Microsoft Big Data Solutions

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Microsoft Big Data Solutions

Author : Adam Jorgensen
Publisher : John Wiley & Sons
ISBN 13 : 1118729552
Total Pages : 408 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Microsoft Big Data Solutions by : Adam Jorgensen

Download or read book Microsoft Big Data Solutions written by Adam Jorgensen and published by John Wiley & Sons. This book was released on 2014-02-24 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tap the power of Big Data with Microsoft technologies Big Data is here, and Microsoft's new Big Data platform is a valuable tool to help your company get the very most out of it. This timely book shows you how to use HDInsight along with HortonWorks Data Platform for Windows to store, manage, analyze, and share Big Data throughout the enterprise. Focusing primarily on Microsoft and HortonWorks technologies but also covering open source tools, Microsoft Big Data Solutions explains best practices, covers on-premises and cloud-based solutions, and features valuable case studies. Best of all, it helps you integrate these new solutions with technologies you already know, such as SQL Server and Hadoop. Walks you through how to integrate Big Data solutions in your company using Microsoft's HDInsight Server, HortonWorks Data Platform for Windows, and open source tools Explores both on-premises and cloud-based solutions Shows how to store, manage, analyze, and share Big Data through the enterprise Covers topics such as Microsoft's approach to Big Data, installing and configuring HortonWorks Data Platform for Windows, integrating Big Data with SQL Server, visualizing data with Microsoft and HortonWorks BI tools, and more Helps you build and execute a Big Data plan Includes contributions from the Microsoft and HortonWorks Big Data product teams If you need a detailed roadmap for designing and implementing a fully deployed Big Data solution, you'll want Microsoft Big Data Solutions.

Microsoft Azure Data Solutions - An Introduction

Author : Daniel A. Seara
Publisher : Microsoft Press
ISBN 13 : 0137252528
Total Pages : 634 pages
Book Rating : 4.1/5 (372 download)

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Book Synopsis Microsoft Azure Data Solutions - An Introduction by : Daniel A. Seara

Download or read book Microsoft Azure Data Solutions - An Introduction written by Daniel A. Seara and published by Microsoft Press. This book was released on 2021-07-14 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover and apply the Azure platform's most powerful data solutions Cloud technologies are advancing at an accelerating pace, supplanting traditional relational and data warehouse storage solutions with novel, high-value alternatives. Now, three pioneering Azure Data consultants offer an expert introduction to the relational, non-relational, and data warehouse solutions offered by the Azure platform. Drawing on their extensive experience helping organizations get more value from the Microsoft Data Platform, the authors guide you through decision-making, implementation, operations, security, and more. Throughout, step-by-step tutorials and hands-on exercises prepare you to succeed, even if you have no cloud data experience. Three leading experts in Microsoft Azure Data Solutions show how to: Master essential concepts of data storage and processing in cloud environments Handle the changing responsibilities of data engineers moving to the cloud Get started with Azure data storage accounts and other data facilities Walk through implementing relational and non-relational data stores in Azure Secure data using the least-permissions principle, Azure Active Directory, role-based access control, and other methods Develop efficient Azure batch processing and streaming solutions Monitor Azure SQL databases, blob storage, data lakes, Azure Synapse Analytics, and Cosmos DB Optimize Azure data solutions by solving problems with storage, management, and service interactions About This Book For data engineers, systems engineers, IT managers, developers, database administrators, cloud architects, and other IT professionals Requires little or no knowledge about Azure tools and services for data analysis

Data Lake Analytics on Microsoft Azure

Author : Harsh Chawla
Publisher : Apress
ISBN 13 : 9781484262511
Total Pages : 228 pages
Book Rating : 4.2/5 (625 download)

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Book Synopsis Data Lake Analytics on Microsoft Azure by : Harsh Chawla

