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Development Methodologies for Big Data Analytics Systems

Author : Manuel Mora

Publisher : Springer Nature

Page : 289 pages

File Size : 19,2 MB

Release : 2023-11-03

Category : Technology & Engineering

ISBN : 3031409566

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Book Description

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

Author : Saumyadipta Pyne

Publisher : Springer

Page : 278 pages

File Size : 17,4 MB

Release : 2016-10-12

Category : Computers

ISBN : 8132236289

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Book Description

This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.



Big Data Analytics: Systems, Algorithms, Applications

Author : C.S.R. Prabhu

Publisher : Springer Nature

Page : 412 pages

File Size : 21,10 MB

Release : 2019-10-14

Category : Computers

ISBN : 9811500940

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Book Description

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.



Enterprise Big Data Engineering, Analytics, and Management

Author : Atzmueller, Martin

Publisher : IGI Global

Page : 293 pages

File Size : 36,82 MB

Release : 2016-06-01

Category : Computers

ISBN : 1522502947

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Book Description

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.



Marketing and Big Data Analytics in Tourism and Events

Author : Hashem, Tareq Nael

Publisher : IGI Global

Page : 313 pages

File Size : 19,13 MB

Release : 2024-05-06

Category : Business & Economics

ISBN :

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Book Description

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.



Designing Big Data Platforms

Author : Yusuf Aytas

Publisher : John Wiley & Sons

Page : 338 pages

File Size : 38,98 MB

Release : 2021-07-27

Category : Mathematics

ISBN : 1119690927

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Book Description

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.



Big Data Analytics in Agile Software Development

Author : David Gerald

Publisher :

Page : 75 pages

File Size : 22,34 MB

Release : 2021-07-04

Category :

ISBN :

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Book Description

Over the last decade, Agile methods have changed the software development process in an unparalleled way. As opposed to traditional, plan-driven models of software development (e.g. waterfall model), where processes are organized in a series of sequentially ordered stages, Agile software development (ASD) entails collaborative development with swift and incremental iterations. As a result, adaptability to fre- quently changing requirements and a strong emphasis on delivering value to customers represent the crux of ASD and have driven its wide acceptance among software practitioners in the last years. Furthermore, this paradigm shift from plan-driven software development processes to ASD accorded with social and technological advances. Keywords: Big Data analytics in Agile software development big data facebook big data baseball big data analysis for green computing concepts and applications big data big climb big data systems big data healthcare big data aws big data science big data mba big data a big data dragon tank big data a revolution that will transform big data a revolution that will transform how we live work and think big data algorithms big data analysis big data analytics big data and health analytics big data and social science big data architect big data architecture big data at work big data band big data big analytics big data big climb big data big design big data book big data dangerous big data demystified big data design big data does size matter big data driven business big data engineer big data engineering big data español big data finance big data for beginners big data for social good big data frameworks big data fundamentals big data fundamentals concepts, drivers & techniques big data genomics big data glossary big data health analytics big data in education big data in finance big data in healthcare big data in practice big data integration big data interview big data lake big data management big data manning big data marketing big data marz big data mba big data mba driving business strategies with data science big data modeling big data on campus big data para ceos y directores de marketing big data platform big data policing big data principles and best practices big data profits success analytics big data project big data project management big data python big data questions and answers big data race big data real estate big data revolution big data science big data science in finance big data security big data small wars big data spanish big data spark big data system big data technologies for business big data textbook big data uncharted big data understanding how data powers big business big data using hadoop big data using hadoop and hive big data visualization big data with java big data with spark



Agile Analytics

Author : Ken Collier

Publisher : Addison-Wesley

Page : 368 pages

File Size : 37,9 MB

Release : 2012

Category : Business & Economics

ISBN : 032150481X

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Book Description

Using Agile methods, you can bring far greater innovation, value, and quality to any data warehousing (DW), business intelligence (BI), or analytics project. However, conventional Agile methods must be carefully adapted to address the unique characteristics of DW/BI projects. In Agile Analytics, Agile pioneer Ken Collier shows how to do just that. Collier introduces platform-agnostic Agile solutions for integrating infrastructures consisting of diverse operational, legacy, and specialty systems that mix commercial and custom code. Using working examples, he shows how to manage analytics development teams with widely diverse skill sets and how to support enormous and fast-growing data volumes. Collier's techniques offer optimal value whether your projects involve "back-end" data management, "front-end" business analysis, or both. Part I focuses on Agile project management techniques and delivery team coordination, introducing core practices that shape the way your Agile DW/BI project community can collaborate toward success Part II presents technical methods for enabling continuous delivery of business value at production-quality levels, including evolving superior designs; test-driven DW development; version control; and project automation Collier brings together proven solutions you can apply right now--whether you're an IT decision-maker, data warehouse professional, database administrator, business intelligence specialist, or database developer. With his help, you can mitigate project risk, improve business alignment, achieve better results--and have fun along the way.



Model Management and Analytics for Large Scale Systems

Author : Bedir Tekinerdogan

Publisher : Academic Press

Page : 344 pages

File Size : 10,87 MB

Release : 2019-09-14

Category : Computers

ISBN : 0128166509

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Book Description

Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics. This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management. Identifies key problems and offers solution approaches and tools that have been developed or are necessary for model management and analytics Explores basic theory and background, current research topics, related challenges and the research directions for model management and analytics Provides a complete overview of model management and analytics frameworks, the different types of analytics (descriptive, diagnostics, predictive and prescriptive), the required modelling and method steps, and important future directions



High-Performance Big-Data Analytics

Author : Pethuru Raj

Publisher : Springer

Page : 443 pages

File Size : 46,84 MB

Release : 2015-10-16

Category : Computers

ISBN : 331920744X

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Book Description

This book presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. Features: includes case studies and learning activities throughout the book and self-study exercises in every chapter; presents detailed case studies on social media analytics for intelligent businesses and on big data analytics (BDA) in the healthcare sector; describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data; examines real-time analytics solutions; introduces in-database processing and in-memory analytics techniques for data mining; discusses the use of mainframes for handling real-time big data and the latest types of data management systems for BDA; provides information on the use of cluster, grid and cloud computing systems for BDA; reviews the peer-to-peer techniques and tools and the common information visualization techniques, used in BDA.