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Azure Data Engineering Cookbook : Design and Implement Batch and Streaming Analytics Using Azure Cloud Services

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Τίτλος: Azure Data Engineering Cookbook : Design and Implement Batch and Streaming Analytics Using Azure Cloud Services
Περιγραφή: Over 90 recipes to help you orchestrate modern ETL/ELT workflows and perform analytics using Azure services more easilyKey FeaturesBuild highly efficient ETL pipelines using the Microsoft Azure Data servicesCreate and execute real-time processing solutions using Azure Databricks, Azure Stream Analytics, and Azure Data ExplorerDesign and execute batch processing solutions using Azure Data FactoryBook DescriptionData engineering is one of the faster growing job areas as Data Engineers are the ones who ensure that the data is extracted, provisioned and the data is of the highest quality for data analysis. This book uses various Azure services to implement and maintain infrastructure to extract data from multiple sources, and then transform and load it for data analysis. It takes you through different techniques for performing big data engineering using Microsoft Azure Data services. It begins by showing you how Azure Blob storage can be used for storing large amounts of unstructured data and how to use it for orchestrating a data workflow. You'll then work with different Cosmos DB APIs and Azure SQL Database. Moving on, you'll discover how to provision an Azure Synapse database and find out how to ingest and analyze data in Azure Synapse. As you advance, you'll cover the design and implementation of batch processing solutions using Azure Data Factory, and understand how to manage, maintain, and secure Azure Data Factory pipelines. You'll also design and implement batch processing solutions using Azure Databricks and then manage and secure Azure Databricks clusters and jobs. In the concluding chapters, you'll learn how to process streaming data using Azure Stream Analytics and Data Explorer. By the end of this Azure book, you'll have gained the knowledge you need to be able to orchestrate batch and real-time ETL workflows in Microsoft Azure.What you will learnUse Azure Blob storage for storing large amounts of unstructured dataPerform CRUD operations on the Cosmos Table APIImplement elastic pools and business continuity with Azure SQL DatabaseIngest and analyze data using Azure Synapse AnalyticsDevelop Data Factory data flows to extract data from multiple sourcesManage, maintain, and secure Azure Data Factory pipelinesProcess streaming data using Azure Stream Analytics and Data ExplorerWho this book is forThis book is for Data Engineers, Database administrators, Database developers, and extract, load, transform (ETL) developers looking to build expertise in Azure Data engineering using a recipe-based approach. Technical architects and database architects with experience in designing data or ETL applications either on-premise or on any other cloud vendor who wants to learn Azure Data engineering concepts will also find this book useful. Prior knowledge of Azure fundamentals and data engineering concepts is needed.
Συγγραφείς: Ahmad Osama, Nagaraj Venkatesan
Resource Type: eBook.
Θέματα: Electronic data processing--Batch processing, Database management, Cloud computing, Streaming technology (Telecommunications)
Categories: COMPUTERS / Data Science / Data Modeling & Design, COMPUTERS / Data Science / General, COMPUTERS / Data Science / Data Warehousing
Βάση Δεδομένων: eBook Index
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  Data: Azure Data Engineering Cookbook : Design and Implement Batch and Streaming Analytics Using Azure Cloud Services
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  Data: Over 90 recipes to help you orchestrate modern ETL/ELT workflows and perform analytics using Azure services more easilyKey FeaturesBuild highly efficient ETL pipelines using the Microsoft Azure Data servicesCreate and execute real-time processing solutions using Azure Databricks, Azure Stream Analytics, and Azure Data ExplorerDesign and execute batch processing solutions using Azure Data FactoryBook DescriptionData engineering is one of the faster growing job areas as Data Engineers are the ones who ensure that the data is extracted, provisioned and the data is of the highest quality for data analysis. This book uses various Azure services to implement and maintain infrastructure to extract data from multiple sources, and then transform and load it for data analysis. It takes you through different techniques for performing big data engineering using Microsoft Azure Data services. It begins by showing you how Azure Blob storage can be used for storing large amounts of unstructured data and how to use it for orchestrating a data workflow. You'll then work with different Cosmos DB APIs and Azure SQL Database. Moving on, you'll discover how to provision an Azure Synapse database and find out how to ingest and analyze data in Azure Synapse. As you advance, you'll cover the design and implementation of batch processing solutions using Azure Data Factory, and understand how to manage, maintain, and secure Azure Data Factory pipelines. You'll also design and implement batch processing solutions using Azure Databricks and then manage and secure Azure Databricks clusters and jobs. In the concluding chapters, you'll learn how to process streaming data using Azure Stream Analytics and Data Explorer. By the end of this Azure book, you'll have gained the knowledge you need to be able to orchestrate batch and real-time ETL workflows in Microsoft Azure.What you will learnUse Azure Blob storage for storing large amounts of unstructured dataPerform CRUD operations on the Cosmos Table APIImplement elastic pools and business continuity with Azure SQL DatabaseIngest and analyze data using Azure Synapse AnalyticsDevelop Data Factory data flows to extract data from multiple sourcesManage, maintain, and secure Azure Data Factory pipelinesProcess streaming data using Azure Stream Analytics and Data ExplorerWho this book is forThis book is for Data Engineers, Database administrators, Database developers, and extract, load, transform (ETL) developers looking to build expertise in Azure Data engineering using a recipe-based approach. Technical architects and database architects with experience in designing data or ETL applications either on-premise or on any other cloud vendor who wants to learn Azure Data engineering concepts will also find this book useful. Prior knowledge of Azure fundamentals and data engineering concepts is needed.
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RecordInfo BibRecord:
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      – Code: 004.6782
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Electronic data processing--Batch processing
        Type: general
      – SubjectFull: Database management
        Type: general
      – SubjectFull: Cloud computing
        Type: general
      – SubjectFull: Streaming technology (Telecommunications)
        Type: general
    Titles:
      – TitleFull: Azure Data Engineering Cookbook : Design and Implement Batch and Streaming Analytics Using Azure Cloud Services
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          Name:
            NameFull: Ahmad Osama
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          Name:
            NameFull: Nagaraj Venkatesan
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          Name:
            NameFull: Ahmad Osama
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          Name:
            NameFull: Nagaraj Venkatesan
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2021
            – D: 25
              M: 11
              Type: profile
              Y: 2021
          Identifiers:
            – Type: isbn-print
              Value: 9781800206557
            – Type: isbn-electronic
              Value: 9781800201545
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