Download or read book Data Lake Analytics on Microsoft Azure written by Harsh Chawla and published by Apress. This book was released on 2020-11-15 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get a 360-degree view of how the journey of data analytics solutions has evolved from monolithic data stores and enterprise data warehouses to data lakes and modern data warehouses. You will This book includes comprehensive coverage of how: To architect data lake analytics solutions by choosing suitable technologies available on Microsoft Azure The advent of microservices applications covering ecommerce or modern solutions built on IoT and how real-time streaming data has completely disrupted this ecosystem These data analytics solutions have been transformed from solely understanding the trends from historical data to building predictions by infusing machine learning technologies into the solutions Data platform professionals who have been working on relational data stores, non-relational data stores, and big data technologies will find the content in this book useful. The book also can help you start your journey into the data engineer world as it provides an overview of advanced data analytics and touches on data science concepts and various artificial intelligence and machine learning technologies available on Microsoft Azure. What Will You Learn You will understand the: Concepts of data lake analytics, the modern data warehouse, and advanced data analytics Architecture patterns of the modern data warehouse and advanced data analytics solutions Phases—such as Data Ingestion, Store, Prep and Train, and Model and Serve—of data analytics solutions and technology choices available on Azure under each phase In-depth coverage of real-time and batch mode data analytics solutions architecture Various managed services available on Azure such as Synapse analytics, event hubs, Stream analytics, CosmosDB, and managed Hadoop services such as Databricks and HDInsight Who This Book Is For Data platform professionals, database architects, engineers, and solution architects

Designing Distributed Systems

Author : Brendan Burns
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491983612
Total Pages : 164 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Designing Distributed Systems by : Brendan Burns

Download or read book Designing Distributed Systems written by Brendan Burns and published by "O'Reilly Media, Inc.". This book was released on 2018-02-20 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: Without established design patterns to guide them, developers have had to build distributed systems from scratch, and most of these systems are very unique indeed. Today, the increasing use of containers has paved the way for core distributed system patterns and reusable containerized components. This practical guide presents a collection of repeatable, generic patterns to help make the development of reliable distributed systems far more approachable and efficient. Author Brendan Burns—Director of Engineering at Microsoft Azure—demonstrates how you can adapt existing software design patterns for designing and building reliable distributed applications. Systems engineers and application developers will learn how these long-established patterns provide a common language and framework for dramatically increasing the quality of your system. Understand how patterns and reusable components enable the rapid development of reliable distributed systems Use the side-car, adapter, and ambassador patterns to split your application into a group of containers on a single machine Explore loosely coupled multi-node distributed patterns for replication, scaling, and communication between the components Learn distributed system patterns for large-scale batch data processing covering work-queues, event-based processing, and coordinated workflows

Mastering Azure Analytics

Author : Zoiner Tejada
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491956607
Total Pages : 461 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Mastering Azure Analytics by : Zoiner Tejada

Download or read book Mastering Azure Analytics written by Zoiner Tejada and published by "O'Reilly Media, Inc.". This book was released on 2017-04-06 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: Microsoft Azure has over 20 platform-as-a-service (PaaS) offerings that can act in support of a big data analytics solution. So which one is right for your project? This practical book helps you understand the breadth of Azure services by organizing them into a reference framework you can use when crafting your own big data analytics solution. You’ll not only be able to determine which service best fits the job, but also learn how to implement a complete solution that scales, provides human fault tolerance, and supports future needs. Understand the fundamental patterns of the data lake and lambda architecture Recognize the canonical steps in the analytics data pipeline and learn how to use Azure Data Factory to orchestrate them Implement data lakes and lambda architectures, using Azure Data Lake Store, Data Lake Analytics, HDInsight (including Spark), Stream Analytics, SQL Data Warehouse, and Event Hubs Understand where Azure Machine Learning fits into your analytics pipeline Gain experience using these services on real-world data that has real-world problems, with scenarios ranging from aviation to Internet of Things (IoT)

Data Engineering on Azure

Author : Vlad Riscutia
Publisher : Simon and Schuster
ISBN 13 : 1617298921
Total Pages : 334 pages
Book Rating : 4.6/5 (172 download)

