Rise Of The Data Cloud
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Rise Of The Data Cloud
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Author : Frank Slootman
language : en
Publisher: AuthorHouse
Release Date : 2020-12-18
Rise Of The Data Cloud written by Frank Slootman and has been published by AuthorHouse this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-18 with Business & Economics categories.
The rise of the Data Cloud is ushering in a new era of computing. The world’s digital data is mass migrating to the cloud, where it can be more effectively integrated, managed, and mobilized. The data cloud eliminates data siloes and enables data sharing with business partners, capitalizing on data network effects. It democratizes data analytics, making the most sophisticated data science tools accessible to organizations of all sizes. Data exchanges enable businesses to discover, explore, and easily purchase or sell data—opening up new revenue streams. Business leaders have long dreamed of data driving their organizations. Now, thanks to the Data Cloud, nothing stands in their way.
To The Cloud
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Author : Vincent Mosco
language : en
Publisher: Routledge
Release Date : 2015-11-17
To The Cloud written by Vincent Mosco and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-17 with Political Science categories.
Cloud computing and big data are arguably the most significant forces in information technology today. In the wake of revelations about National Security Agency (NSA) activities, many of which occur "in the cloud", this book offers both enlightenment and a critical view. Vincent Mosco explores where the cloud originated, what it means, and how important it is for business, government and citizens. He describes the intense competition among cloud companies like Amazon and Google, the spread of the cloud to government agencies like the controversial NSA, and the astounding growth of entire cloud cities in China. Is the cloud the long-promised information utility that will solve many of the world's economic and social problems? Or is it just marketing hype? To the Cloud provides the first thorough analysis of the potential and the problems of a technology that may very well disrupt the world.
Continued Rise Of The Cloud
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Author : Zaigham Mahmood
language : en
Publisher: Springer
Release Date : 2014-07-07
Continued Rise Of The Cloud written by Zaigham Mahmood and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-07 with Computers categories.
This book captures the state of the art in cloud technologies, infrastructures, and service delivery and deployment models. The work provides guidance and case studies on the development of cloud-based services and infrastructures from an international selection of expert researchers and practitioners. Features: presents a focus on security and access control mechanisms for cloud environments, analyses standards and brokerage services, and investigates the role of certification for cloud adoption; evaluates cloud ERP, suggests a framework for implementing “big data” science, and proposes an approach for cloud interoperability; reviews existing elasticity management solutions, discusses the relationship between cloud management and governance, and describes the development of a cloud service capability assessment model; examines cloud applications in higher education, including the use of knowledge-as-a-service in the provision of education, and cloud-based e-learning for students with disabilities.
Jumpstart Snowflake
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Author : Dmitry Anoshin
language : en
Publisher: Apress
Release Date : 2019-12-20
Jumpstart Snowflake written by Dmitry Anoshin and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-20 with Computers categories.
Explore the modern market of data analytics platforms and the benefits of using Snowflake computing, the data warehouse built for the cloud. With the rise of cloud technologies, organizations prefer to deploy their analytics using cloud providers such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform. Cloud vendors are offering modern data platforms for building cloud analytics solutions to collect data and consolidate into single storage solutions that provide insights for business users. The core of any analytics framework is the data warehouse, and previously customers did not have many choices of platform to use. Snowflake was built specifically for the cloud and it is a true game changer for the analytics market. This book will help onboard you to Snowflake, present best practices to deploy, and use the Snowflake data warehouse. In addition, it covers modern analytics architecture and use cases. It provides use cases of integration with leading analytics software such as Matillion ETL, Tableau, and Databricks. Finally, it covers migration scenarios for on-premise legacy data warehouses. What You Will Learn Know the key functionalities of Snowflake Set up security and access with cluster Bulk load data into Snowflake using the COPY command Migrate from a legacy data warehouse to Snowflake integrate the Snowflake data platform with modern business intelligence (BI) and data integration tools Who This Book Is For Those working with data warehouse and business intelligence (BI) technologies, and existing and potential Snowflake users
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 Cloud For Beginners
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Author : Caroyln Lando
language : en
Publisher: Independently Published
Release Date : 2021-03
Data Cloud For Beginners written by Caroyln Lando and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03 with categories.
Over 400 million SaaS data sets remained siloed globally, isolated in cloud data storage and on-premise data centers. The Data Cloud eliminates these silos, allowing you to seamlessly unify, analyze, share, and even monetize your data This Data Cloud Information book will give you an understanding of what we've built to help you create a business with data as its most robust foundation. Snowflake delivers the Data Cloud -- a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Inside the Data Cloud, organizations unite their siloes of data, easily discover and securely share governed data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single and seamless experience across multiple public clouds, helping power the data economy. Snowflake's platform is the engine that powers and provides access to the Data Cloud, creating a solution for data warehousing, data lakes, data engineering, data science, data application development, and data sharing.
Critical Research On Scalability And Security Issues In Virtual Cloud Environments
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Author : Aljawarneh, Shadi
language : en
Publisher: IGI Global
Release Date : 2017-12-30
Critical Research On Scalability And Security Issues In Virtual Cloud Environments written by Aljawarneh, Shadi and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-30 with Computers categories.
Individual users and business organizations are shifting their data storage and utilizing cloud computing because of its easy availability and reduced costs. Although, this technology is creating an easy way to store, share, and access data, serious security concerns have been generated. Critical Research on Scalability and Security Issues in Virtual Cloud Environments is a critical scholarly resource that examines the concept of cloud computing and explores the various shortcomings of using the cloud. Featuring coverage on a broad range of topics such as cloud architecture for scalability, data vulnerability, and server virtualization management, this book is geared towards academicians, practitioners, and researchers seeking current research on developing effective security measures for cloud paradigm.
