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所在平台: Udemy |
课程主页: https://www.udemy.com/course/dp-600-implementing-analytics-solutions-using-microsoft-fabric/
课程评论：没有评论
课程名称：Microsoft DP-600 备考：Fabric Analytics Engineer Associate 概述：本课程涵盖了DP-600 “Fabric Analytics Engineer Associate” 认证考试所需的内容，符合2024年7月22日的DP-600要求，并根据2024年11月15日的更新进行了调整。该课程对以下微软应用技能也很有帮助：APL-3008 “使用Microsoft Fabric实现实时智能解决方案”、APL-3009 “在Microsoft Fabric中实现湖屋”、APL-3010 “在Microsoft Fabric中实现数据仓库”。请注意：本课程与微软没有任何关联、认可或赞助。 学生反馈： Andrew表示：“我很喜欢这门课程，学到了很多有用的东西。计算组为我阐明了这个相对较新的功能，我将在未来使用它。我即将参加DP-600考试，这门课程填补了我对Fabric的知识空缺。由于这门课程，我还激活了Fabric 60天试用版，可以亲自实践创建项目和操作数据。这门课程的呈现方式清晰而有逻辑。” Saurabh说：“这门课程很棒。Phillip详细解释了概念，加上动手活动、实践活动和对高级DAX函数、SQL、PySpark和KQL的深入解析，使这门课程脱颖而出。我将在接下来的四天内参加DP-600考试。谢谢你，Phillip，我在每个视频中都学到了新东西。希望继续带来这样的好课程，我喜欢你的深入动手课程。” Jerry表示：“毫无疑问，这是Udemy上最好的DP-600课程之一。我购买了其他几门课程，但没有一门能与之相比。这门课程清晰、简洁而专注，没有多余的内容。多亏了这门优秀的课程，我获得了认证。强烈推荐！” 课程内容结构： 第一部分 - 如果您已经学习了PL-300考试，您将获得的Power BI知识； 第二部分 - 额外的Power BI知识（不属于PL-300考试）； 第三部分 - 使用SQL创建Fabric湖屋和数据仓库； 第四部分 - 使用KQL创建事件屋。 第一部分适合尚未学习微软PL-300考试的学员；如果您已学习过，请直接进入第二部分。第一部分内容包括：在Power BI Desktop中安装并创建报告，然后上传到Power BI服务，使用DAX创建计算列和度量值，以及DP-600考试所需的其他PL-300考试主题。 第二部分内容开始于Power BI，包括：开发语义模型的设计，扩展我们的DAX知识，使用外部应用程序如Tableau Editor 2和DAX Studio，实现多对多关系，动态字符串和使用优化菜单。还将涵盖分析开发生命周期、版本控制和部署解决方案、创建聚合表和使用XMLA端点等主题。 第三部分将介绍如何使用SQL在Fabric湖屋和数据仓库中查询和操作数据，包括数据摄取、创建湖屋和数据仓库，以及使用SQL分析端点操作SQL中的数据。 第四部分关注事件屋和KQL：创建事件屋、示例KQL查询、将SQL查询转换为KQL，使用KQL进行数据选择、筛选和聚合，扩展KQL查询的字符串、数字、日期时间和时间跨度功能，转换数据、合并和连接数据，并识别和解决重复及缺失数据。 课程适合所有知识水平的学员，尽管任何DAX、SQL或KQL的先验知识会有所帮助。完成课程后，您将对维护数据分析解决方案、准备数据以及实施和管理语义模型有良好的理解，经过一些实践，您甚至可以申请官方的微软认证DP-600——难道“微软认证：Fabric Analytics Engineer Associate”认证不会让您的简历看起来更出色吗？希望在课程中见到您——不妨来看看您可以学到些什么！
This course covers the content required for the DP-600 "Fabric Analytics Engineer Associate" certification exam. It is as per the DP-600 requirements as of 22 July 2024, with some updates as of 15 November 2024.This course is also useful for the following Microsoft Applied Skills:APL-3008 "Implement a Real-Time Intelligence solution with Microsoft Fabric"APL-3009 "Implement a lakehouse in Microsoft Fabric"APL-3010 "Implement a data warehouse in Microsoft Fabric"Please note: This course is not affiliated with, endorsed by, or sponsored by Microsoft.What do students like you say about this course?Andrew says: "I enjoyed this course, and I learned some really useful things. The Calculation Group clarified this relatively new feature for me, so I will use it in the future. I'm taking my DP-600 exam soon. This course has filled in my knowledge of Fabric. I've even activated my Fabric 60 Day Trial because of this course, so I can actually go through the steps of creating items and manipulating data first-hand. The corse was presented in clear and logical manner."Saurabh says: "This course is great. Phillip has explained the concepts in details and hands on activities, practice activities and in depth explanation of advanced DAX functions, SQL, PySpark and KQL makes this course stand out. I am going to attempt DP 600 in next four days. Thank you Phillip, I learned new things in each video. Keep bringing such great courses. I love your such in depth hands on courses."Jerry says: "Hands down, this is one of the best courses for DP-600 available on Udemy. I've purchased several other courses, but none compare to this one. It's clear, concise, and focused, with no unnecessary content. I've received my certification, thanks to this excellent course. Highly recommend!"It comes in four parts:Part 1 - Power BI knowledge you will have gained if you have already studied for the PL-300 exam,Part 2 - additional Power BI knowledge (not part of the PL-300 exam), Part 3 - Fabric lakehouses and data warehouses using SQL, and Part 4 - eventhouses using KQL.Part 1 of this course is for you if you have not studied for Microsoft's PL-300 exam. If you have, then please join me in Section 1, and then skip to Part 2 (Section 9). In Part 1, we'll look at:Installing and creating a report in Power BI Desktop and uploading it to Power BI Service,Creating calculated columns and measures using DAX, andOther PL-300 exam topics needed for the DP-600 exam.In Part 2 of this course, we'll start with Power BI. We'll look at:Developing our design of semantic models, including calculation groups/items and field parameters. Expanding our DAX knowledge, with DAX variables and windowing functions.Using external apps, such as Tableau Editor 2 and DAX Studio,Implementing many-to-many relationships, implementing dynamic strings, and using the Optimize menu.The analytics development lifecycle, focusing on version control and deployment solutions,Other Analytics topics, such as creating aggregation tables and using the XMLA endpoint.In Part 3 of this course, we'll query and manipulate data in Fabric lakehouses and data warehouses using SQL.After a brief look around Fabric, we'll start by ingesting data by using data pipelines and dataflows.We'll then create a lakehouse and Data Warehouse and use the SQL Analytics Endpoint to manipulate the data in SQL. We'll learn the 6 principle clauses in the SQL Select statement: SELECT, FROM, WHERE, GROUP BY, HAVING and ORDER BY.In Part 4 of this course, we'll look at the Eventhouses and KQL:We'll create an eventhouse, see sample KQL queries, and how you can convert SQL queries to KQL.We'll select, filter and aggregate data using KQL.We'll expand our KQL queries using string, number, datetime and timespan functions.Finally, we'll transform data using KQL, merging and joining data, and identify and resolve duplicate and missing data. No prior knowledge is assumed. We will start from the beginning for all languages and items, although any prior knowledge of DAX, SQL or KQL is useful.Once you have completed the course, you will have a good knowledge of maintaining a data analytics solution, preparing data, and implementing and managing semantic models. And with some practice, you could even go for the official Microsoft certification DP-600 - wouldn't the "Microsoft Certified: Fabric Analytics Engineer Associate" certification look good on your CV or resume?I hope to see you in the course - why not have a look at what you could learn?