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Book Synopsis Data Engineering on Azure by : Vlad Riscutia

Download or read book Data Engineering on Azure written by Vlad Riscutia and published by Simon and Schuster. This book was released on 2021-08-17 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build a data platform to the industry-leading standards set by Microsoft’s own infrastructure. Summary In Data Engineering on Azure you will learn how to: Pick the right Azure services for different data scenarios Manage data inventory Implement production quality data modeling, analytics, and machine learning workloads Handle data governance Using DevOps to increase reliability Ingesting, storing, and distributing data Apply best practices for compliance and access control Data Engineering on Azure reveals the data management patterns and techniques that support Microsoft’s own massive data infrastructure. Author Vlad Riscutia, a data engineer at Microsoft, teaches you to bring an engineering rigor to your data platform and ensure that your data prototypes function just as well under the pressures of production. You'll implement common data modeling patterns, stand up cloud-native data platforms on Azure, and get to grips with DevOps for both analytics and machine learning. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Build secure, stable data platforms that can scale to loads of any size. When a project moves from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement cloud-based data infrastructure that you can easily monitor, scale, and modify. About the book In Data Engineering on Azure you’ll learn the skills you need to build and maintain big data platforms in massive enterprises. This invaluable guide includes clear, practical guidance for setting up infrastructure, orchestration, workloads, and governance. As you go, you’ll set up efficient machine learning pipelines, and then master time-saving automation and DevOps solutions. The Azure-based examples are easy to reproduce on other cloud platforms. What's inside Data inventory and data governance Assure data quality, compliance, and distribution Build automated pipelines to increase reliability Ingest, store, and distribute data Production-quality data modeling, analytics, and machine learning About the reader For data engineers familiar with cloud computing and DevOps. About the author Vlad Riscutia is a software architect at Microsoft. Table of Contents 1 Introduction PART 1 INFRASTRUCTURE 2 Storage 3 DevOps 4 Orchestration PART 2 WORKLOADS 5 Processing 6 Analytics 7 Machine learning PART 3 GOVERNANCE 8 Metadata 9 Data quality 10 Compliance 11 Distributing data

Microsoft Azure Essentials Azure Machine Learning

Author : Jeff Barnes
Publisher : Microsoft Press
ISBN 13 : 073569818X
Total Pages : 393 pages
Book Rating : 4.7/5 (356 download)

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Book Synopsis Microsoft Azure Essentials Azure Machine Learning by : Jeff Barnes

Download or read book Microsoft Azure Essentials Azure Machine Learning written by Jeff Barnes and published by Microsoft Press. This book was released on 2015-04-25 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure. This third ebook in the series introduces Microsoft Azure Machine Learning, a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services. The ebook presents an overview of modern data science theory and principles, the associated workflow, and then covers some of the more common machine learning algorithms in use today. It builds a variety of predictive analytics models using real world data, evaluates several different machine learning algorithms and modeling strategies, and then deploys the finished models as machine learning web services on Azure within a matter of minutes. The ebook also expands on a working Azure Machine Learning predictive model example to explore the types of client and server applications you can create to consume Azure Machine Learning web services. Watch Microsoft Press’s blog and Twitter (@MicrosoftPress) to learn about other free ebooks in the Microsoft Azure Essentials series.

Cloud Data Design, Orchestration, and Management Using Microsoft Azure

Author : Francesco Diaz
Publisher : Apress
ISBN 13 : 1484236157
Total Pages : 451 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Cloud Data Design, Orchestration, and Management Using Microsoft Azure by : Francesco Diaz