Designing Cloud Data Platforms
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Author : Danil Zburivsky
language : en
Publisher: Simon and Schuster
Release Date : 2021-03-17
Designing Cloud Data Platforms written by Danil Zburivsky and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-17 with Computers categories.
In Designing Cloud Data Platforms, Danil Zburivsky and Lynda Partner reveal a six-layer approach that increases flexibility and reduces costs. Discover patterns for ingesting data from a variety of sources, then learn to harness pre-built services provided by cloud vendors. Summary Centralized data warehouses, the long-time defacto standard for housing data for analytics, are rapidly giving way to multi-faceted cloud data platforms. Companies that embrace modern cloud data platforms benefit from an integrated view of their business using all of their data and can take advantage of advanced analytic practices to drive predictions and as yet unimagined data services. Designing Cloud Data Platforms is a hands-on guide to envisioning and designing a modern scalable data platform that takes full advantage of the flexibility of the cloud. As you read, you’ll learn the core components of a cloud data platform design, along with the role of key technologies like Spark and Kafka Streams. You’ll also explore setting up processes to manage cloud-based data, keep it secure, and using advanced analytic and BI tools to analyze it. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Well-designed pipelines, storage systems, and APIs eliminate the complicated scaling and maintenance required with on-prem data centers. Once you learn the patterns for designing cloud data platforms, you’ll maximize performance no matter which cloud vendor you use. About the book In Designing Cloud Data Platforms, Danil Zburivsky and Lynda Partner reveal a six-layer approach that increases flexibility and reduces costs. Discover patterns for ingesting data from a variety of sources, then learn to harness pre-built services provided by cloud vendors. What's inside Best practices for structured and unstructured data sets Cloud-ready machine learning tools Metadata and real-time analytics Defensive architecture, access, and security About the reader For data professionals familiar with the basics of cloud computing, and Hadoop or Spark. About the author Danil Zburivsky has over 10 years of experience designing and supporting large-scale data infrastructure for enterprises across the globe. Lynda Partner is the VP of Analytics-as-a-Service at Pythian, and has been on the business side of data for over 20 years. Table of Contents 1 Introducing the data platform 2 Why a data platform and not just a data warehouse 3 Getting bigger and leveraging the Big 3: Amazon, Microsoft Azure, and Google 4 Getting data into the platform 5 Organizing and processing data 6 Real-time data processing and analytics 7 Metadata layer architecture 8 Schema management 9 Data access and security 10 Fueling business value with data platforms
The Rise Of Big Spatial Data
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Author : Igor Ivan
language : en
Publisher: Springer
Release Date : 2016-10-14
The Rise Of Big Spatial Data written by Igor Ivan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-14 with Science categories.
This edited volume gathers the proceedings of the Symposium GIS Ostrava 2016, the Rise of Big Spatial Data, held at the Technical University of Ostrava, Czech Republic, March 16–18, 2016. Combining theoretical papers and applications by authors from around the globe, it summarises the latest research findings in the area of big spatial data and key problems related to its utilisation. Welcome to dawn of the big data era: though it’s in sight, it isn’t quite here yet. Big spatial data is characterised by three main features: volume beyond the limit of usual geo-processing, velocity higher than that available using conventional processes, and variety, combining more diverse geodata sources than usual. The popular term denotes a situation in which one or more of these key properties reaches a point at which traditional methods for geodata collection, storage, processing, control, analysis, modelling, validation and visualisation fail to provide effective solutions. >Entering the era of big spatial data calls for finding solutions that address all “small data” issues that soon create “big data” troubles. Resilience for big spatial data means solving the heterogeneity of spatial data sources (in topics, purpose, completeness, guarantee, licensing, coverage etc.), large volumes (from gigabytes to terabytes and more), undue complexity of geo-applications and systems (i.e. combination of standalone applications with web services, mobile platforms and sensor networks), neglected automation of geodata preparation (i.e. harmonisation, fusion), insufficient control of geodata collection and distribution processes (i.e. scarcity and poor quality of metadata and metadata systems), limited analytical tool capacity (i.e. domination of traditional causal-driven analysis), low visual system performance, inefficient knowledge-discovery techniques (for transformation of vast amounts of information into tiny and essential outputs) and much more. These trends are accelerating as sensors become more ubiquitous around the world.
Reliability Assurance Of Big Data In The Cloud
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Author : Yun Yang
language : en
Publisher: Morgan Kaufmann
Release Date : 2014-12-09
Reliability Assurance Of Big Data In The Cloud written by Yun Yang and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-09 with Computers categories.
With the rapid growth of Cloud computing, the size of Cloud data is expanding at a dramatic speed. A huge amount of data is generated and processed by Cloud applications, putting a higher demand on cloud storage. While data reliability should already be a requirement, data in the Cloud needs to be stored in a highly cost-effective manner. This book focuses on the trade-off between data storage cost and data reliability assurance for big data in the Cloud. Throughout the whole Cloud data lifecycle, four major features are presented: first, a novel generic data reliability model for describing data reliability in the Cloud; second, a minimum replication calculation approach for meeting a given data reliability requirement to facilitate data creation; third, a novel cost-effective data reliability assurance mechanism for big data maintenance, which could dramatically reduce the storage space needed in the Cloud; fourth, a cost-effective strategy for facilitating data creation and recovery, which could significantly reduce the energy consumption during data transfer. Captures data reliability with variable disk rates and compares virtual to physical disks Offers methods for reducing cloud-based storage cost and energy consumption Presents a minimum replication benchmark for data reliability requirements to evaluate various replication-based data storage approaches