Optimizing The Big Data Problem Statement

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Optimizing the Big Data Problem Statement

Author : Roy Jafari
Publisher : Roy Jafari
ISBN 13 :
Total Pages : 127 pages
Book Rating : 4./5 ( download)

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Book Synopsis Optimizing the Big Data Problem Statement by : Roy Jafari

Download or read book Optimizing the Big Data Problem Statement written by Roy Jafari and published by Roy Jafari. This book was released on 2023-05-02 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today's tech world, Big Data is the name of the game and a unique and powerful opportunity that can unlock a lot of potential. However, before you can start using big data, you need to have a clear understanding of the problem you are trying to solve. This is where problem statement optimization comes in. Problem statement optimization is the process of finding the right balance between the cost of understanding the problem and the cost of making future mistakes. The cost of understanding the big data problem includes the time and resources it takes to understand how exactly the size of the data is challenging you, and that empowers you to be able to find the right solution for your big data problem. The cost of making future mistakes includes the cost of fixing mistakes in the model, the cost of lost opportunities, and the cost of damage to your reputation. The book comprises five chapters covering various aspects of Big Data preparation, including Understanding Big Data Problems Cross-Industry Standard Process for Data Mining (CRISP-DM) Data Solution Life Cycle (DSLC) Types of Data Manipulations Recognizing the Right Data-Prep Problem. This book is a valuable resource for anyone who wants to use big data to solve problems. Whether you are a data scientist, analyst, or business professional, this book will help you get the most out of big data. Here are some additional benefits of reading this book: You will learn how to use big data to solve real-world problems. You will develop the skills you need to be successful in the world of big data. You will gain a deeper understanding If you are serious about using big data, then this book is a must-read.

Big Data Optimization: Recent Developments and Challenges

Author : Ali Emrouznejad
Publisher : Springer
ISBN 13 : 3319302655
Total Pages : 492 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Big Data Optimization: Recent Developments and Challenges by : Ali Emrouznejad

Download or read book Big Data Optimization: Recent Developments and Challenges written by Ali Emrouznejad and published by Springer. This book was released on 2016-05-26 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.

Data Mining and Big Data

Author : Ying Tan
Publisher : Springer
ISBN 13 : 9813295635
Total Pages : 340 pages
Book Rating : 4.8/5 (132 download)

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Book Synopsis Data Mining and Big Data by : Ying Tan

Download or read book Data Mining and Big Data written by Ying Tan and published by Springer. This book was released on 2019-07-25 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th International Conference on Data Mining and Big Data, DMBD 2019, held in Chiang Mai, Thailand, in July 2019. The 26 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 79 submissions. They are organized in topical sections named: data analysis; prediction; clustering; classification; mining pattern; mining tasks.

Integration of IoT with Cloud Computing for Smart Applications

Author : Rohit Anand
Publisher : CRC Press
ISBN 13 : 1000906094
Total Pages : 267 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Integration of IoT with Cloud Computing for Smart Applications by : Rohit Anand

Download or read book Integration of IoT with Cloud Computing for Smart Applications written by Rohit Anand and published by CRC Press. This book was released on 2023-07-25 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integration of IoT with Cloud Computing for Smart Applications provides an integrative overview of the Internet of Things (IoT) and cloud computing to be used for the various futuristic and intelligent applications. The aim of this book is to integrate IoT and cloud computing to translate ordinary resources into smart things. Discussions in this book include a broad and integrated perspective on the collaboration, security, growth of cloud infrastructure, and real-time data monitoring. Features: Presents an integrated approach to solve the problems related to security, reliability, and energy consumption. Explains a unique approach to discuss the research challenges and opportunities in the field of IoT and cloud computing. Discusses a novel approach for smart agriculture, smart healthcare systems, smart cities and many other modern systems based on machine learning, artificial intelligence, and big data, etc. Information presented in a simplified way for students, researchers, academicians and scientists, business innovators and entrepreneurs, management professionals and practitioners. This book can be great reference for graduate and postgraduate students, researchers, and academicians working in the field of computer science, cloud computing, artificial intelligence, etc.

Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications

Author : Arun Kumar Sangaiah
Publisher : Academic Press
ISBN 13 : 0128133279
Total Pages : 364 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications by : Arun Kumar Sangaiah

Download or read book Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications written by Arun Kumar Sangaiah and published by Academic Press. This book was released on 2018-08-21 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural network (NN), particle swarm optimization (PSO), evolutionary algorithm (GA), fuzzy sets (FS) and rough sets (RS), etc. Furthermore, the book highlights recent research on representative techniques to elaborate how a data-centric system formed a powerful platform for the processing of cloud hosted multimedia big data and how it could be analyzed, processed and characterized by CI. The book also provides a view on how techniques in CI can offer solutions in modeling, relationship pattern recognition, clustering and other problems in bioengineering. It is written for domain experts and developers who want to understand and explore the application of computational intelligence aspects (opportunities and challenges) for design and development of a data-centric system in the context of multimedia cloud, big data era and its related applications, such as smarter healthcare, homeland security, traffic control trading analysis and telecom, etc. Researchers and PhD students exploring the significance of data centric systems in the next paradigm of computing will find this book extremely useful. - Presents a brief overview of computational intelligence paradigms and its significant role in application domains - Illustrates the state-of-the-art and recent developments in the new theories and applications of CI approaches - Familiarizes the reader with computational intelligence concepts and technologies that are successfully used in the implementation of cloud-centric multimedia services in massive data processing - Provides new advances in the fields of CI for bio-engineering application

Modern Data Architecture on AWS

Author : Behram Irani
Publisher : Packt Publishing Ltd
ISBN 13 : 1801810125
Total Pages : 420 pages
Book Rating : 4.8/5 (18 download)

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Book Synopsis Modern Data Architecture on AWS by : Behram Irani

Download or read book Modern Data Architecture on AWS written by Behram Irani and published by Packt Publishing Ltd. This book was released on 2023-08-31 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover all the essential design and architectural patterns in one place to help you rapidly build and deploy your modern data platform using AWS services Key Features Learn to build modern data platforms on AWS using data lakes and purpose-built data services Uncover methods of applying security and governance across your data platform built on AWS Find out how to operationalize and optimize your data platform on AWS Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMany IT leaders and professionals are adept at extracting data from a particular type of database and deriving value from it. However, designing and implementing an enterprise-wide holistic data platform with purpose-built data services, all seamlessly working in tandem with the least amount of manual intervention, still poses a challenge. This book will help you explore end-to-end solutions to common data, analytics, and AI/ML use cases by leveraging AWS services. The chapters systematically take you through all the building blocks of a modern data platform, including data lakes, data warehouses, data ingestion patterns, data consumption patterns, data governance, and AI/ML patterns. Using real-world use cases, each chapter highlights the features and functionalities of numerous AWS services to enable you to create a scalable, flexible, performant, and cost-effective modern data platform. By the end of this book, you’ll be equipped with all the necessary architectural patterns and be able to apply this knowledge to efficiently build a modern data platform for your organization using AWS services.What you will learn Familiarize yourself with the building blocks of modern data architecture on AWS Discover how to create an end-to-end data platform on AWS Design data architectures for your own use cases using AWS services Ingest data from disparate sources into target data stores on AWS Build data pipelines, data sharing mechanisms, and data consumption patterns using AWS services Find out how to implement data governance using AWS services Who this book is for This book is for data architects, data engineers, and professionals creating data platforms. The book's use case–driven approach helps you conceptualize possible solutions to specific use cases, while also providing you with design patterns to build data platforms for any organization. It's beneficial for technical leaders and decision makers to understand their organization's data architecture and how each platform component serves business needs. A basic understanding of data & analytics architectures and systems is desirable along with beginner’s level understanding of AWS Cloud.

Big Data

Author : Dan Olteanu
Publisher : Springer
ISBN 13 : 3642394671
Total Pages : 312 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Big Data by : Dan Olteanu

Download or read book Big Data written by Dan Olteanu and published by Springer. This book was released on 2013-06-25 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 29th British National Conference on Databases, BNCOD 2013, held in Oxford, UK, in July 2013. The 20 revised full papers, presented together with three keynote talks, two tutorials, and one panel session, were carefully reviewed and selected from 42 submissions. Special focus of the conference has been "Big Data" and so the papers cover a wide range of topics such as query and update processing; relational storage; benchmarking; XML query processing; big data; spatial data and indexing; data extraction and social networks.

