Computational Complexity A Modern Approach Amazon
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Amazon Redshift Cookbook
Author: Shruti Worlikar
language: en
Publisher: Packt Publishing Ltd
Release Date: 2025-04-25
Set up a petabyte-scale, cloud-based data warehouse that is burstable and built to scale for end-to-end analytical solutions Key Features Learn how to translate familiar data warehousing concepts into Redshift implementation Use impressive Redshift features to optimize development, productionizing, and operation processes Find out how to use advanced features such as concurrency scaling, Redshift Spectrum, and federated queries Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAmazon Redshift Cookbook offers comprehensive guidance for leveraging AWS's fully managed cloud data warehousing service. Whether you're building new data warehouse workloads or migrating traditional on-premises platforms to the cloud, this essential resource delivers proven implementation strategies. Written by AWS specialists, these easy-to-follow recipes will equip you with the knowledge to successfully implement Amazon Redshift-based data analytics solutions using established best practices. The book focuses on Redshift architecture, showing you how to perform database administration tasks on Redshift. You'll learn how to optimize your data warehouse to quickly execute complex analytic queries against very large datasets. The book covers recipes to help you take full advantage of Redshift's columnar architecture and managed services. You'll discover how to deploy fully automated and highly scalable extract, transform, and load (ETL) processes, helping you minimize the operational effort that you invest in managing regular ETL pipelines and ensuring the timely and accurate refreshing of your data warehouse. By the end of this Redshift book, you'll be able to implement a Redshift-based data analytics solution by adopting best-practice approaches for solving commonly faced problems.What you will learn Integrate data warehouses with data lakes using AWS features Create end-to-end analytical solutions from sourcing to consumption Utilize Redshift's security for strict business requirements Apply architectural insights with analytical recipes Discover big data best practices for managed solutions Enable data sharing for data mesh and hub-and-spoke architectures Explore Redshift ML and generative AI with Amazon Q Who this book is for This book is for anyone involved in architecting, implementing, and optimizing an Amazon Redshift data warehouse, including data warehouse developers, data analysts, database administrators, data engineers, and data scientists. Basic knowledge of data warehousing, database systems, as well as cloud concepts and familiarity with Redshift is beneficial.
Guide to Security Assurance for Cloud Computing
This practical and didactic text/reference discusses the leading edge of secure cloud computing, exploring the essential concepts and principles, tools, techniques and deployment models in this field. Enlightening perspectives are presented by an international collection of pre-eminent authorities in cloud security assurance from both academia and industry. Topics and features: · Describes the important general concepts and principles of security assurance in cloud-based environments · Presents applications and approaches to cloud security that illustrate the current state of the art · Reviews pertinent issues in relation to challenges that prevent organizations moving to cloud architectures · Provides relevant theoretical frameworks and the latest empirical research findings · Discusses real-world vulnerabilities of cloud-based software in order to address the challenges of securing distributed software · Highlights the practicalities of cloud security, and how applications can assure and comply with legislation · Includes review questions at the end of each chapter This Guide to Security Assurance for Cloud Computing will be of great benefit to a broad audience covering enterprise architects, business analysts and leaders, IT infrastructure managers, cloud security engineers and consultants, and application developers involved in system design and implementation. The work is also suitable as a textbook for university instructors, with the outline for a possible course structure suggested in the preface. The editors are all members of the Computing and Mathematics Department at the University of Derby, UK, where Dr. Shao Ying Zhu serves as a Senior Lecturer in Computing, Dr. Richard Hill as a Professor and Head of the Computing and Mathematics Department, and Dr. Marcello Trovati as a Senior Lecturer in Mathematics. The other publications of the editors include the Springer titles Big-Data Analytics and Cloud Computing, Guide to Cloud Computing and Cloud Computing for Enterprise Architectures.
Emerging Challenges in Intelligent Management Information Systems
This book contains the second volume of proceedings of the ECAI 2024 Workshop on Intelligent Management Information Systems (IMIS 2024). IMIS 2024 was part of the 27th European Conference on Artificial Intelligence ECAI 2024, held in Santiago de Compostela from October 19, 2024, to October 24, 2024. The book discusses emerging challenges related to implementing artificial intelligence in management information systems. The main focus is put on knowledge management and machine learning methods in information systems, artificial intelligence for decision support systems, intelligent customer management methods, hybrid artificial intelligence, and multiple criteria decision analysis methods and advanced computational methods for support business processes and decision-making. The book is divided into three major parts covering the main issues related to the topic. The first part presents issues related to the knowledge management in intelligent information systems. The second part is devoted to application of machine learning in management information systems. The third part presents problems related to multiple criteria decision analysis and computational methods. The book has an interdisciplinary character; therefore, it is intended for a broad scope of readers, including researchers, students, managers, and employees of business organizations, software developers, IT, and management specialists.