Описание: 1 Overview of data architecture on Microsoft Azure Introduction Technologies: everyone touched in the book plus some other edge technologies just mentioned. We explain the scenarios of the book.This chapter will be written during the whole process, updating it with the relevant content of the scenarios developed in the chapters. 2 Working with Relational DBs on Azure Relational DBs scenarios Technologies: VMs, Backup, Storage, SQL Server DR and GEO-DR, (Oracle, MySQL)We would like to cover the best practices to deploy standard RDBMSs while using Azure VMs and networking. 3 Working with Azure SQL Database Azure DB scenarios Technologies: Azure SQL DB, Stretch DB, Database Pools, Sharding data, Migration from other RDBMSs to Azure SQL DBThis chapter is about the SQL Database PaaS, with some tricks for advanced usage. We cover the services and the connected services, how to scale with relational DBs and how to write multi-tenant applications. 4 Working with NoSQL alternatives NoSQL scenarios Technologies: Storage, DocumentDB, Redis, Azure SearchThis chapter enforces the polyglot persistence idea, where different technologies and data sources address different needs. The NoSQL alternatives can fill the gap of modern applications in terms of performance and feature set. 5 Orchestrate data with Azure Data Factory Integration scenarios Technologies: Azure Data FactoryIn this chapter we talk about integration of different data sources and advanced pipelines of data transformation. We explore some scenarios to lower the complexity of the Data Factory service and we see how to setup existing solutions to fit it. 6 Advanced analysis with Azure Data Lake Analysis scenarios Technologies: Data Lake Store/Analytics, U-SQLThis is the first chapter about ingestion of big data. This is focused on ingestion of native data, to be prepared, enriched and evaluated/analyzed in a second step. 7 Real-time Ingestion, Processing and Prediction Real-time scenarios Technologies: Machine Learning, Stream Analytics, Event HubThis is instead focused in ingestion of well-known and structured data with the aim to process it in real-time. In addition a step of prediction is added to react (in real time too) to certain events. 8 Working with Big Data with Azure Batch and Map/Reduce Big data scenarios Technologies: HDInsight, Hadoop, Spark, R Server, Storm, Azure BatchThis is the last chapter about Big Data, exploring the industry standard to perform data operations, while executing those engines on Azure. 9 APPENDIX (tbd yet, adding some of the topics below to one of the other chapter still has to be defined) Other Technologies: Azure Analysis Services (chapter 3?), Power BI (chapter 6?), Azure SQL DataWarehouse (chapter 6?), Azure Data Catalog (chapter 5?)Those technologies should fit the existing chapters, but we do not know where they best fit at the time being.
Автор: Guay Paz, Jose Rolando Название: Microsoft azure cosmos db revealed ISBN: 1484233506 ISBN-13(EAN): 9781484233504 Издательство: Springer Рейтинг: Цена: 6288.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Learn the main features of Azure Cosmos DB and how to use Microsoft’s multi-model database service as a data store for mission-critical applications. The clear examples help in writing your own applications to take advantage of Cosmos DB’s multi-model, globally distributed, elastic database. Simple step-by-step instructions show how to resolve common and uncommon scenarios involving Azure Cosmos DB, and scenarios such as delivering extremely low response times (in the order of milliseconds), and scaling rapidly and globally.
Microsoft Azure Cosmos DB Revealed demonstrates a multitude of possible implementations to get you started. This book guides you toward best practices to get the most out of Microsoft’s Cosmos DB service. Later chapters in the book cover advanced implementation features, helping you master important elements such as securing the database, querying, and using various APIs.
What You'll Learn
Set up a development environment to work with Azure Cosmos DBConfigure Azure Cosmos DB in a production environment with multi-region distributionQuery using all APIs, including SQL, JavaScript, MongoDB, and GraphWork with the Azure Cosmos DB.NET SDK in an application you builtAccess Cosmos DB from web applications created in .NET
Who This Book Is For
Developers who build applications to be hosted in Microsoft Azure, whether they use PaaS or IaaS. No previous knowledge of Azure Cosmos DB is assumed, but readers must be familiar with developing applications in Microsoft Visual Studio.
This chapter provides overview of exciting and relevant technical areas essential to professionals in the IoT industry. Chapter provides an introduction to Internet of Things (IoT) and covers the concepts, hardware, and platforms of an IoT solution available in the market.
Introduction
Building blocks
Design Principles
IoT Devices and Sensors
IoT Platforms
Industrial IoT
Chapter 2: Microsoft Azure IoT Platform 20
This chapter introduces with various offerings of Microsoft Azure IoT platform and its service offerings. Reader will learn various solution architecture suiting with different business needs, like single and bi-directional communication Architecture.
Introduction
IoT Services
Architect
Chapter 3: Streaming IoT data to Microsoft Azure 20
This chapter provides hands-on experience registering and configuring device, setting up IoT environment and invoking messages. Students will learn to stream data (ingesting the telemetry) from simulated device to IoT hub.
Manage IoT hub
Device registration
Stream structural data and non-structural data
Storing data
Lab - Using simulated device
Chapter 4: IoT Applications in Manufacturing 25
This chapter introduces possible real-time applications of IoT in Manufacturing business. Managers will learn How to run an IoT enabled Manufacturing business using Microsoft Azure. Developers will gain hands-on experience in Stream Analytics by analyzing stream of data in real-time using a SQL-like language. This makes it possible for monitor asset, detecting anomalies, checking conditions and displaying real-time data for preventive maintenance.
Автор: Soh, Julian Singh, Priyanshi Название: Data science solutions on azure ISBN: 1484264045 ISBN-13(EAN): 9781484264041 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Part I - Introduction to Data Science and its rise to prominence
Chapter 1 Data Science in the modern enterprise
What is Data Science
The Data Scientists' tools and lingo
Ethics and ethical AI
Significance of Data Science in organizations
Case Studies of applied Data Science
Chapter 2 Most important Statistical Tehniques in Data Science
Top Statistical Tehniques Data Scientists need to know
Описание: 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 Learn
Understand 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 For
Data engineers and big data developers. ETL (extract, transform, load) developers also will find the book useful in demonstrating various operations.
Автор: Vinit Yadav Название: Processing Big Data with Azure HDInsight ISBN: 1484228685 ISBN-13(EAN): 9781484228685 Издательство: Springer Рейтинг: Цена: 5309.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Get a jump start on using Azure HDInsight and Hadoop Ecosystem components. As most Hadoop and Big Data projects are written in Java, Scala or Python, this book minimizes the effort to learn another language and is written from the perspective of a .NET developer. Hadoop components are covered, and code samples are written in .NET only.