Handbook of Machine Learning for Computational Optimization

Author : Vishal Jain
Publisher : CRC Press
ISBN 13 : 100045567X
Total Pages : 295 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Handbook of Machine Learning for Computational Optimization by : Vishal Jain

Download or read book Handbook of Machine Learning for Computational Optimization written by Vishal Jain and published by CRC Press. This book was released on 2021-11-02 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technology is moving at an exponential pace in this era of computational intelligence. Machine learning has emerged as one of the most promising tools used to challenge and think beyond current limitations. This handbook will provide readers with a leading edge to improving their products and processes through optimal and smarter machine learning techniques. This handbook focuses on new machine learning developments that can lead to newly developed applications. It uses a predictive and futuristic approach, which makes machine learning a promising tool for processes and sustainable solutions. It also promotes newer algorithms that are more efficient and reliable for new dimensions in discovering other applications, and then goes on to discuss the potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making. Individuals looking for machine learning-based knowledge will find interest in this handbook. The readership ranges from undergraduate students of engineering and allied courses to researchers, professionals, and application designers.

Machine Learning and Optimization for Engineering Design

Author : Apoorva S. Shastri
Publisher : Springer Nature
ISBN 13 : 9819974569
Total Pages : 175 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Machine Learning and Optimization for Engineering Design by : Apoorva S. Shastri

Download or read book Machine Learning and Optimization for Engineering Design written by Apoorva S. Shastri and published by Springer Nature. This book was released on 2024-01-27 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to provide a collection of state-of-the-art scientific and technical research papers related to machine learning-based algorithms in the field of optimization and engineering design. The theoretical and practical development for numerous engineering applications such as smart homes, ICT-based irrigation systems, academic success prediction, future agro-industry for crop production, disease classification in plants, dental problems and solutions, loan eligibility processing, etc., and their implementation with several case studies and literature reviews are included as self-contained chapters. Additionally, the book intends to highlight the importance of study and effectiveness in addressing the time and space complexity of problems and enhancing accuracy, analysis, and validations for different practical applications by acknowledging the state-of-the-art literature survey. The book targets a larger audience by exploring multidisciplinary research directions such as computer vision, machine learning, artificial intelligence, modified/newly developed machine learning algorithms, etc., to enhance engineering design applications for society. State-of-the-art research work with illustrations and exercises along with pseudo-code has been provided here.

Optimization and Control for Systems in the Big-Data Era

Author : Tsan-Ming Choi
Publisher : Springer
ISBN 13 : 3319535188
Total Pages : 281 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Optimization and Control for Systems in the Big-Data Era by : Tsan-Ming Choi

Download or read book Optimization and Control for Systems in the Big-Data Era written by Tsan-Ming Choi and published by Springer. This book was released on 2017-05-04 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on optimal control and systems engineering in the big data era. It examines the scientific innovations in optimization, control and resilience management that can be applied to further success. In both business operations and engineering applications, there are huge amounts of data that can overwhelm computing resources of large-scale systems. This “big data” provides new opportunities to improve decision making and addresses risk for individuals as well in organizations. While utilizing data smartly can enhance decision making, how to use and incorporate data into the decision making framework remains a challenging topic. Ultimately the chapters in this book present new models and frameworks to help overcome this obstacle. Optimization and Control for Systems in the Big-Data Era: Theory and Applications is divided into five parts. Part I offers reviews on optimization and control theories, and Part II examines the optimization and control applications. Part III provides novel insights and new findings in the area of financial optimization analysis. The chapters in Part IV deal with operations analysis, covering flow-shop operations and quick response systems. The book concludes with final remarks and a look to the future of big data related optimization and control problems.

Cloud Networking for Big Data

Author : Deze Zeng
Publisher : Springer
ISBN 13 : 3319247204
Total Pages : 114 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Cloud Networking for Big Data by : Deze Zeng

Download or read book Cloud Networking for Big Data written by Deze Zeng and published by Springer. This book was released on 2015-12-09 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces two basic big data processing paradigms for batch data and streaming data. Representative programming frameworks are also presented, as well as software defined networking (SDN) and network function virtualization (NFV) technologies as key cloud networking technologies. The authors illustrate that SDN and NFV can be applied to benefit the big data processing by proposing a cloud networking framework. Based on the framework, two case studies examine how to improve the cost efficiency of big data processing. Cloud Networking for Big Data targets professionals and researchers working in big data, networks, wireless communications and information technology. Advanced-level students studying computer science and electrical engineering will also find this book valuable as a study guide.

