Introducing Microsoft Azure HDInsight

Introducing Microsoft Azure HDInsight
Author: Avkash Chauhan,Valentine Fontama,Michele Hart,Wee-Hyong Tok,Buck Woody
Publsiher: Microsoft Press
Total Pages: 94
Release: 2014-06-12
ISBN: 0133965910
Category: Computers
Language: EN, FR, DE, ES & NL

Introducing Microsoft Azure HDInsight Book Excerpt:

Microsoft Azure HDInsight is Microsoft’s 100 percent compliant distribution of Apache Hadoop on Microsoft Azure. This means that standard Hadoop concepts and technologies apply, so learning the Hadoop stack helps you learn the HDInsight service. At the time of this writing, HDInsight (version 3.0) uses Hadoop version 2.2 and Hortonworks Data Platform 2.0. In Introducing Microsoft Azure HDInsight, we cover what big data really means, how you can use it to your advantage in your company or organization, and one of the services you can use to do that quickly–specifically, Microsoft’s HDInsight service. We start with an overview of big data and Hadoop, but we don’t emphasize only concepts in this book–we want you to jump in and get your hands dirty working with HDInsight in a practical way. To help you learn and even implement HDInsight right away, we focus on a specific use case that applies to almost any organization and demonstrate a process that you can follow along with. We also help you learn more. In the last chapter, we look ahead at the future of HDInsight and give you recommendations for self-learning so that you can dive deeper into important concepts and round out your education on working with big data.

Introducing Microsoft Azure Hdinsight

Introducing Microsoft Azure Hdinsight
Author: Noah A. Hooper
Publsiher: CreateSpace
Total Pages: 94
Release: 2015-08-19
ISBN: 9781516957804
Category: Electronic Book
Language: EN, FR, DE, ES & NL

Introducing Microsoft Azure Hdinsight Book Excerpt:

This updated and expanded second edition of the Introducing Microsoft Azure HDInsight provides a user-friendly introduction to the subject Taking a clear structural framework, it guides the reader through the subject's core elements. A flowing writing style combines with the use of illustrations and diagrams throughout the text to ensure the reader understands even the most complex of concepts. This succinct and enlightening overview is a required reading for all those interested in the subject . We hope you find this book useful in shaping your future career & Business.

Introducing Windows Azure for IT Professionals

Introducing Windows Azure for IT Professionals
Author: Mitch Tulloch
Publsiher: Microsoft Press
Total Pages: 148
Release: 2013-11-15
ISBN: 0735682895
Category: Computers
Language: EN, FR, DE, ES & NL

Introducing Windows Azure for IT Professionals Book Excerpt:

We’re thrilled to share another free ebook with you: Introducing Microsoft Azure HDInsight, by Avkash Chauhan, Valentine Fontama, Michele Hart, Wee Hyong Tok, and Buck Woody. Here are the download links: Download the PDF (6.37 MB; 130 pages) from http://aka.ms/IntroHDInsight/PDF Download the EPUB (8.46 MB) from http://aka.ms/IntroHDInsight/EPUB Download the MOBI (12.8 MB) from http://aka.ms/IntroHDInsight/MOBI Download the code samples (6.83 KB) from http://aka.ms/IntroHDInsight/CompContent Get a head start evaluating Windows Azure - with technical insights from a Microsoft MVP Mitch Tulloch. This guide introduces the latest features and capabilities, with scenario-based advice on how the platform can meet the needs of your business. Get the high-level overview you need to begin preparing your deployment now. Topics include: Understanding Windows Azure Windows Azure Compute Services Windows Azure Network Services Windows Azure Data Services Windows Azure App Services Getting Started with Windows Azure

Introducing Microsoft SQL Server 2014

Introducing Microsoft SQL Server 2014
Author: Ross Mistry,Stacia Misner
Publsiher: Microsoft Press
Total Pages: 144
Release: 2014-04-15
ISBN: 0133966178
Category: Computers
Language: EN, FR, DE, ES & NL

Introducing Microsoft SQL Server 2014 Book Excerpt:

