BOOKS - Big Data Analytics Theory, Techniques, Platforms, and Applications
Big Data Analytics Theory, Techniques, Platforms, and Applications - Umit Demirbaga, Gagangeet Singh Aujla, Anish Jindal 2024 PDF | EPUB Springer BOOKS
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Big Data Analytics Theory, Techniques, Platforms, and Applications
Author: Umit Demirbaga, Gagangeet Singh Aujla, Anish Jindal
Year: 2024
Format: PDF | EPUB
File size: 39.8 MB
Language: ENG



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Book Description: 'Big Data Analytics Theory Techniques Platforms and Applications' is a comprehensive guide that provides insights into the latest trends, techniques, and applications of big data analytics. The book covers the fundamental concepts, theories, and methodologies of big data analytics, including data mining, machine learning, and data visualization. It also explores the current state-of-the-art platforms and tools used in big data analytics, such as Hadoop, Spark, and NoSQL databases. Additionally, the book delves into real-world applications of big data analytics in various industries, including healthcare, finance, and retail. The book begins by discussing the evolution of technology and its impact on society, highlighting the need to develop a personal paradigm for understanding the technological process of developing modern knowledge. This paradigm is essential for survival in a warring world, where the ability to adapt and evolve is crucial. The author emphasizes the importance of studying and understanding the process of technology evolution to stay ahead of the curve and remain relevant in the ever-changing landscape of big data analytics. The book then delves into the fundamentals of big data analytics, explaining the concept of big data and its significance in today's data-driven world. It covers the different types of big data, including structured, semi-structured, and unstructured data, and their unique characteristics and challenges. The author also discusses the role of data mining and machine learning in big data analytics, providing insights into the latest techniques and methodologies used in these fields.
«Платформы и приложения для теории аналитики больших данных» - это всеобъемлющее руководство, в котором представлены последние тенденции, методы и приложения для аналитики больших данных. Книга охватывает фундаментальные концепции, теории и методологии аналитики больших данных, включая интеллектуальный анализ данных, машинное обучение и визуализацию данных. В нем также рассматриваются современные платформы и инструменты, используемые в аналитике больших данных, такие как базы данных Hadoop, Spark и NoSQL. Кроме того, книга углубляется в реальные приложения аналитики больших данных в различных отраслях, включая здравоохранение, финансы и розничную торговлю. Книга начинается с обсуждения эволюции технологий и их влияния на общество, подчёркивая необходимость выработки личностной парадигмы понимания технологического процесса развития современных знаний. Эта парадигма необходима для выживания в воюющем мире, где способность адаптироваться и развиваться имеет решающее значение. Автор подчеркивает важность изучения и понимания процесса эволюции технологий, чтобы оставаться на опережение и сохранять актуальность в постоянно меняющемся ландшафте аналитики больших данных. Затем книга углубляется в основы аналитики больших данных, объясняя концепцию больших данных и их значение в современном мире, управляемом данными. Она охватывает различные типы больших данных, включая структурированные, полуструктурированные и неструктурированные данные, а также их уникальные характеристики и проблемы. Автор также обсуждает роль интеллектуального анализа данных и машинного обучения в аналитике больших данных, предоставляя информацию о новейших методах и методологиях, используемых в этих областях.
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