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Azure Data Engineering Cookbook: Design and implement batch and streaming analytics using Azure Cloud Services
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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.
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- Over 90 recipes to help data scientists and AI engineers orchestrate modern ETL/ELT workflows and perform analytics using Azure services more easilyKey FeaturesDiscover how to work with different SQL and NoSQL data stores in Microsoft AzureCreate 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 a growing field that focuses on preparing data for 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.This book takes you through different techniques for performing big data engineering using Microsoft cloud 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 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 want to learn Azure Data engineering concepts will also find this book useful. Prior knowledge of Azure fundamentals and data engineering concepts is needed.Table of ContentsWorking with Azure Blob StorageWorking with Relational Database in AzureAnalyzing Data with Azure Synapse AnalyticsControl Flow Activities in Azure Data FactoryControl Flow Transformation and Copy Data Activity in Azure Data FactoryData Flow in Azure Data FactoryAzure Data Factory Integration RuntimeDeploying Azure Data Factory PipelinesBatch and Streaming Data Processing with Azure Databricks
| Publisher | Packt Publishing |
| Publication date | April 5, 2021 |
| Language | English |
| Print length | 454 pages |
| ISBN-10 | 1800206550 |
| ISBN-13 | 978-1800206557 |
| Item Weight | 1.84 pounds (830 grams) |
| Dimensions | 7.5 x 1.03 x 9.25 inches (19.1 x 2.6 x 23.5 cm) |
Who Should Buy?
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Data Engineers
Ideal for data engineers seeking practical recipes to implement batch and streaming analytics on Azure platforms.
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Cloud Developers
Useful for cloud developers wanting to integrate Azure data services for scalable analytical solutions across applications.
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Business Analysts
Great for business analysts aiming to understand how to leverage Azure's analytics capabilities for data-driven decisions.
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Beginners
Not suitable for beginners with no prior knowledge of data engineering or Azure services; requires foundational understanding.
Product Description
Customer Questions & Answers
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Question:
What is the Azure Data Engineering Cookbook about?
Answer: The Azure Data Engineering Cookbook serves as a practical guide for designing and implementing efficient data engineering solutions using Azure Cloud Services. It covers various techniques for both batch and streaming analytics, making it ideal for professionals looking to leverage Azure's capabilities. This cookbook includes recipes ranging from setting up data pipelines to optimizing data flow, helping you navigate real-world challenges in data engineering workflows. -
Question:
Who should read the Azure Data Engineering Cookbook?
Answer: This cookbook is tailored for data engineers, developers, and architects who aim to deepen their understanding of Azure's data services. If you're involved in designing data solutions or wish to improve your skills in data analytics, this resource is invaluable. Additionally, beginners in the field of data engineering looking to learn practical applications of Azure will find the step-by-step recipes particularly beneficial. -
Question:
What types of recipes are included in the cookbook?
Answer: The cookbook includes a diverse range of recipes focusing on both batch and streaming analytics. Specific topics cover data ingestion, ETL processes, data transformation, and data storage using Azure services like Azure Data Factory, Azure Synapse Analytics, and Azure Stream Analytics. Each recipe is structured to provide clear methodologies and real-world applications to facilitate learning and implementation. -
Question:
Can beginners understand the content in the Azure Data Engineering Cookbook?
Answer: Yes, beginners can absolutely understand and utilize the content within the Azure Data Engineering Cookbook. The material is designed to progressively build knowledge, starting from foundational concepts to more complex implementations. With detailed explanations and practical examples, even those new to Azure Cloud Services can follow along and apply the lessons to their own scenarios. -
Question:
How can I implement batch analytics using this cookbook?
Answer: To implement batch analytics using the Azure Data Engineering Cookbook, follow the structured recipes focused on batch processing. These recipes provide comprehensive guidance on creating data pipelines that automate the collection, processing, and transformation of data. You'll learn how to leverage Azure tools like Azure Data Factory for orchestrating data workflows, making it easier to analyze historical data sets. -
Question:
What are streaming analytics, and how are they addressed in the cookbook?
