Udemy

Microsoft DP-600 prep: Fabric Analytics Engineer Associate

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  • 12,776 名學生
  • 更新於 3/2026
4.6
(1,668 個評分)
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課程資料

報名日期
全年招生
課程級別
學習模式
修業期
18 小時 10 分鐘
教學語言
英語
評分
4.6
(1,668 個評分)
2次瀏覽

課程簡介

Microsoft DP-600 prep: Fabric Analytics Engineer Associate

Learn advanced DAX skills, lakehouses, warehouses, SQL/KQL code. Helps with APL-3008, 3009, 3010 Microsoft Applied Skill

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 15 November 2024, with some updates as of 14 January 2026 and 20 April 2026.

This course is also useful for the following Microsoft Applied Skills:

  • APL-3008 "Implement a Real-Time Intelligence solution with 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:

  1. Part 1 - Power BI knowledge you will have gained if you have already studied for the PL-300 exam,

  2. Part 2 - additional Power BI knowledge (not part of the PL-300 exam),

  3. Part 3 - Fabric lakehouses and data warehouses using SQL, and

  4. 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, and

  • Other 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?

課程章節

  • 32 個章節
  • 197 堂課
  • 第 1 章 Introduction
  • 第 2 章 Part 1 Level 1: Installing and using Power BI Desktop and Service
  • 第 3 章 18. Part 1 Level 2: Creating calculated columns, including Logical functions
  • 第 4 章 Part 1 Level 3: Statistical functions
  • 第 5 章 Part 1 Level 4: Expanding our data model and Information Functions
  • 第 6 章 32b. Part 1 Level 5 - Filter and Value Functions
  • 第 7 章 Part 1 Level 6 - Date, Time and Time Intelligence functions
  • 第 8 章 Part 1 Level 7 - Other PL-300 exam topics needed for the DP-600 exam
  • 第 9 章 Part 2 Level 1: Design and build semantic models
  • 第 10 章 Part 2 Level 2: Calculation groups/items and field parameters
  • 第 11 章 Part 2 Level 3: DAX functions
  • 第 12 章 Part 2 Level 4: Optimize enterprise-scale semantic models
  • 第 13 章 Part 2 Level 5: Relationships and performance improvements
  • 第 14 章 Part 2 Level 6: Manage the analytics development lifecycle
  • 第 15 章 Part 2 Level 7: Other Power BI Analytics topics
  • 第 16 章 Part 2 - Practice Test for advanced Power BI semantic models
  • 第 17 章 Part 3 Section 1 - A look around Fabric
  • 第 18 章 12, 14. Part 3 Section 2 - Using data pipelines and dataflows
  • 第 19 章 Part 3 Section 3 - Transforming data using a Dataflow Gen2
  • 第 20 章 Part 3 Section 4 - Loading and saving data using notebooks
  • 第 21 章 Part 3 Section 5 - Creating SQL queries using the SELECT and FROM clauses
  • 第 22 章 Part 3 Section 6 - Using the WHERE, GROUP BY, HAVING and ORDER BY clauses
  • 第 23 章 Part 3 Section 7 - Transform data in a lakehouse
  • 第 24 章 Part 3 Section 8 - Transform data in a data warehouse
  • 第 25 章 Part 3 Section 9 - Improving performance in SQL
  • 第 26 章 Part 4 Section 1 - Creating an eventhouse
  • 第 27 章 28. Part 4 Section 2 - Selecting, filtering and aggregating data using KQL
  • 第 28 章 18, 25, 28. Part 4 Section 3 - Functions
  • 第 29 章 Part 4 Section 4 - Transforming data using KQL
  • 第 30 章 Part 4 Section 5 - Configure security and governance, and deployment pipelines
  • 第 31 章 Congratulations for completing the course
  • 第 32 章 Bonus lecture

課程內容

  • Plan, implement, and manage a solution for data analytics, Prepare and serve data, Implement and manage semantic models, Explore and analyze data


評價

  • M
    Michael Papamikroulis
    5.0

    Really good to get into Fabric. The instructor dedicates much time to show you Power BI which is essential for Fabric. Nice examples using Fabric. In my opinion, instructor shows too much regarding KQL. All in all a great course to begin with Fabric.

  • K
    Kapil Srivastava
    5.0

    I will write review after I pass the exam.

  • J
    Joe Douglas
    3.5

    I like to be able to follow along and practice lessons. The sections where you use your SQL database make it difficult to practice what you're saying. However, the information is clearly communicated and I understand it.

  • R
    Rachel Roos
    5.0

    This course had great explanations and examples that help you understand the material. Perhaps an update could be added about the default semantic model that used to be created automatically. This feature has been recently retired.

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