Modern Data Systems
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Security Privacy And Trust In Modern Data Management
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Author : Milan Petkovic
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-06-12
Security Privacy And Trust In Modern Data Management written by Milan Petkovic and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-12 with Computers categories.
The vision of ubiquitous computing and ambient intelligence describes a world of technology which is present anywhere, anytime in the form of smart, sensible devices that communicate with each other and provide personalized services. However, open interconnected systems are much more vulnerable to attacks and unauthorized data access. In the context of this threat, this book provides a comprehensive guide to security and privacy and trust in data management.
Modern Data Strategy
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Author : Mike Fleckenstein
language : en
Publisher: Springer
Release Date : 2018-02-12
Modern Data Strategy written by Mike Fleckenstein and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-12 with Computers categories.
This book contains practical steps business users can take to implement data management in a number of ways, including data governance, data architecture, master data management, business intelligence, and others. It defines data strategy, and covers chapters that illustrate how to align a data strategy with the business strategy, a discussion on valuing data as an asset, the evolution of data management, and who should oversee a data strategy. This provides the user with a good understanding of what a data strategy is and its limits. Critical to a data strategy is the incorporation of one or more data management domains. Chapters on key data management domains—data governance, data architecture, master data management and analytics, offer the user a practical approach to data management execution within a data strategy. The intent is to enable the user to identify how execution on one or more data management domains can help solve business issues. This book is intended for business users who work with data, who need to manage one or more aspects of the organization’s data, and who want to foster an integrated approach for how enterprise data is managed. This book is also an excellent reference for students studying computer science and business management or simply for someone who has been tasked with starting or improving existing data management.
Designing Big Data Platforms
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Author : Yusuf Aytas
language : en
Publisher: John Wiley & Sons
Release Date : 2021-07-08
Designing Big Data Platforms written by Yusuf Aytas and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-08 with Mathematics categories.
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.
Architecting Modern Data Platforms
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Author : Jan Kunigk
language : en
Publisher: O'Reilly Media
Release Date : 2018
Architecting Modern Data Platforms written by Jan Kunigk and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Apache Hadoop categories.
There's a lot of information about big data technologies, but splicing these technologies into an end-to-end enterprise data platform is a daunting task not widely covered. With this practical book, you'll learn how to build big data infrastructure both on-premises and in the cloud and successfully architect a modern data platform. Ideal for enterprise architects, IT managers, application architects, and data engineers, this book shows you how to overcome the many challenges that emerge during Hadoop projects. You'll explore the vast landscape of tools available in the Hadoop and big data realm in a thorough technical primer before diving into: Infrastructure: Look at all component layers in a modern data platform, from the server to the data center, to establish a solid foundation for data in your enterprise Platform: Understand aspects of deployment, operation, security, high availability, and disaster recovery, along with everything you need to know to integrate your platform with the rest of your enterprise IT Taking Hadoop to the cloud: Learn the important architectural aspects of running a big data platform in the cloud while maintaining enterprise security and high availability
Designing Data Intensive Applications
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Author : Martin Kleppmann
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-03-16
Designing Data Intensive Applications written by Martin Kleppmann and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-16 with Computers categories.
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures
Modern Data Protection
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Author : W. Curtis Preston
language : en
Publisher: O'Reilly Media
Release Date : 2021-06-30
Modern Data Protection written by W. Curtis Preston and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-30 with categories.
Give your organization the data protection it deserves, without the uncertainty and cost overruns experienced by your predecessors or other companies. System and network administrators today have their work cut out for them to protect physical and virtual machines in the data center and the cloud, mobile devices including laptops and tablets, SaaS services like Microsoft 365, Google Workspace, and Salesforce, and any persistent data created by Kubernetes and container workloads. To help you navigate the breadth and depth of this challenge, this book presents several solutions so you can determine which one is right for your company. You'll learn the unique requirements that each workload presents, then explore various categories of commercial backup hardware, software, and services available to protect these data sources, including the advantages and disadvantages of each approach. Learn the workload types that your organization should be backing up Explore the hardware, software, and services you can use to back up your systems Understand what's wrong with your current data protection system Pair your backed-up workloads to the appropriate backup system Learn the adjustments you need to make to make your backups better, without wasting money
Database Internals
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Author : Alex Petrov
language : en
Publisher: O'Reilly Media
Release Date : 2019-09-13
Database Internals written by Alex Petrov and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-13 with Computers categories.