NOTE: This title is also available as a free eBook on the Microsoft Download Center. It is offered for sale in print format as a convenience. Get a head start evaluating SQL Server 2014 - guided by two experts who have worked with the technology from the earliest beta. Based on Community Technology Preview 2 (CTP2) software, this guide introduces new features and capabilities, with practical insights on how SQL Server 2014 can meet the needs of your business. Get the early, high-level overview you need to begin preparing your deployment now. Coverage includes: SQL Server 2014 Editions and engine enhancements Mission-critical performance enhancements Hybrid cloud enhancements Self-service Business Intelligence enhancements in Microsoft Excel Enterprise information management enhancements Big Data solutions

Predictive Analytics with Microsoft Azure Machine Learning 2nd Edition

Predictive Analytics with Microsoft Azure Machine Learning 2nd Edition
Author: Valentine Fontama,Roger Barga,Wee Hyong Tok
Publsiher: Apress
Total Pages: 291
Release: 2015-08-26
ISBN: 1484212002
Category: Computers
Language: EN, FR, DE, ES & NL

Predictive Analytics with Microsoft Azure Machine Learning 2nd Edition Book Excerpt:

Predictive Analytics with Microsoft Azure Machine Learning, Second Edition is a practical tutorial introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book provides a thorough overview of the Microsoft Azure Machine Learning service released for general availability on February 18th, 2015 with practical guidance for building recommenders, propensity models, and churn and predictive maintenance models. The authors use task oriented descriptions and concrete end-to-end examples to ensure that the reader can immediately begin using this new service. The book describes all aspects of the service from data ingress to applying machine learning, evaluating the models, and deploying them as web services. Learn how you can quickly build and deploy sophisticated predictive models with the new Azure Machine Learning from Microsoft. What’s New in the Second Edition? Five new chapters have been added with practical detailed coverage of: Python Integration – a new feature announced February 2015 Data preparation and feature selection Data visualization with Power BI Recommendation engines Selling your models on Azure Marketplace

Predictive Analytics with Microsoft Azure Machine Learning

Predictive Analytics with Microsoft Azure Machine Learning
Author: Valentine Fontama,Roger Barga,Wee Hyong Tok
Publsiher: Apress
Total Pages: 188
Release: 2014-11-25
ISBN: 148420445X
Category: Computers
Language: EN, FR, DE, ES & NL

Predictive Analytics with Microsoft Azure Machine Learning Book Excerpt:

Data Science and Machine Learning are in high demand, as customers are increasingly looking for ways to glean insights from all their data. More customers now realize that Business Intelligence is not enough as the volume, speed and complexity of data now defy traditional analytics tools. While Business Intelligence addresses descriptive and diagnostic analysis, Data Science unlocks new opportunities through predictive and prescriptive analysis. The purpose of this book is to provide a gentle and instructionally organized introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book also provides a thorough overview of the Microsoft Azure Machine Learning service using task oriented descriptions and concrete end-to-end examples, sufficient to ensure the reader can immediately begin using this important new service. It describes all aspects of the service from data ingress to applying machine learning and evaluating the resulting model, to deploying the resulting model as a machine learning web service. Finally, this book attempts to have minimal dependencies, so that you can fairly easily pick and choose chapters to read. When dependencies do exist, they are listed at the start and end of the chapter. The simplicity of this new service from Microsoft will help to take Data Science and Machine Learning to a much broader audience than existing products in this space. Learn how you can quickly build and deploy sophisticated predictive models as machine learning web services with the new Azure Machine Learning service from Microsoft.

Introducing Microsoft SQL Server 2019

Introducing Microsoft SQL Server 2019
Author: Kellyn Gorman,Allan Hirt,Dave Noderer,Mitchell Pearson,James Rowland-Jones,Dustin Ryan,Arun Sirpal,Buck Woody
Publsiher: Packt Publishing Ltd
Total Pages: 488
Release: 2020-04-27
ISBN: 1838829822
Category: Computers
Language: EN, FR, DE, ES & NL

Introducing Microsoft SQL Server 2019 Book Excerpt:

