover key topics such as stream data processing, data analytics, data science, data discovery, and data security. This real-world manual for Big Data technologies: Provides up-to-date coverage of the tools currently used in Big Data processing and management Offers step-by-step guidance on building a data pipeline, from basic scripting to distributed systems Highlights and explains how data is processed at scale Includes an introduction to the foundation of a modern data platform Designing Big Data Platforms: How to Use, Deploy, and Maintain Big Data Systems is a must-have for all professionals working with Big Data, as well researchers and students in computer science and related fields.

Handbook of Research on Pattern Engineering System Development for Big Data Analytics

Tiwari, Vivek,Thakur, Ramjeevan Singh,Tiwari, Basant,Gupta, Shailendra
Handbook of Research on Pattern Engineering System Development for Big Data Analytics Book PDF

Author : Tiwari, Vivek,Thakur, Ramjeevan Singh,Tiwari, Basant,Gupta, Shailendra
Publisher : IGI Global
Page : 396 pages
File Size : 55,9 Mb
Release : 2018-04-20
Category : Computers
ISBN : 9781522538714

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Handbook of Research on Pattern Engineering System Development for Big Data Analytics by Tiwari, Vivek,Thakur, Ramjeevan Singh,Tiwari, Basant,Gupta, Shailendra Pdf

Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries. It is necessary to develop new techniques for managing data in order to ensure adequate usage. The Handbook of Research on Pattern Engineering System Development for Big Data Analytics is a critical scholarly resource that examines the incorporation of pattern management in business technologies as well as decision making and prediction process through the use of data management and analysis. Featuring coverage on a broad range of topics such as business intelligence, feature extraction, and data collection, this publication is geared towards professionals, academicians, practitioners, and researchers seeking current research on the development of pattern management systems for business applications.

Big Data, Big Analytics

Michael Minelli,Michele Chambers,Ambiga Dhiraj
Big Data Big Analytics Book PDF

Author : Michael Minelli,Michele Chambers,Ambiga Dhiraj
Publisher : John Wiley & Sons
Page : 230 pages
File Size : 49,5 Mb
Release : 2013-01-22
Category : Business & Economics
ISBN : 9781118147603

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Big Data, Big Analytics by Michael Minelli,Michele Chambers,Ambiga Dhiraj Pdf

Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more.

Big Data Analytics

David Loshin
Big Data Analytics Book PDF

Author : David Loshin
Publisher : Elsevier
Page : 143 pages
File Size : 44,9 Mb
Release : 2013-08-23
Category : Computers
ISBN : 9780124186644

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Big Data Analytics by David Loshin Pdf

Big Data Analytics will assist managers in providing an overview of the drivers for introducing big data technology into the organization and for understanding the types of business problems best suited to big data analytics solutions, understanding the value drivers and benefits, strategic planning, developing a pilot, and eventually planning to integrate back into production within the enterprise. Guides the reader in assessing the opportunities and value proposition Overview of big data hardware and software architectures Presents a variety of technologies and how they fit into the big data ecosystem

Applied Big Data Analytics in Operations Management

Kumar, Manish
Applied Big Data Analytics in Operations Management Book PDF

Author : Kumar, Manish
Publisher : IGI Global
Page : 251 pages
File Size : 40,7 Mb
Release : 2016-09-30
Category : Business & Economics
ISBN : 9781522508878

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Applied Big Data Analytics in Operations Management by Kumar, Manish Pdf

Operations management is a tool by which companies can effectively meet customers’ needs using the least amount of resources necessary. With the emergence of sensors and smart metering, big data is becoming an intrinsic part of modern operations management. Applied Big Data Analytics in Operations Management enumerates the challenges and creative solutions and tools to apply when using big data in operations management. Outlining revolutionary concepts and applications that help businesses predict customer behavior along with applications of artificial neural networks, predictive analytics, and opinion mining on business management, this comprehensive publication is ideal for IT professionals, software engineers, business professionals, managers, and students of management.