When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it’s often difficult to understand what each one offers and how they differ. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals. Throughout the book, you’ll explore relevant material gleaned from numerous books, papers, blog posts, and the source code of several open source databases. These resources are listed at the end of parts one and two. You’ll discover that the most significant distinctions among many modern databases reside in subsystems that determine how storage is organized and how data is distributed. This book examines: Storage engines: Explore storage classification and taxonomy, and dive into B-Tree-based and immutable Log Structured storage engines, with differences and use-cases for each Storage building blocks: Learn how database files are organized to build efficient storage, using auxiliary data structures such as Page Cache, Buffer Pool and Write-Ahead Log Distributed systems: Learn step-by-step how nodes and processes connect and build complex communication patterns Database clusters: Which consistency models are commonly used by modern databases and how distributed storage systems achieve consistency
Spring Data
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Author : Mark Pollack
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2012-10-12
Spring Data written by Mark Pollack and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-12 with Computers categories.
You can choose several data access frameworks when building Java enterprise applications that work with relational databases. But what about big data? This hands-on introduction shows you how Spring Data makes it relatively easy to build applications across a wide range of new data access technologies such as NoSQL and Hadoop. Through several sample projects, you’ll learn how Spring Data provides a consistent programming model that retains NoSQL-specific features and capabilities, and helps you develop Hadoop applications across a wide range of use-cases such as data analysis, event stream processing, and workflow. You’ll also discover the features Spring Data adds to Spring’s existing JPA and JDBC support for writing RDBMS-based data access layers. Learn about Spring’s template helper classes to simplify the use ofdatabase-specific functionality Explore Spring Data’s repository abstraction and advanced query functionality Use Spring Data with Redis (key/value store), HBase(column-family), MongoDB (document database), and Neo4j (graph database) Discover the GemFire distributed data grid solution Export Spring Data JPA-managed entities to the Web as RESTful web services Simplify the development of HBase applications, using a lightweight object-mapping framework Build example big-data pipelines with Spring Batch and Spring Integration
Data Lakehouse In Action
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Author : Pradeep Menon
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-03-17
Data Lakehouse In Action written by Pradeep Menon and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-17 with Computers categories.
Propose a new scalable data architecture paradigm, Data Lakehouse, that addresses the limitations of current data architecture patterns Key FeaturesUnderstand how data is ingested, stored, served, governed, and secured for enabling data analyticsExplore a practical way to implement Data Lakehouse using cloud computing platforms like AzureCombine multiple architectural patterns based on an organization's needs and maturity levelBook Description The Data Lakehouse architecture is a new paradigm that enables large-scale analytics. This book will guide you in developing data architecture in the right way to ensure your organization's success. The first part of the book discusses the different data architectural patterns used in the past and the need for a new architectural paradigm, as well as the drivers that have caused this change. It covers the principles that govern the target architecture, the components that form the Data Lakehouse architecture, and the rationale and need for those components. The second part deep dives into the different layers of Data Lakehouse. It covers various scenarios and components for data ingestion, storage, data processing, data serving, analytics, governance, and data security. The book's third part focuses on the practical implementation of the Data Lakehouse architecture in a cloud computing platform. It focuses on various ways to combine the Data Lakehouse pattern to realize macro-patterns, such as Data Mesh and Data Hub-Spoke, based on the organization's needs and maturity level. The frameworks introduced will be practical and organizations can readily benefit from their application. By the end of this book, you'll clearly understand how to implement the Data Lakehouse architecture pattern in a scalable, agile, and cost-effective manner. What you will learnUnderstand the evolution of the Data Architecture patterns for analyticsBecome well versed in the Data Lakehouse pattern and how it enables data analyticsFocus on methods to ingest, process, store, and govern data in a Data Lakehouse architectureLearn techniques to serve data and perform analytics in a Data Lakehouse architectureCover methods to secure the data in a Data Lakehouse architectureImplement Data Lakehouse in a cloud computing platform such as AzureCombine Data Lakehouse in a macro-architecture pattern such as Data MeshWho this book is for This book is for data architects, big data engineers, data strategists and practitioners, data stewards, and cloud computing practitioners looking to become well-versed with modern data architecture patterns to enable large-scale analytics. Basic knowledge of data architecture and familiarity with data warehousing concepts are required.
Data Driven Science And Engineering
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Author : Steven L. Brunton
language : en
Publisher: Cambridge University Press
Release Date : 2022-05-05
Data Driven Science And Engineering written by Steven L. Brunton and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-05 with Computers categories.
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.