Explore the impressive storage and analytic tools available with the in-cloud and on-premises versions of Microsoft SQL Server 2019. Key FeaturesGain insights into what’s new in SQL Server 2019Understand use cases and customer scenarios that can be implemented with SQL Server 2019Discover new cross-platform tools that simplify management and analysisBook Description Microsoft SQL Server comes equipped with industry-leading features and the best online transaction processing capabilities. If you are looking to work with data processing and management, getting up to speed with Microsoft Server 2019 is key. Introducing SQL Server 2019 takes you through the latest features in SQL Server 2019 and their importance. You will learn to unlock faster querying speeds and understand how to leverage the new and improved security features to build robust data management solutions. Further chapters will assist you with integrating, managing, and analyzing all data, including relational, NoSQL, and unstructured big data using SQL Server 2019. Dedicated sections in the book will also demonstrate how you can use SQL Server 2019 to leverage data processing platforms, such as Apache Hadoop and Spark, and containerization technologies like Docker and Kubernetes to control your data and efficiently monitor it. By the end of this book, you'll be well versed with all the features of Microsoft SQL Server 2019 and understand how to use them confidently to build robust data management solutions. What you will learnBuild a custom container image with a DockerfileDeploy and run the SQL Server 2019 container imageUnderstand how to use SQL server on LinuxMigrate existing paginated reports to Power BI Report ServerLearn to query Hadoop Distributed File System (HDFS) data using Azure Data StudioUnderstand the benefits of In-Memory OLTPWho this book is for This book is for database administrators, architects, big data engineers, or anyone who has experience with SQL Server and wants to explore and implement the new features in SQL Server 2019. Basic working knowledge of SQL Server and relational database management system (RDBMS) is required.

Big Data Analytics with Microsoft HDInsight in 24 Hours Sams Teach Yourself

Big Data Analytics with Microsoft HDInsight in 24 Hours  Sams Teach Yourself
Author: Manpreet Singh,Arshad Ali
Publsiher: Sams Publishing
Total Pages: 592
Release: 2015-11-12
ISBN: 013403533X
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Analytics with Microsoft HDInsight in 24 Hours Sams Teach Yourself Book Excerpt:

Sams Teach Yourself Big Data Analytics with Microsoft HDInsight in 24 Hours In just 24 lessons of one hour or less, Sams Teach Yourself Big Data Analytics with Microsoft HDInsight in 24 Hours helps you leverage Hadoop’s power on a flexible, scalable cloud platform using Microsoft’s newest business intelligence, visualization, and productivity tools. This book’s straightforward, step-by-step approach shows you how to provision, configure, monitor, and troubleshoot HDInsight and use Hadoop cloud services to solve real analytics problems. You’ll gain more of Hadoop’s benefits, with less complexity–even if you’re completely new to Big Data analytics. Every lesson builds on what you’ve already learned, giving you a rock-solid foundation for real-world success. Practical, hands-on examples show you how to apply what you learn Quizzes and exercises help you test your knowledge and stretch your skills Notes and tips point out shortcuts and solutions Learn how to… · Master core Big Data and NoSQL concepts, value propositions, and use cases · Work with key Hadoop features, such as HDFS2 and YARN · Quickly install, configure, and monitor Hadoop (HDInsight) clusters in the cloud · Automate provisioning, customize clusters, install additional Hadoop projects, and administer clusters · Integrate, analyze, and report with Microsoft BI and Power BI · Automate workflows for data transformation, integration, and other tasks · Use Apache HBase on HDInsight · Use Sqoop or SSIS to move data to or from HDInsight · Perform R-based statistical computing on HDInsight datasets · Accelerate analytics with Apache Spark · Run real-time analytics on high-velocity data streams · Write MapReduce, Hive, and Pig programs Register your book at informit.com/register for convenient access to downloads, updates, and corrections as they become available.

Introducing Windows Server 2016 Technical Preview

Introducing Windows Server 2016 Technical Preview
Author: John McCabe
Publsiher: Microsoft Press
Total Pages: 300
Release: 2016-05-11
ISBN: 0735697833
Category: Computers
Language: EN, FR, DE, ES & NL

Introducing Windows Server 2016 Technical Preview Book Excerpt:

Get a head start evaluating Windows Server 2016–guided by the experts. Based on Technical Preview 4, John McCabe and the Windows Server team introduce the new features and capabilities, with practical insights on how Windows Server 2016 can meet the needs of your business. Get the early, high-level overview you need to begin preparing your deployment now!

