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所在平台: Udemy |
课程主页: https://www.udemy.com/course/azure-data-engineering-real-world-projects-fundamentals/
课程评论：没有评论
课程名称：Azure 数据工程：真实世界项目与基础知识 课程概述：欢迎来到 Azure 数据工程大师班，这是您掌握 Azure 云基础知识并通过沉浸式项目获得实践经验的终极指南。无论您是渴望掌握 Azure 基础知识的新手，还是希望提升数据工程技能的经验丰富的专业人士，这门全面的课程旨在赋予您能力。 您将学习到的内容： 模块 1：Azure 云简介 - 了解云计算在现代数据处理中的变革力量。 - 掌握基本的云计算概念，包括 IaaS、PaaS 和 SaaS。 - 学习如何高效设置和管理 Azure 帐户，以优化资源利用。 模块 2：掌握 Azure Databricks - 发掘 Azure Databricks 的全部潜力，这是一个动态的数据分析工具。 - 深入了解 Apache Spark 在 Databricks 中的角色，以实现无缝的数据探索和转换。 - 探索协作功能和高效数据处理的最佳实践。 模块 3：掌握 Azure Blob 存储 - 成为 Azure Blob 存储的专家，利用其进行安全和可扩展的数据存储。 - 学习如何无缝管理数据，包括上传、下载和版本控制。 - 探索不同的存储选项及其各自的使用案例，以优化数据管理。 模块 4：掌握 Azure 数据工厂 - 开始全面的 Azure 数据工厂之旅，这是现代数据集成的基石。 - 掌握构建强大数据管道的艺术，进行数据复制和数据流等活动。 - 探索与其他 Azure 服务的集成，以创建无缝的数据工作流，提高生产力。 模块 5：掌握 Azure 密钥保管库 - 深入了解 Azure 密钥保管库及其在保护敏感信息中的重要作用。 - 学习如何自信地实施和配置 Azure 密钥保管库，确保强大的安全措施。 - 探索在不同开发场景中安全密钥管理的最佳实践。 实践项目： 1. Play Store 数据集分析 - 集成 Azure 服务，使用密钥保管库进行加密安全。 - 使用 Azure 数据工厂 (ADF) 构建复制活动管道，动态获取 GitHub 中的压缩 tar.gz 文件并上传到存储帐户容器。 - 在 Azure Databricks 中对数据进行预处理，以确保准确性和可靠性。 2. 奥运数据集分析 - 利用 API 请求从 Kaggle 获取数据集并存储在 Azure 存储帐户中。 - 在 Azure Databricks 中进行数据预处理和探索，揭示奥运会事件的洞见。 3. Stack Overflow 数据集分析 - 构建动态数据工厂管道，以获取 Stack Overflow 开发者调查数据并进行预处理分析。 - 提取开发者的教育水平、学习来源偏好和人口统计趋势的见解。 4. Uber 出租车数据集分析 - 创建强大的数据工厂管道，从 NYC TLC 网站获取 Uber 出租车数据并进行预处理。 - 分析出租车需求模式、支付方式分布及支付方式与行程距离之间的关系。 课程特点： - Azure 服务的无缝集成，实现安全高效的数据处理。 - 涵盖各种数据集和分析场景的实用项目。 - 专家指导和构建强大数据管道、获取可操作见解的最佳实践。 加入我们的 Azure 数据工程大师班，将您的 Azure 数据技能提升到一个新的水平。无论您是数据爱好者、渴望成为数据工程师的人，还是经验丰富的专业人士，这门大师班都是您掌握 Azure 云基础知识和真实世界数据工程项目的门户。
Course Description:Welcome to the Azure Data Engineering Masterclass, your ultimate guide to mastering Azure Cloud fundamentals and gaining practical experience through immersive projects. Whether you're a novice eager to grasp Azure essentials or an experienced professional aiming to enhance your data engineering skills, this comprehensive course is designed to empower you.What You'll Learn:Module 1: Introduction to Azure CloudDiscover the transformative power of cloud computing for modern data processing.Gain a solid understanding of essential cloud computing concepts, including IaaS, PaaS, and SaaS.Learn how to set up and manage your Azure account efficiently for optimal resource utilization.Module 2: Mastering Azure DatabricksUnlock the full potential of Azure Databricks, a dynamic tool for data analytics.Dive deep into Apache Spark and its role within Databricks for seamless data exploration and transformation.Explore collaborative features and best practices for efficient data processing.Module 3: Mastering Azure Blob StorageBecome an Azure Blob Storage expert and harness its capabilities for secure and scalable data storage.Learn to manage data seamlessly with Blob Storage, including uploading, downloading, and versioning.Explore different storage options and their respective use cases for optimized data management.Module 4: Mastering Azure Data FactoryEmbark on a comprehensive journey into Azure Data Factory, a cornerstone of modern data integration.Master the art of building robust data pipelines with activities like copy data and data flow.Explore integration with other Azure services to create seamless data workflows for enhanced productivity.Module 5: Mastering Azure Key VaultsDive deep into Azure Key Vaults and their crucial role in safeguarding sensitive information.Learn to implement and configure Azure Key Vaults with confidence, ensuring robust security measures.Explore best practices for secure key management across diverse development scenarios.Hands-On Projects:Play Store Dataset AnalysisDescription:Integrate Azure services using Key Vault for encrypted security.Build a copy activity pipeline with Azure Data Factory (ADF) to dynamically fetch compressed tar.gz files from GitHub and upload them to a storage account container.Preprocess the data in Azure Databricks to ensure accuracy and reliability.Analyze Play Store data to derive insights such as app installs, ratings, distribution of free vs. paid apps, and more.Olympics Dataset AnalysisDescription:Utilize API requests to fetch datasets from Kaggle and store them in Azure storage accounts.Perform data preprocessing and exploration in Azure Databricks to uncover insights on Olympic events.Analyze gender, national, and sports-level participation trends to understand historical performance and popularity shifts.Stack Overflow Dataset AnalysisDescription:Build dynamic data factory pipelines to fetch Stack Overflow developer survey data and preprocess it for analysis.Extract insights on developers' education levels, preferred sources of learning, and demographic trends.Utilize Azure services to handle diverse data formats and generate actionable insights for understanding developer backgrounds.Uber Taxi Dataset AnalysisDescription:Create robust data factory pipelines to retrieve Uber taxi data from NYC TLC site and preprocess it for analysis.Analyze taxi demand patterns, payment types distribution, and correlations between payment methods and trip distances.Utilize Azure Data Factory's capabilities to handle dynamic file paths and generate valuable insights for optimizing transportation services.Key Features:Seamless integration of Azure services for secure and efficient data handling.Practical, hands-on projects covering diverse datasets and analytical scenarios.Expert guidance and best practices for building robust data pipelines and deriving actionable insights.Join us in the Azure Data Engineering Masterclass and take your Azure data skills to the next level. Whether you're a data enthusiast, aspiring data engineer, or seasoned professional, this masterclass is your gateway to mastering Azure Cloud fundamentals and real-world data engineering projects.