Answer: Streaming analytics involve real-time data processing from continuous data streams, allowing businesses to derive insights instantaneously. The Azure Data Engineering Cookbook addresses streaming analytics through dedicated recipes that utilize services like Azure Stream Analytics. You'll learn to set up real-time data ingestion, windowing functions, and how to visualize data dynamically, which is crucial for applications in finance, IoT, and more. -
Question:
Does the cookbook cover integration with other Azure services?
Answer: Indeed, the Azure Data Engineering Cookbook delves into the integration of various Azure services, showcasing how to create cohesive data solutions. It includes recipes that link services such as Azure Blob Storage, Azure SQL Database, and Azure Databricks. This comprehensive approach enables users to leverage the full spectrum of Azure's capabilities, streamlining workflows from data collection to analysis. -
Question:
What tools and technologies does the cookbook focus on?
Answer: The Azure Data Engineering Cookbook focuses on a variety of tools and technologies within the Azure ecosystem, including Azure Data Factory, Azure Synapse Analytics, Azure Stream Analytics, and more. By familiarizing yourself with these tools through hands-on recipes, you'll not only understand their functionalities but also discover how to effectively leverage them for building robust data engineering solutions tailored to your project needs. -
Question:
Can the Azure Data Engineering Cookbook help with job preparation for data engineering roles?
Answer: Absolutely! The Azure Data Engineering Cookbook is an excellent resource for job preparation. By engaging with its practical recipes, you'll gain hands-on experience and skills relevant to today's data engineering roles. Understanding the use of Azure services enables you to showcase your competence in interviews, build a portfolio of projects, and stay up-to-date with industry standards. -
Question:
Where can I buy Azure Data Engineering Cookbook in Slovenia?
Answer: You can purchase the Azure Data Engineering Cookbook on Ubuy. They offer a broad selection of books and deliver internationally, making it a reliable option to get your copy whether you are starting your data engineering journey or looking to expand your knowledge in Azure analytics.
Data Modeling & Design Editorial Review
The "Azure Data Engineering Cookbook" has garnered positive attention from users seeking a thorough exploration of data engineering practices within the Azure framework. The book has been lauded for its detailed, step-by-step approach to implementing batch and streaming analytics using various Azure Cloud Services. Readers appreciate the comprehensive exposition of critical services like Azure Data Factory, Synapse Analytics, and Databricks, which cater specifically to data engineers looking to establish robust data pipelines and analytics solutions. Many reviewers commend the author's ability to elucidate complex concepts in a clear and accessible manner, making it an excellent resource for both beginners and those more seasoned in Azure. The inclusion of practical recipes that provide not only procedural guidance but also context on Azure services is a significant highlight, although some users feel that the explanations on certain processes could have been more in-depth. The emphasis on the Data Factory service throughout the book, while beneficial, has left some readers wanting more detailed coverage of other important services such as Data Lake and Databricks. Additionally, while the authorship's organization of material is appreciated, the lack of further reading resources and links to official Microsoft documentation has been noted as a missed opportunity to enhance the book's utility. Overall, the "Azure Data Engineering Cookbook" is seen as an invaluable tool for learning and applying Azure’s data engineering capabilities, especially for professionals looking to integrate various Azure services effectively. **
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Pros
- Detailed and comprehensive step-by-step guides
- Clear explanations and lucid language
- Useful PowerShell scripts and visuals
- Focus on critical services like Azure Data Factory
- Suitable for beginners and those familiar with Azure
Cons
- Limited depth in explanations of processes and technologies
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Features & Benefits
- Over 90 recipes for data scientists and AI engineers.
- Learn to create and execute real-time processing solutions.
- Master batch processing with Azure Data Factory and Databricks.
- Understand how to work with SQL and NoSQL data stores.
- Gain skills to manage, maintain, and secure Azure services.
- Perfect for database administrators and ETL developers.
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