Pro Microsoft HDInsight

Pro Microsoft HDInsight
Author: Debarchan Sarkar
Publsiher: Apress
Total Pages: 272
Release: 2014-02-18
ISBN: 1430260556
Category: Computers
Language: EN, FR, DE, ES & NL

Pro Microsoft HDInsight Book Excerpt:

"The expert's voice in big data"--Cover.

Practical Recommender Systems

Practical Recommender Systems
Author: Kim Falk
Publsiher: Simon and Schuster
Total Pages: 432
Release: 2019-01-18
ISBN: 1638353980
Category: Computers
Language: EN, FR, DE, ES & NL

Practical Recommender Systems Book Excerpt:

Summary Online recommender systems help users find movies, jobs, restaurants-even romance! There's an art in combining statistics, demographics, and query terms to achieve results that will delight them. Learn to build a recommender system the right way: it can make or break your application! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Recommender systems are everywhere, helping you find everything from movies to jobs, restaurants to hospitals, even romance. Using behavioral and demographic data, these systems make predictions about what users will be most interested in at a particular time, resulting in high-quality, ordered, personalized suggestions. Recommender systems are practically a necessity for keeping your site content current, useful, and interesting to your visitors. About the Book Practical Recommender Systems explains how recommender systems work and shows how to create and apply them for your site. After covering the basics, you'll see how to collect user data and produce personalized recommendations. You'll learn how to use the most popular recommendation algorithms and see examples of them in action on sites like Amazon and Netflix. Finally, the book covers scaling problems and other issues you'll encounter as your site grows. What's inside How to collect and understand user behavior Collaborative and content-based filtering Machine learning algorithms Real-world examples in Python About the Reader Readers need intermediate programming and database skills. About the Author Kim Falk is an experienced data scientist who works daily with machine learning and recommender systems. Table of Contents PART 1 - GETTING READY FOR RECOMMENDER SYSTEMS What is a recommender? User behavior and how to collect it Monitoring the system Ratings and how to calculate them Non-personalized recommendations The user (and content) who came in from the cold PART 2 - RECOMMENDER ALGORITHMS Finding similarities among users and among content Collaborative filtering in the neighborhood Evaluating and testing your recommender Content-based filtering Finding hidden genres with matrix factorization Taking the best of all algorithms: implementing hybrid recommenders Ranking and learning to rank Future of recommender systems

Big Data Processing Using Spark in Cloud

Big Data Processing Using Spark in Cloud
Author: Mamta Mittal,Valentina E. Balas,Lalit Mohan Goyal,Raghvendra Kumar
Publsiher: Springer
Total Pages: 264
Release: 2018-06-16
ISBN: 9811305501
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Processing Using Spark in Cloud Book Excerpt:

The book describes the emergence of big data technologies and the role of Spark in the entire big data stack. It compares Spark and Hadoop and identifies the shortcomings of Hadoop that have been overcome by Spark. The book mainly focuses on the in-depth architecture of Spark and our understanding of Spark RDDs and how RDD complements big data’s immutable nature, and solves it with lazy evaluation, cacheable and type inference. It also addresses advanced topics in Spark, starting with the basics of Scala and the core Spark framework, and exploring Spark data frames, machine learning using Mllib, graph analytics using Graph X and real-time processing with Apache Kafka, AWS Kenisis, and Azure Event Hub. It then goes on to investigate Spark using PySpark and R. Focusing on the current big data stack, the book examines the interaction with current big data tools, with Spark being the core processing layer for all types of data. The book is intended for data engineers and scientists working on massive datasets and big data technologies in the cloud. In addition to industry professionals, it is helpful for aspiring data processing professionals and students working in big data processing and cloud computing environments.