Download or read book Cloud Data Design, Orchestration, and Management Using Microsoft Azure written by Francesco Diaz and published by Apress. This book was released on 2018-06-28 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use Microsoft Azure to optimally design your data solutions and save time and money. Scenarios are presented covering analysis, design, integration, monitoring, and derivatives. This book is about data and provides you with a wide range of possibilities to implement a data solution on Azure, from hybrid cloud to PaaS services. Migration from existing solutions is presented in detail. Alternatives and their scope are discussed. Five of six chapters explore PaaS, while one focuses on SQL Server features for cloud and relates to hybrid cloud and IaaS functionalities. What You'll Learn Know the Azure services useful to implement a data solution Match the products/services used to your specific needs Fit relational databases efficiently into data design Understand how to work with any type of data using Azure hybrid and public cloud features Use non-relational alternatives to solve even complex requirements Orchestrate data movement using Azure services Approach analysis and manipulation according to the data life cycle Who This Book Is For Software developers and professionals with a good data design background and basic development skills who want to learn how to implement a solution using Azure data services

Stream Analytics with Microsoft Azure

Author : Anindita Basak
Publisher : Packt Publishing Ltd
ISBN 13 : 1788390628
Total Pages : 314 pages
Book Rating : 4.7/5 (883 download)

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Book Synopsis Stream Analytics with Microsoft Azure by : Anindita Basak

Download or read book Stream Analytics with Microsoft Azure written by Anindita Basak and published by Packt Publishing Ltd. This book was released on 2017-12-01 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develop and manage effective real-time streaming solutions by leveraging the power of Microsoft Azure About This Book Analyze your data from various sources using Microsoft Azure Stream Analytics Develop, manage and automate your stream analytics solution with Microsoft Azure A practical guide to real-time event processing and performing analytics on the cloud Who This Book Is For If you are looking for a resource that teaches you how to process continuous streams of data in real-time, this book is what you need. A basic understanding of the concepts in analytics is all you need to get started with this book What You Will Learn Perform real-time event processing with Azure Stream Analysis Incorporate the features of Big Data Lambda architecture pattern in real-time data processing Design a streaming pipeline for storage and batch analysis Implement data transformation and computation activities over stream of events Automate your streaming pipeline using Powershell and the .NET SDK Integrate your streaming pipeline with popular Machine Learning and Predictive Analytics modelling algorithms Monitor and troubleshoot your Azure Streaming jobs effectively In Detail Microsoft Azure is a very popular cloud computing service used by many organizations around the world. Its latest analytics offering, Stream Analytics, allows you to process and get actionable insights from different kinds of data in real-time. This book is your guide to understanding the basics of how Azure Stream Analytics works, and building your own analytics solution using its capabilities. You will start with understanding what Stream Analytics is, and why it is a popular choice for getting real-time insights from data. Then, you will be introduced to Azure Stream Analytics, and see how you can use the tools and functions in Azure to develop your own Streaming Analytics. Over the course of the book, you will be given comparative analytic guidance on using Azure Streaming with other Microsoft Data Platform resources such as Big Data Lambda Architecture integration for real time data analysis and differences of scenarios for architecture designing with Azure HDInsight Hadoop clusters with Storm or Stream Analytics. The book also shows you how you can manage, monitor, and scale your solution for optimal performance. By the end of this book, you will be well-versed in using Azure Stream Analytics to develop an efficient analytics solution that can work with any type of data. Style and approach A comprehensive guidance on developing real-time event processing with Azure Stream Analysis

Enterprise Cloud Strategy

Author : Barry Briggs
Publisher : Microsoft Press
ISBN 13 : 1509301992
Total Pages : 228 pages
Book Rating : 4.5/5 (93 download)

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Book Synopsis Enterprise Cloud Strategy by : Barry Briggs

Download or read book Enterprise Cloud Strategy written by Barry Briggs and published by Microsoft Press. This book was released on 2016-01-07 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: How do you start? How should you build a plan for cloud migration for your entire portfolio? How will your organization be affected by these changes? This book, based on real-world cloud experiences by enterprise IT teams, seeks to provide the answers to these questions. Here, you’ll see what makes the cloud so compelling to enterprises; with which applications you should start your cloud journey; how your organization will change, and how skill sets will evolve; how to measure progress; how to think about security, compliance, and business buy-in; and how to exploit the ever-growing feature set that the cloud offers to gain strategic and competitive advantage.