Big Data and Networks Technologies

Author : Yousef Farhaoui
Publisher : Springer
ISBN 13 : 3030236722
Total Pages : 380 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Big Data and Networks Technologies by : Yousef Farhaoui

Download or read book Big Data and Networks Technologies written by Yousef Farhaoui and published by Springer. This book was released on 2019-07-17 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the state of the art in big data analysis and networks technologies. It addresses a range of issues that pertain to: signal processing, probability models, machine learning, data mining, databases, data engineering, pattern recognition, visualization, predictive analytics, data warehousing, data compression, computer programming, smart cities, networks technologies, etc. Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. In turn, data science inspires novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and the social sciences. All papers presented here are the product of extensive field research involving applications and techniques related to data analysis in general, and to big data and networks technologies in particular. Given its scope, the book will appeal to advanced undergraduate and graduate students, postdoctoral researchers, lecturers and industrial researchers, as well general readers interested in big data analysis and networks technologies.

Intelligent Systems and Applications

Author : Kohei Arai
Publisher : Springer Nature
ISBN 13 : 3031160754
Total Pages : 859 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Intelligent Systems and Applications by : Kohei Arai

Download or read book Intelligent Systems and Applications written by Kohei Arai and published by Springer Nature. This book was released on 2022-08-31 with total page 859 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a remarkable collection of chapters covering a wide domain of topics related to artificial intelligence and its applications to the real world. The conference attracted a total of 494 submissions from many academic pioneering researchers, scientists, industrial engineers, and students from all around the world. These submissions underwent a double-blind peer-reviewed process. Of the total submissions, 176 submissions have been selected to be included in these proceedings. It is difficult to imagine how artificial intelligence has become an inseparable part of our life. From mobile phones, smart watches, washing machines to smart homes, smart cars, and smart industries, artificial intelligence has helped to revolutionize the whole globe. As we witness exponential growth of computational intelligence in several directions and use of intelligent systems in everyday applications, this book is an ideal resource for reporting latest innovations and future of AI. Distinguished researchers have made valuable studies to understand the various bottlenecks existing in different arenas and how they can be overcome with the use of intelligent systems. This book also provides new directions and dimensions of future research work. We hope that readers find the volume interesting and valuable.

Big Data Analytics Using Multiple Criteria Decision-Making Models

Author : Ramakrishnan Ramanathan
Publisher : CRC Press
ISBN 13 : 1351648691
Total Pages : 435 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Big Data Analytics Using Multiple Criteria Decision-Making Models by : Ramakrishnan Ramanathan

Download or read book Big Data Analytics Using Multiple Criteria Decision-Making Models written by Ramakrishnan Ramanathan and published by CRC Press. This book was released on 2017-07-12 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple Criteria Decision Making (MCDM) is a subfield of Operations Research, dealing with decision making problems. A decision-making problem is characterized by the need to choose one or a few among a number of alternatives. The field of MCDM assumes special importance in this era of Big Data and Business Analytics. In this volume, the focus will be on modelling-based tools for Business Analytics (BA), with exclusive focus on the sub-field of MCDM within the domain of operations research. The book will include an Introduction to Big Data and Business Analytics, and challenges and opportunities for developing MCDM models in the era of Big Data.

Designing Big Data Platforms

Author : Yusuf Aytas
Publisher : John Wiley & Sons
ISBN 13 : 1119690951
Total Pages : 336 pages
Book Rating : 4.1/5 (196 download)

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Book Synopsis Designing Big Data Platforms by : Yusuf Aytas

Download or read book Designing Big Data Platforms written by Yusuf Aytas and published by John Wiley & Sons. This book was released on 2021-07-08 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 and Knowledge Discovery

Author : Robert Wrembel
Publisher : Springer Nature
ISBN 13 : 3031683234
Total Pages : 409 pages
Book Rating : 4.0/5 (316 download)

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Book Synopsis Big Data Analytics and Knowledge Discovery by : Robert Wrembel

Download or read book Big Data Analytics and Knowledge Discovery written by Robert Wrembel and published by Springer Nature. This book was released on with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Big Data Analytics and Knowledge Discovery

Author : Sanjay Madria
Publisher : Springer
ISBN 13 : 3319227297
Total Pages : 419 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Big Data Analytics and Knowledge Discovery by : Sanjay Madria

Download or read book Big Data Analytics and Knowledge Discovery written by Sanjay Madria and published by Springer. This book was released on 2015-08-09 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 17th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2015, held in Valencia, Spain, September 2015. The 31 revised full papers presented were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections similarity measure and clustering; data mining; social computing; heterogeneos networks and data; data warehouses; stream processing; applications of big data analysis; and big data.