Enterprise Big Data Engineering, Analytics, and Management

Atzmueller, Martin
Enterprise Big Data Engineering Analytics and Management Book PDF

Author : Atzmueller, Martin
Publisher : IGI Global
Page : 272 pages
File Size : 47,8 Mb
Release : 2016-06-01
Category : Computers
ISBN : 9781522502944

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Enterprise Big Data Engineering, Analytics, and Management by Atzmueller, Martin Pdf

The significance of big data can be observed in any decision-making process as it is often used for forecasting and predictive analytics. Additionally, big data can be used to build a holistic view of an enterprise through a collection and analysis of large data sets retrospectively. As the data deluge deepens, new methods for analyzing, comprehending, and making use of big data become necessary. Enterprise Big Data Engineering, Analytics, and Management presents novel methodologies and practical approaches to engineering, managing, and analyzing large-scale data sets with a focus on enterprise applications and implementation. Featuring essential big data concepts including data mining, artificial intelligence, and information extraction, this publication provides a platform for retargeting the current research available in the field. Data analysts, IT professionals, researchers, and graduate-level students will find the timely research presented in this publication essential to furthering their knowledge in the field.

Big Data Technologies and Applications

Borko Furht,Flavio Villanustre
Big Data Technologies and Applications Book PDF

Author : Borko Furht,Flavio Villanustre
Publisher : Springer
Page : 400 pages
File Size : 47,5 Mb
Release : 2016-09-16
Category : Computers
ISBN : 9783319445502

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Big Data Technologies and Applications by Borko Furht,Flavio Villanustre Pdf

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.

Big Data Analytics

Mrutyunjaya Panda,Ajith Abraham,Aboul Ella Hassanien
Big Data Analytics Book PDF

Author : Mrutyunjaya Panda,Ajith Abraham,Aboul Ella Hassanien
Publisher : CRC Press
Page : 255 pages
File Size : 54,9 Mb
Release : 2018-12-12
Category : Business & Economics
ISBN : 9781351622585

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Big Data Analytics by Mrutyunjaya Panda,Ajith Abraham,Aboul Ella Hassanien Pdf

Social networking has increased drastically in recent years, resulting in an increased amount of data being created daily. Furthermore, diversity of issues and complexity of the social networks pose a challenge in social network mining. Traditional algorithm software cannot deal with such complex and vast amounts of data, necessitating the development of novel analytic approaches and tools. This reference work deals with social network aspects of big data analytics. It covers theory, practices and challenges in social networking. The book spans numerous disciplines like neural networking, deep learning, artificial intelligence, visualization, e-learning in higher education, e-healthcare, security and intrusion detection.

Managerial Perspectives on Intelligent Big Data Analytics

Sun, Zhaohao
Managerial Perspectives on Intelligent Big Data Analytics Book PDF

Author : Sun, Zhaohao
Publisher : IGI Global
Page : 335 pages
File Size : 54,5 Mb
Release : 2019-02-22
Category : Computers
ISBN : 9781522572787

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Managerial Perspectives on Intelligent Big Data Analytics by Sun, Zhaohao Pdf

Big data, analytics, and artificial intelligence are revolutionizing work, management, and lifestyles and are becoming disruptive technologies for healthcare, e-commerce, and web services. However, many fundamental, technological, and managerial issues for developing and applying intelligent big data analytics in these fields have yet to be addressed. Managerial Perspectives on Intelligent Big Data Analytics is a collection of innovative research that discusses the integration and application of artificial intelligence, business intelligence, digital transformation, and intelligent big data analytics from a perspective of computing, service, and management. While highlighting topics including e-commerce, machine learning, and fuzzy logic, this book is ideally designed for students, government officials, data scientists, managers, consultants, analysts, IT specialists, academicians, researchers, and industry professionals in fields that include big data, artificial intelligence, computing, and commerce.

Network Data Analytics

K. G. Srinivasa,Siddesh G. M.,Srinidhi H.
Network Data Analytics Book PDF

Author : K. G. Srinivasa,Siddesh G. M.,Srinidhi H.
Publisher : Springer
Page : 398 pages
File Size : 51,5 Mb
Release : 2018-04-26
Category : Computers
ISBN : 9783319778006

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Network Data Analytics by K. G. Srinivasa,Siddesh G. M.,Srinidhi H. Pdf

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.