Cloud Analytics with Microsoft Azure

Author : Has Altaiar
Publisher : Packt Publishing Ltd
ISBN 13 : 1800200285
Total Pages : 185 pages
Book Rating : 4.8/5 (2 download)

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Book Synopsis Cloud Analytics with Microsoft Azure by : Has Altaiar

Download or read book Cloud Analytics with Microsoft Azure written by Has Altaiar and published by Packt Publishing Ltd. This book was released on 2021-01-28 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to extract actionable insights from your big data in real time using a range of Microsoft Azure features Key FeaturesUpdated with the latest features and new additions to Microsoft AzureMaster the fundamentals of cloud analytics using AzureLearn to use Azure Synapse Analytics (formerly known as Azure SQL Data Warehouse) to derive real-time customer insightsBook Description Cloud Analytics with Microsoft Azure serves as a comprehensive guide for big data analysis and processing using a range of Microsoft Azure features. This book covers everything you need to build your own data warehouse and learn numerous techniques to gain useful insights by analyzing big data The book begins by introducing you to the power of data with big data analytics, the Internet of Things (IoT), machine learning, artificial intelligence, and DataOps. You will learn about cloud-scale analytics and the services Microsoft Azure offers to empower businesses to discover insights. You will also be introduced to the new features and functionalities added to the modern data warehouse. Finally, you will look at two real-world business use cases to demonstrate high-level solutions using Microsoft Azure. The aim of these use cases will be to illustrate how real-time data can be analyzed in Azure to derive meaningful insights and make business decisions. You will learn to build an end-to-end analytics pipeline on the cloud with machine learning and deep learning concepts. By the end of this book, you will be proficient in analyzing large amounts of data with Azure and using it effectively to benefit your organization. What you will learnExplore the concepts of modern data warehouses and data pipelinesDiscover unique design considerations while applying a cloud analytics solutionDesign an end-to-end analytics pipeline on the cloudDifferentiate between structured, semi-structured, and unstructured dataChoose a cloud-based service for your data analytics solutionsUse Azure services to ingest, store, and analyze data of any scaleWho this book is for This book is designed to benefit software engineers, Azure developers, cloud consultants, and anyone who is keen to learn the process of deriving business insights from huge amounts of data using Azure. Though not necessary, a basic understanding of data analytics concepts such as data streaming, data types, the machine learning life cycle, and Docker containers will help you get the most out of the book.

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

Author : Manpreet Singh
Publisher : Sams Publishing
ISBN 13 : 013403533X
Total Pages : 1044 pages
Book Rating : 4.1/5 (34 download)

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Book Synopsis Big Data Analytics with Microsoft HDInsight in 24 Hours, Sams Teach Yourself by : Manpreet Singh

Download or read book Big Data Analytics with Microsoft HDInsight in 24 Hours, Sams Teach Yourself written by Manpreet Singh and published by Sams Publishing. This book was released on 2015-11-12 with total page 1044 pages. Available in PDF, EPUB and Kindle. 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.

The Modern Data Warehouse in Azure

Author : Matt How
Publisher : Apress
ISBN 13 : 1484258231
Total Pages : 297 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis The Modern Data Warehouse in Azure by : Matt How