Big Data and Knowledge Sharing in Virtual Organizations

Big Data and Knowledge Sharing in Virtual Organizations
Author: Gyamfi, Albert,Williams, Idongesit
Publsiher: IGI Global
Total Pages: 313
Release: 2019-01-25
ISBN: 1522575200
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data and Knowledge Sharing in Virtual Organizations Book Excerpt:

Knowledge in its pure state is tacit in nature—difficult to formalize and communicate—but can be converted into codified form and shared through both social interactions and the use of IT-based applications and systems. Even though there seems to be considerable synergies between the resulting huge data and the convertible knowledge, there is still a debate on how the increasing amount of data captured by corporations could improve decision making and foster innovation through effective knowledge-sharing practices. Big Data and Knowledge Sharing in Virtual Organizations provides innovative insights into the influence of big data analytics and artificial intelligence and the tools, methods, and techniques for knowledge-sharing processes in virtual organizations. The content within this publication examines cloud computing, machine learning, and knowledge sharing. It is designed for government officials and organizations, policymakers, academicians, researchers, technology developers, and students.

Handbook of Research on Big Data Storage and Visualization Techniques

Handbook of Research on Big Data Storage and Visualization Techniques
Author: Segall, Richard S.,Cook, Jeffrey S.
Publsiher: IGI Global
Total Pages: 917
Release: 2018-01-05
ISBN: 1522531432
Category: Computers
Language: EN, FR, DE, ES & NL

Handbook of Research on Big Data Storage and Visualization Techniques Book Excerpt:

The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject.

Building a Scalable Data Warehouse with Data Vault 2 0

Building a Scalable Data Warehouse with Data Vault 2 0
Author: Dan Linstedt,Michael Olschimke
Publsiher: Morgan Kaufmann
Total Pages: 684
Release: 2015-09-15
ISBN: 0128026480
Category: Computers
Language: EN, FR, DE, ES & NL

Building a Scalable Data Warehouse with Data Vault 2 0 Book Excerpt:

The Data Vault was invented by Dan Linstedt at the U.S. Department of Defense, and the standard has been successfully applied to data warehousing projects at organizations of different sizes, from small to large-size corporations. Due to its simplified design, which is adapted from nature, the Data Vault 2.0 standard helps prevent typical data warehousing failures. "Building a Scalable Data Warehouse" covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss: How to load each layer using SQL Server Integration Services (SSIS), including automation of the Data Vault loading processes. Important data warehouse technologies and practices. Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture. Provides a complete introduction to data warehousing, applications, and the business context so readers can get-up and running fast Explains theoretical concepts and provides hands-on instruction on how to build and implement a data warehouse Demystifies data vault modeling with beginning, intermediate, and advanced techniques Discusses the advantages of the data vault approach over other techniques, also including the latest updates to Data Vault 2.0 and multiple improvements to Data Vault 1.0

Architecting the Industrial Internet

Architecting the Industrial Internet
Author: Shyam Nath,Robert Stackowiak,Carla Romano
Publsiher: Packt Publishing Ltd
Total Pages: 360
Release: 2017-09-22
ISBN: 1787283747
Category: Computers
Language: EN, FR, DE, ES & NL

Architecting the Industrial Internet Book Excerpt:

Learn the ins and outs of the Industrial Internet of Things through subjects ranging from its history and evolution, right up to what the future holds. About This Book Define solutions that can connect existing systems and newer cloud-based solutions to thousands of thousands of edge devices and industrial machines Identify, define, and justify Industrial Internet of Things (IIoT) projects, and design an application that can connect to and control thousands of machines Leverage the power and features of a platform to monitor, perform analytics, and maintain the Industrial Internet Who This Book Is For Architects who are interested in learning how to define solutions for the Industrial Internet will benefit immensely from this book. Relevant architect roles include enterprise architects, business architects, information architects, cloud solution architects, software architects, and others. The content is also relevant for technically inclined line of business leaders investing in these solutions. What You Will Learn Learn the history of the Industrial Internet and why an architectural approach is needed Define solutions that can connect to and control thousands of edge devices and machines Understand the significance of working with line of business leadership and key metrics to be gathered Connect business requirements to the functional architecture Gain the right expectation as to the capabilities of Industrial Internet applications and how to assess them Understand what data and analytics components should be included in your architecture solution Understand deployment trade-offs, management and security considerations, and the impact of emerging technologies In Detail The Industrial Internet or the IIoT has gained a lot of traction. Many leading companies are driving this revolution by connecting smart edge devices to cloud-based analysis platforms and solving their business challenges in new ways. To ensure a smooth integration of such machines and devices, sound architecture strategies based on accepted principles, best practices, and lessons learned must be applied. This book begins by providing a bird's eye view of what the IIoT is and how the industrial revolution has evolved into embracing this technology. It then describes architectural approaches for success, gathering business requirements, and mapping requirements into functional solutions. In a later chapter, many other potential use cases are introduced including those in manufacturing and specific examples in predictive maintenance, asset tracking and handling, and environmental impact and abatement. The book concludes by exploring evolving technologies that will impact IIoT architecture in the future and discusses possible societal implications of the Industrial Internet and perceptions regarding these projects. By the end of this book, you will be better equipped to embrace the benefits of the burgeoning IIoT. Style and approach This book takes a comprehensive approach to the Industrial Internet, thoroughly acquainting the reader with the concepts and philosophy of the IIoT. It provides a basis for defining an IIoT solution in a thoughtful manner and creating what will be viewed as a successful project.

