Название: Data Analytics and Machine Learning: Navigating the Big Data Landscape
Автор: Рushра Singh, Аshа Rаni Мishrа, Рауаl Gаrg
Издательство: Springer
Серия: Studies in Big Data
Год: 2024
Страниц: 357
Язык: английский
Формат: pdf (true)
Размер: 10.7 MB

This book presents an in-depth analysis of successful data-driven initiatives, highlighting how organizations have leveraged data to drive decision-making processes, optimize operations, and achieve remarkable outcomes. Through case studies, readers gain valuable insights and learn practical strategies for implementing data analytics, Big Data, and Machine Learning solutions in their own organizations. The book discusses the transformative power of data analytics and Big Data in various industries and sectors and how Machine Learning applications have revolutionized exploration by enabling advanced data analysis techniques for mapping, geospatial analysis, and environmental monitoring, enhancing our understanding of the world and its dynamic processes. This book explores how Big Data explosion, the power of analytics and Machine Learning revolution can bring new prospects and opportunities in the dynamic and data-rich landscape. It highlights the future research directions in data analytics, Big Data, and Machine Learning that explores the emerging trends, challenges, and opportunities in these fields by covering interdisciplinary approaches such as handling and analyzing real-time and streaming data. The study is done using a popular statistical tool named R programming.

Название: Big Data Management and Analytics
Автор: Вrij В Guрtа and Маmtа
Издательство: World Scientific Publishing
Год: 2024
Страниц: 288
Язык: английский
Формат: pdf (true)
Размер: 19.6 MB

With the proliferation of information, Big Data management and analysis have become an indispensable part of any system to handle such amounts of data. The amount of data generated by the multitude of interconnected devices increases exponentially, making the storage and processing of these data a real challenge. Big Data management and analytics have gained momentum in almost every industry, ranging from finance or healthcare. Big Data can reveal key insights if handled and analyzed properly; it has great application potential to improve the working of any industry. This book covers the spectrum aspects of Big Data; from the preliminary level to specific case studies. It will help readers gain knowledge of the Big Data landscape.Highlights of the topics covered include description of the Big Data ecosystem; real-world instances of Big Data issues; how the Vs of Big Data (volume, velocity, variety, veracity, valence, and value) affect data collection, monitoring, storage, analysis, and reporting; structural process to get value out of Big Data and recognize the differences between a standard database management system and a Big Data management system. Readers will gain insights into choice of data models, data extraction, data integration to solve large data problems, data modelling using Machine Learning techniques, Spark's scalable Machine Learning techniques, modeling a Big Data problem into a graph database and performing scalable analytical operations over the graph and different tools and techniques for processing Big Data and its applications including in healthcare and finance.

Название: Big Data and Hadoop: Fundamentals, tools, and techniques for data-driven success - 2nd Edition
Автор: Мауаnk Вhushаn
Издательство: BPB Publications
Год: 2024
Страниц: 548
Язык: английский
Формат: epub (true)
Размер: 27.8 MB

In today's data-driven world, harnessing the power of big data is no longer a luxury, but a necessity. This comprehensive guide, "Big Data and Hadoop," dives deep into the world of big data and equips you with the knowledge and skills you need to conquer even the most complex data landscapes. Start with the fundamentals of big data, exploring its growing significance and diverse applications. You'll look into the heart of the Apache Hadoop ecosystem, mastering its core components like HDFS and MapReduce. We'll demystify NoSQL databases, introducing you to HBase and Cassandra as powerful alternatives to traditional databases. Clarify the details of MapReduce programming with practical examples, and discover the power of PigLatin and HiveQL for efficient data analysis. Explore advanced tools like Spark, unlocking its potential for real-time data processing and analytics. Rounding out your knowledge, the book delves into practical applications, exploring real-world scenarios and research-based insights. By the end of this book, you'll emerge as a confident big data explorer, equipped to tackle any data challenge with expertise and precision. Whether you are a beginner or have some experience with Big Data. This book is for aspiring Big Data professionals, including data analysts, software developers, IT professionals, and students in Computer Science and related fields.

Название: Hypothesis Generation and Interpretation: Design Principles and Patterns for Big Data Applications
Автор: Нirоshi Ishikаwа
Издательство: Springer
Серия: Studies in Big Data
Год: 2024
Страниц: 380
Язык: английский
Формат: pdf (true)
Размер: 11.1 MB

This book focuses in detail on Data Science and data analysis and emphasizes the importance of data engineering and data management in the design of Big Data applications. The author uses patterns discovered in a collection of Big Data applications to provide design principles for hypothesis generation, integrating Big Data processing and management, Machine Learning and data mining techniques. The book proposes and explains innovative principles for interpreting hypotheses by integrating micro-explanations (those based on the explanation of analytical models and individual decisions within them) with macro-explanations (those based on applied processes and model generation). Practical case studies are used to demonstrate how hypothesis-generation and -interpretation technologies work. These are based on “social infrastructure” applications like in-bound tourism, disaster management, lunar and planetary exploration, and treatment of infectious diseases. The novel methods and technologies proposed in Hypothesis Generation and Interpretation are supported by the incorporation of historical perspectives on science and an emphasis on the origin and development of the ideas behind their design principles and patterns. In the Big Data era, characterized by volume, variety, and velocity, which generates a large amount of diverse data at high speed, the role of a hypothesis is more important to generate the final value, and such a hypothesis is more complicated and complex than ever. At the same time, the era of Big Data creates new vague concerns for end users as to whether Big Data relevant to them will be used appropriately.