Download or read book The Modern Data Warehouse in Azure written by Matt How and published by Apress. This book was released on 2020-06-15 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build a modern data warehouse on Microsoft's Azure Platform that is flexible, adaptable, and fast—fast to snap together, reconfigure, and fast at delivering results to drive good decision making in your business. Gone are the days when data warehousing projects were lumbering dinosaur-style projects that took forever, drained budgets, and produced business intelligence (BI) just in time to tell you what to do 10 years ago. This book will show you how to assemble a data warehouse solution like a jigsaw puzzle by connecting specific Azure technologies that address your own needs and bring value to your business. You will see how to implement a range of architectural patterns using batches, events, and streams for both data lake technology and SQL databases. You will discover how to manage metadata and automation to accelerate the development of your warehouse while establishing resilience at every level. And you will know how to feed downstream analytic solutions such as Power BI and Azure Analysis Services to empower data-driven decision making that drives your business forward toward a pattern of success. This book teaches you how to employ the Azure platform in a strategy to dramatically improve implementation speed and flexibility of data warehousing systems. You will know how to make correct decisions in design, architecture, and infrastructure such as choosing which type of SQL engine (from at least three options) best meets the needs of your organization. You also will learn about ETL/ELT structure and the vast number of accelerators and patterns that can be used to aid implementation and ensure resilience. Data warehouse developers and architects will find this book a tremendous resource for moving their skills into the future through cloud-based implementations. What You Will LearnChoose the appropriate Azure SQL engine for implementing a given data warehouse Develop smart, reusable ETL/ELT processes that are resilient and easily maintained Automate mundane development tasks through tools such as PowerShell Ensure consistency of data by creating and enforcing data contracts Explore streaming and event-driven architectures for data ingestionCreate advanced staging layers using Azure Data Lake Gen 2 to feed your data warehouse Who This Book Is For Data warehouse or ETL/ELT developers who wish to implement a data warehouse project in the Azure cloud, and developers currently working in on-premise environments who want to move to the cloud, and for developers with Azure experience looking to tighten up their implementation and consolidate their knowledge

Cloud Scale Analytics with Azure Data Services

Author : Patrik Borosch
Publisher : Packt Publishing Ltd
ISBN 13 : 1800562144
Total Pages : 520 pages
Book Rating : 4.8/5 (5 download)

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Book Synopsis Cloud Scale Analytics with Azure Data Services by : Patrik Borosch

Download or read book Cloud Scale Analytics with Azure Data Services written by Patrik Borosch and published by Packt Publishing Ltd. This book was released on 2021-07-23 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to implementing a scalable and fast state-of-the-art analytical data estate Key FeaturesStore and analyze data with enterprise-grade security and auditingPerform batch, streaming, and interactive analytics to optimize your big data solutions with easeDevelop and run parallel data processing programs using real-world enterprise scenariosBook Description Azure Data Lake, the modern data warehouse architecture, and related data services on Azure enable organizations to build their own customized analytical platform to fit any analytical requirements in terms of volume, speed, and quality. This book is your guide to learning all the features and capabilities of Azure data services for storing, processing, and analyzing data (structured, unstructured, and semi-structured) of any size. You will explore key techniques for ingesting and storing data and perform batch, streaming, and interactive analytics. The book also shows you how to overcome various challenges and complexities relating to productivity and scaling. Next, you will be able to develop and run massive data workloads to perform different actions. Using a cloud-based big data-modern data warehouse-analytics setup, you will also be able to build secure, scalable data estates for enterprises. Finally, you will not only learn how to develop a data warehouse but also understand how to create enterprise-grade security and auditing big data programs. By the end of this Azure book, you will have learned how to develop a powerful and efficient analytical platform to meet enterprise needs. What you will learnImplement data governance with Azure servicesUse integrated monitoring in the Azure Portal and integrate Azure Data Lake Storage into the Azure MonitorExplore the serverless feature for ad-hoc data discovery, logical data warehousing, and data wranglingImplement networking with Synapse Analytics and Spark poolsCreate and run Spark jobs with Databricks clustersImplement streaming using Azure Functions, a serverless runtime environment on AzureExplore the predefined ML services in Azure and use them in your appWho this book is for This book is for data architects, ETL developers, or anyone who wants to get well-versed with Azure data services to implement an analytical data estate for their enterprise. The book will also appeal to data scientists and data analysts who want to explore all the capabilities of Azure data services, which can be used to store, process, and analyze any kind of data. A beginner-level understanding of data analysis and streaming will be required.

