Описание: This book includes the proceedings of the Intelligent and Fuzzy Techniques INFUS 2019 Conference, held in Istanbul, Turkey, on July 23–25, 2019. Big data analytics refers to the strategy of analyzing large volumes of data, or big data, gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. Big data analytics allows data scientists and various other users to evaluate large volumes of transaction data and other data sources that traditional business systems would be unable to tackle. Data-driven and knowledge-driven approaches and techniques have been widely used in intelligent decision-making, and they are increasingly attracting attention due to their importance and effectiveness in addressing uncertainty and incompleteness. INFUS 2019 focused on intelligent and fuzzy systems with applications in big data analytics and decision-making, providing an international forum that brought together those actively involved in areas of interest to data science and knowledge engineering. These proceeding feature about 150 peer-reviewed papers from countries such as China, Iran, Turkey, Malaysia, India, USA, Spain, France, Poland, Mexico, Bulgaria, Algeria, Pakistan, Australia, Lebanon, and Czech Republic.
Описание: This volume is aiming at a wide range of readers andresearchers in the area of Big Data by presenting the recent advances in the fieldsof Big Data Analysis, as well as the techniques and tools used to analyze it.
Описание: This book describes analytical techniques for optimizing knowledge acquisition, processing, and propagation, especially in the contexts of cyber-infrastructure and big data.
Develop modern solutions with Snowflake's unique architecture and integration capabilities; process bulk and real-time data into a data lake; and leverage time travel, cloning, and data-sharing features to optimize data operations
Key Features
Build and scale modern data solutions using the all-in-one Snowflake platform
Perform advanced cloud analytics for implementing big data and data science solutions
Make quicker and better-informed business decisions by uncovering key insights from your data
Book Description
Snowflake is a unique cloud-based data warehousing platform built from scratch to perform data management on the cloud. This book introduces you to Snowflake's unique architecture, which places it at the forefront of cloud data warehouses.
You'll explore the compute model available with Snowflake, and find out how Snowflake allows extensive scaling through the virtual warehouses. You will then learn how to configure a virtual warehouse for optimizing cost and performance. Moving on, you'll get to grips with the data ecosystem and discover how Snowflake integrates with other technologies for staging and loading data.
As you progress through the chapters, you will leverage Snowflake's capabilities to process a series of SQL statements using tasks to build data pipelines and find out how you can create modern data solutions and pipelines designed to provide high performance and scalability. You will also get to grips with creating role hierarchies, adding custom roles, and setting default roles for users before covering advanced topics such as data sharing, cloning, and performance optimization.
By the end of this Snowflake book, you will be well-versed in Snowflake's architecture for building modern analytical solutions and understand best practices for solving commonly faced problems using practical recipes.
What You Will Learn
Get to grips with data warehousing techniques aligned with Snowflake's cloud architecture
Broaden your skills as a data warehouse designer to cover the Snowflake ecosystem
Transfer skills from on-premise data warehousing to the Snowflake cloud analytics platform
Optimize performance and costs associated with a Snowflake solution
Stage data on object stores and load it into Snowflake
Secure data and share it efficiently for access
Manage transactions and extend Snowflake using stored procedures
Extend cloud data applications using Spark Connector
Who this book is for
This book is for data warehouse developers, data analysts, database administrators, and anyone involved in designing, implementing, and optimizing a Snowflake data warehouse. Knowledge of data warehousing and database and cloud concepts will be useful. Basic familiarity with Snowflake is beneficial, but not necessary.
Автор: Akerkar Rajendra, Sajja Priti Srinivas Название: Intelligent Techniques for Data Science ISBN: 3319805142 ISBN-13(EAN): 9783319805146 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Preface.- Introduction.- Data Analytics.- Basic Learning Algorithms.- Fuzzy Logic.- Artificial Neural Networks.- Genetic Algorithms and Evolutionary Computing.- Other Metaheuristics and Classification Approaches.- Analytics and Big Data.- Data Analytics Using R.- Appendix I: Tools for Data Science.- Appendix II: Tools for Computational Intelligence.
Автор: Qamar Usman, Raza Muhammad Summair Название: Data Science Concepts and Techniques with Applications ISBN: 981156132X ISBN-13(EAN): 9789811561320 Издательство: Springer Цена: 6986.00 р. Наличие на складе: Поставка под заказ.
Описание: This book comprehensively covers the topic of data science. Followed by discussion on wide range of applications of data science and widely used techniques in data science.The second section is devoted to the tools and techniques of data science.
Описание: This book describes analytical techniques for optimizing knowledge acquisition, processing, and propagation, especially in the contexts of cyber-infrastructure and big data. Further, it presents easy-to-use analytical models of knowledge-related processes and their applications. The need for such methods stems from the fact that, when we have to decide where to place sensors, or which algorithm to use for processing the data—we mostly rely on experts’ opinions. As a result, the selected knowledge-related methods are often far from ideal. To make better selections, it is necessary to first create easy-to-use models of knowledge-related processes. This is especially important for big data, where traditional numerical methods are unsuitable. The book offers a valuable guide for everyone interested in big data applications: students looking for an overview of related analytical techniques, practitioners interested in applying optimization techniques, and researchers seeking to improve and expand on these techniques.
Автор: J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed, Pandian Vasant Название: Deep Learning Techniques and Optimization Strategies in Big Data Analytics ISBN: 179981193X ISBN-13(EAN): 9781799811930 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 27027.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there's a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.
Автор: J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed, Название: Deep Learning Techniques and Optimization Strategies in Big Data Analytics ISBN: 1799811921 ISBN-13(EAN): 9781799811923 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 35897.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there's a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.
Автор: B. S.P. Mishra; Satchidananda Dehuri; Euiwhan Kim; Название: Techniques and Environments for Big Data Analysis ISBN: 3319275186 ISBN-13(EAN): 9783319275185 Издательство: Springer Рейтинг: Цена: 16979.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume is aiming at a wide range of readers andresearchers in the area of Big Data by presenting the recent advances in the fieldsof Big Data Analysis, as well as the techniques and tools used to analyze it.
Автор: Lee, Robert Ulric Read, Andrew Marttin, Felix Poulain, Florence Funge-smith, Simon Название: Fisheries emergency rapid assessment tool (ferat) ISBN: 9251323143 ISBN-13(EAN): 9789251323144 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 4574.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Guides the assessment of fisheries after natural or technological disasters and during complex or protracted emergencies. This tool provides guidance in the form of decision trees, divided into six steps - ranging from beneficiaries assessment to impact monitoring - that should be followed in sequence.
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