Название: Прогнозирование: принципы и практика
Автор: Poн Xaйндмaн, Джopдж Aтaнacoпyлoc
Издательство: ДМК Пресс
Год: 2023
Страниц: 459
Язык: русский
Формат: pdf
Размер: 19.9 MB

Данная книга представляет собой всестороннее введение в методы прогнозирования и содержит достаточно информации о каждом из них, помогая читателям разумно их использовать. Примеры с многочисленными наборами данных на языке R авторы заимствовали из собственного опыта консультирования. В конце глав приводятся упражнения по пройденной теме. На протяжении всей книги мы используем язык программирования R и хотим, чтобы студенты научились делать прогнозы с помощью R. Язык R бесплатен и доступен практически в любой операционной системе. Это прекрасный инструмент для любого статистического анализа, а не только для прогнозирования. Инструкции по инсталлированию и использованию R см. в приложении А «Использование языка R». Все примеры на R в книге основаны на допущении, что вы сначала скачали пакет fpp3.

Название: Big Data Analytics and Computational Intelligence for Cybersecurity
Автор: Mariya Ouaissa, Zakaria Boulouard
Издательство: Springer
Год: 2022
Страниц: 336
Язык: английский
Формат: pdf (true), epub
Размер: 35.5 MB

This book presents a collection of state-of-the-art Artificial Intelligence (AI) and Big Data analytics approaches to cybersecurity intelligence. It illustrates the latest trends in AI/ML-based strategic defense mechanisms against malware, vulnerabilities, cyber threats, as well as proactive countermeasures. It also introduces other trending technologies, such as blockchain, SDN, and IoT, and discusses their possible impact on improving security. The book discusses the convergence of AI/ML and big data in cybersecurity by providing an overview of theoretical, practical, and simulation concepts of computational intelligence and big data analytics used in different approaches of security. It also displays solutions that will help analyze complex patterns in user data and ultimately improve productivity.

Название: Big Data Intelligence for Smart Applications
Автор: Youssef Baddi, Youssef Gahi, Yassine Maleh
Издательство: Springer
Год: 2022
Страниц: 343
Язык: английский
Формат: pdf (true), epub
Размер: 38.9 MB

Today, the use of Machine Intelligence, expert systems, and analytical technologies combined with Big Data is the natural evolution of both disciplines. As a result, there is a pressing need for new and innovative algorithms to help us find effective and practical solutions for smart applications such as smart cities, IoT, healthcare, and cybersecurity. This book presents the latest advances in Big Data intelligence for smart applications. It explores several problems and their solutions regarding computational intelligence and big data for smart applications. It also discusses new models, practical solutions,and technological advances related to developing and transforming cities through Machine Intelligence and Big Data models and techniques. This book is helpful for students and researchers as well as practitioners. It is worth noting that technologies such as Artificial intelligence and Big Data are evolving even faster. They are rapidly growing by holding great promise for many sectors. The real revolutionary potential of these technologies mainly relies on their convergence. Big Data and Artificial Intelligence are two technologies that are inextricably linked, to the point that we can think about Big Data Intelligence. AI has become ubiquitous in many industries where intelligent programs relying on big data transform decision-making.

Название: HPC, Big Data, and AI Convergence Towards Exascale: Challenge and Vision
Автор: Olivier Terzo, Jan Martinovic
Издательство: CRC Press
Год: 2022
Страниц: 323
Язык: английский
Формат: pdf (true)
Размер: 31.2 MB

HPC, Big Data, AI Convergence Towards Exascale provides an updated vision on the most advanced computing, storage, and interconnection technologies, that are at basis of convergence among the High-Performance Computing (HPC), Cloud, Big Data, and Artificial Intelligence (AI) domains. All the chapters in this book pave the road to new generation of technologies, support their development and, in addition, verify them on real-world problems. The readers will find this book useful because it provides an overview of currently available technologies that fit with the concept of unified Cloud-HPC-Big Data-AI applications and presents examples of their actual use in scientific and industrial applications.

Название: Practical business statistics
Автор: Maria Catherine Borres
Издательство: Society Publishing
Год: 2020
Страниц: 220
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Practical business statistics explains the subject of statistics and the role it plays in the businesses and also talks about the process of data mining and Big Data in this field. The book discusses the various aspects related to data structure and explains the distribution of data on a histogram to the readers. The book further throws light on the concept of variability and data and the use of probability in the businesses. Also discussed in the book is the concept on uncertainty of numbers in the businesses, giving an overview of the random variables, the concept of confidence interval, the explanation of hypothesis testing and regression analysis and the role of report writing in the proper communication of the results so that the readers get a full insight on the various aspects of statistics in businesses.

Название: The DataOps Revolution: Delivering the Data-Driven Enterprise
Автор: Simon Trewin
Издательство: Auerbach Publications, CRC Press
Год: 2022
Страниц: 194
Язык: английский
Формат: pdf (true)
Размер: 18.7 MB

DataOps is a new way of delivering data and analytics that is proven to get results. It enables IT and users to collaborate in the delivery of solutions that help organisations to embrace a data-driven culture. The DataOps Revolution: Delivering the Data-Driven Enterprise is a narrative about real world issues involved in using DataOps to make data-driven decisions in modern organisations. The book is built around real delivery examples based on the author’s own experience and lays out principles and a methodology for business success using DataOps. Presenting practical design patterns and DataOps approaches, the book shows how DataOps projects are run and presents the benefits of using DataOps to implement data solutions.