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    1. Data och IT
    2. Människa – datorinteraktion

    Azure Data Factory Cookbook

    Build and manage ETL and ELT pipelines with Microsoft Azure's serverless data integration service

    AvDmitry Anoshin,Dmitry Foshin

    Häftad, Engelska, 2020

    649 kr

    Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

    Beskrivning

    Solve real-world data problems and create data-driven workflows for easy data movement and processing at scale with Azure Data FactoryKey FeaturesLearn how to load and transform data from various sources, both on-premises and on cloudUse Azure Data Factory’s visual environment to build and manage hybrid ETL pipelinesDiscover how to prepare, transform, process, and enrich data to generate key insightsBook DescriptionAzure Data Factory (ADF) is a modern data integration tool available on Microsoft Azure. This Azure Data Factory Cookbook helps you get up and running by showing you how to create and execute your first job in ADF. You’ll learn how to branch and chain activities, create custom activities, and schedule pipelines. This book will help you to discover the benefits of cloud data warehousing, Azure Synapse Analytics, and Azure Data Lake Gen2 Storage, which are frequently used for big data analytics. With practical recipes, you’ll learn how to actively engage with analytical tools from Azure Data Services and leverage your on-premise infrastructure with cloud-native tools to get relevant business insights. As you advance, you’ll be able to integrate the most commonly used Azure Services into ADF and understand how Azure services can be useful in designing ETL pipelines. The book will take you through the common errors that you may encounter while working with ADF and show you how to use the Azure portal to monitor pipelines. You’ll also understand error messages and resolve problems in connectors and data flows with the debugging capabilities of ADF.By the end of this book, you’ll be able to use ADF as the main ETL and orchestration tool for your data warehouse or data platform projects.What you will learnCreate an orchestration and transformation job in ADFDevelop, execute, and monitor data flows using Azure SynapseCreate big data pipelines using Azure Data Lake and ADFBuild a machine learning app with Apache Spark and ADFMigrate on-premises SSIS jobs to ADFIntegrate ADF with commonly used Azure services such as Azure ML, Azure Logic Apps, and Azure FunctionsRun big data compute jobs within HDInsight and Azure DatabricksCopy data from AWS S3 and Google Cloud Storage to Azure Storage using ADF s built-in connectorsWho this book is forThis book is for ETL developers, data warehouse and ETL architects, software professionals, and anyone who wants to learn about the common and not-so-common challenges faced while developing traditional and hybrid ETL solutions using Microsoft's Azure Data Factory. You’ll also find this book useful if you are looking for recipes to improve or enhance your existing ETL pipelines. Basic knowledge of data warehousing is expected.

    Produktinformation

    • Utgivningsdatum:2020-12-24
    • Mått:191 x 235 x 21 mm
    • Vikt:712 g
    • Format:Häftad
    • Språk:Engelska
    • Antal sidor:382
    • Förlag:Packt Publishing Limited
    • ISBN:9781800565296

    Utforska kategorier

    • Människa – datorinteraktion inom Data och IT
    • Databaser inom Data och IT

    Mer om författaren

    Dmitry Anoshin is a data-centric technologist and a recognized expert in building and implementing big data and analytics solutions. He has a successful track record of implementing business and digital intelligence projects across retail, finance, marketing, and e-commerce. Dmitry possesses in-depth knowledge of digital/business intelligence, ETL, data warehousing, and big data technologies. He has extensive experience in data integration and is proficient in various data warehousing methodologies. Dmitry has consistently exceeded project expectations across the financial, machine tool, and retail industries. He has completed a number of multinational full BI/DI solution life cycle implementation projects. With expertise in data modeling, Dmitry also has a background and business experience in multiple relational databases, OLAP systems, and NoSQL databases. He is also an active speaker at data conferences and helps people to adopt cloud analytics. Dmitry Foshin is a Business Intelligence team leader focused on delivering business insights to the management team through data engineering, analytics, and visualization. He has led and executed complex full-stack BI solutions (from ETL processes to building DWHs and reporting) using Azure technologies, Data Lake, Data Factory, Data Bricks, MS Office 365, Power BI, and Tableau. He has also successfully launched numerous data analytics projects – both on-premises and in the cloud – that help achieve corporate goals for international FMCG companies, banks, and manufacturing companies. Roman Storchak is a PhD, and is a chief data officer whose main interest lies in building data-driven cultures through making analytics easy. He has led teams that have built ETL-heavy products in AdTech and retail and often uses Azure Stack, PowerBI, and Data Factory. Xenia Ireton is a Senior Software Engineer at Microsoft. She has extensive knowledge in building distributed services, data pipelines and data warehouses.

    Innehållsförteckning

    • Table of ContentsGetting Started with ADFOrchestration and Control FlowSetting up a Cloud Data WarehouseWorking with Azure Data LakeWorking with Big Data Integration with MS SSISData Migration Working with Azure Services IntegrationManaging Deployment Processes with Azure DevOpsMonitoring and Troubleshooting Data Pipelines