Data Intensive Industrial Asset Management

Data Intensive Industrial Asset Management
Author: Farhad Balali,Jessie Nouri,Adel Nasiri,Tian Zhao
Publsiher: Springer Nature
Total Pages: 236
Release: 2020-01-22
ISBN: 3030359301
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Data Intensive Industrial Asset Management Book Excerpt:

This book presents a step by step Asset Health Management Optimization Approach Using Internet of Things (IoT). The authors provide a comprehensive study which includes the descriptive, diagnostic, predictive, and prescriptive analysis in detail. The presentation focuses on the challenges of the parameter selection, statistical data analysis, predictive algorithms, big data storage and selection, data pattern recognition, machine learning techniques, asset failure distribution estimation, reliability and availability enhancement, condition based maintenance policy, failure detection, data driven optimization algorithm, and a multi-objective optimization approach, all of which can significantly enhance the reliability and availability of the system.

Data Lakehouse in Action

Data Lakehouse in Action
Author: Pradeep Menon
Publsiher: Packt Publishing Ltd
Total Pages: 206
Release: 2022-03-17
ISBN: 1801815100
Category: Computers
Language: EN, FR, DE, ES & NL

Data Lakehouse in Action Book Excerpt:

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.

Encyclopedia of Cloud Computing

Encyclopedia of Cloud Computing
Author: San Murugesan,Irena Bojanova
Publsiher: John Wiley & Sons
Total Pages: 744
Release: 2016-08-01
ISBN: 1118821971
Category: Computers
Language: EN, FR, DE, ES & NL

Encyclopedia of Cloud Computing Book Excerpt:

The Encyclopedia of Cloud Computing comprehensively cover all aspects of cloud computing. It provides IT professionals, educators, researchers and students a compendium of cloud computing knowledge – concepts, principles, architecture, technology, security, privacy and regulatory compliance, applications, adoption, business, and social and legal aspects. Containing contributions from a spectrum of subject matter experts in industry and academia, this unique publication also addresses questions related to technological trends and developments, research opportunities, best practices, standards, and cloud adoption that stakeholders might have in the context of development, operation, management, and use of clouds, providing multiple perspectives. Furthermore, itexamines cloud computing's impact now and in the future. The encyclopedia is logically organised into 10 sections amd each section into a maximum of 12 chapters, each covering a major topic/area with cross-references as required. The chapters consist of tables, illustrations, side-bars as appropriate. In additon, it also includes highlights at the beginning of each chapter, as well as backend material references and additional resources for further information (including relevant websites, videos and software tools). The encyclopedia also contains illustrations and case studies. A list of acronyms are provided in the beginning and a comprehensive and informative glossary at the end.

Introduction to Machine Learning in the Cloud with Python

Introduction to Machine Learning in the Cloud with Python
Author: Pramod Gupta,Naresh K. Sehgal
Publsiher: Springer Nature
Total Pages: 284
Release: 2021-04-28
ISBN: 3030712702
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Introduction to Machine Learning in the Cloud with Python Book Excerpt:

This book provides an introduction to machine learning and cloud computing, both from a conceptual level, along with their usage with underlying infrastructure. The authors emphasize fundamentals and best practices for using AI and ML in a dynamic infrastructure with cloud computing and high security, preparing readers to select and make use of appropriate techniques. Important topics are demonstrated using real applications and case studies.