Predictive Analytics with Microsoft Azure Machine Learning

Author : Valentine Fontama
Publisher : Apress
ISBN 13 : 148420445X
Total Pages : 178 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Predictive Analytics with Microsoft Azure Machine Learning by : Valentine Fontama

Download or read book Predictive Analytics with Microsoft Azure Machine Learning written by Valentine Fontama and published by Apress. This book was released on 2014-11-25 with total page 178 pages. Available in PDF, EPUB and Kindle. 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.

Understanding Azure Data Factory

Author : Sudhir Rawat
Publisher : Apress
ISBN 13 : 1484241223
Total Pages : 376 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Understanding Azure Data Factory by : Sudhir Rawat

Download or read book Understanding Azure Data Factory written by Sudhir Rawat and published by Apress. This book was released on 2018-12-18 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Improve your analytics and data platform to solve major challenges, including operationalizing big data and advanced analytics workloads on Azure. You will learn how to monitor complex pipelines, set alerts, and extend your organization's custom monitoring requirements. This book starts with an overview of the Azure Data Factory as a hybrid ETL/ELT orchestration service on Azure. The book then dives into data movement and the connectivity capability of Azure Data Factory. You will learn about the support for hybrid data integration from disparate sources such as on-premise, cloud, or from SaaS applications. Detailed guidance is provided on how to transform data and on control flow. Demonstration of operationalizing the pipelines and ETL with SSIS is included. You will know how to leverage Azure Data Factory to run existing SSIS packages. As you advance through the book, you will wrap up by learning how to create a single pane for end-to-end monitoring, which is a key skill in building advanced analytics and big data pipelines. What You'll LearnUnderstand data integration on Azure cloudBuild and operationalize an ADF pipelineModernize a data warehouseBe aware of performance and security considerations while moving data Who This Book Is ForData engineers and big data developers. ETL (extract, transform, load) developers also will find the book useful in demonstrating various operations.

Machine Learning with Microsoft Technologies

Author : Leila Etaati
Publisher : Apress
ISBN 13 : 1484236580
Total Pages : 363 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Machine Learning with Microsoft Technologies by : Leila Etaati

Download or read book Machine Learning with Microsoft Technologies written by Leila Etaati and published by Apress. This book was released on 2019-06-12 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Know how to do machine learning with Microsoft technologies. This book teaches you to do predictive, descriptive, and prescriptive analyses with Microsoft Power BI, Azure Data Lake, SQL Server, Stream Analytics, Azure Databricks, HD Insight, and more. The ability to analyze massive amounts of real-time data and predict future behavior of an organization is critical to its long-term success. Data science, and more specifically machine learning (ML), is today’s game changer and should be a key building block in every company’s strategy. Managing a machine learning process from business understanding, data acquisition and cleaning, modeling, and deployment in each tool is a valuable skill set. Machine Learning with Microsoft Technologies is a demo-driven book that explains how to do machine learning with Microsoft technologies. You will gain valuable insight into designing the best architecture for development, sharing, and deploying a machine learning solution. This book simplifies the process of choosing the right architecture and tools for doing machine learning based on your specific infrastructure needs and requirements. Detailed content is provided on the main algorithms for supervised and unsupervised machine learning and examples show ML practices using both R and Python languages, the main languages inside Microsoft technologies. What You'll Learn Choose the right Microsoft product for your machine learning solutionCreate and manage Microsoft’s tool environments for development, testing, and production of a machine learning projectImplement and deploy supervised and unsupervised learning in Microsoft products Set up Microsoft Power BI, Azure Data Lake, SQL Server, Stream Analytics, Azure Databricks, and HD Insight to perform machine learning Set up a data science virtual machine and test-drive installed tools, such as Azure ML Workbench, Azure ML Server Developer, Anaconda Python, Jupyter Notebook, Power BI Desktop, Cognitive Services, machine learning and data analytics tools, and more Architect a machine learning solution factoring in all aspects of self service, enterprise, deployment, and sharing Who This Book Is For Data scientists, data analysts, developers, architects, and managers who want to leverage machine learning in their products, organization, and services, and make educated, cost-saving decisions about their ML architecture and tool set.