Microsoft Power BI - The Complete Masterclass [2023 EDITION]
Microsoft Power BI - The Complete Masterclass [2023 EDITION]

Microsoft Power BI - The Complete Masterclass [2023 EDITION]

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Sep 1, 2025 10:05 PM
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Chapter 3 : Data Transformation - The Query EditorChapter 3 : Data Transformation - The Query EditorChapter 4 : Data Transformation - AdvancedChapter 4 : Data Transformation - AdvancedChapter 5 : Creating a Data ModelChapter 5 : Creating a Data ModelChapter 6 : Data VisualizationChapter 6 : Data Visualization📚Chapter 7 : Power BI and PythonChapter 8 : DAX - The EssentialsChapter 9 : DAX - The CALCULATE FunctioChapter 10 : Tell a Story with Your Data - Learn to Visualize EffectivelChapter 11 : Power BI Service - Power BI CloudChapter 12 : Row-Level SecurityChapter 13 : More Data SourcesChapter 14 : Next Steps to Improve and Stay Up-to-Date
Power BI for Data Analytics - Full Course for Beginners

🧮 Course Problems & Certificate 👉 https://lukeb.co/powerbi 📁 Course Files & Projects 👉 https://lukeb.co/powerbi-files My FREE Course to be a Data Analyst 👉 https://lukebarousse.com/5daycourse 𝗢𝘁𝗵𝗲𝗿 𝗖𝗼𝘂𝗿𝘀𝗲 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 ▔▔▔▔▔▔▔▔▔▔▔ Power BI Course Website 👉 https://www.lukebarousse.com/powerbi 📊 Project #1 - Live Dashboard 👉 https://lukeb.co/powerbi-project1 📉 Project #2 - Live Dashboard 👉 https://lukeb.co/powerbi-project2 Parallels VM - Run Windows on a Mac 👉 https://lukeb.co/parallels 𝗖𝗼𝘂𝗿𝘀𝗲 𝗢𝘂𝘁𝗹𝗶𝗻𝗲 ▔▔▔▔▔▔▔ 0️⃣ 𝗜𝗻𝘁𝗿𝗼 00:00 - Welcome 03:58 - What is Power BI? 09:19 - Course Intro 1️⃣ 𝗚𝗿𝗮𝗻𝗱 𝗧𝗼𝘂𝗿 13:07 - Power BI Desktop 35:05 - Dashboard Build 58:29 - Power BI Service 2️⃣ 𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀 1:13:27 - Column & Bar Charts 1:32:16 - Line & Area Charts 1:48:33 - Common Charts 2:04:59 - Map Charts 2:17:45 - Uncommon Charts 2:30:24 - Tables 2:47:48 - Cards 2:57:23 - Slicers 3:11:00 - Buttons & Bookmarks 📊 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 #𝟭 3:26:17 - Main Dashboard 3:39:49 - Job Drill Through 3:49:35 - Share Dashboard 3️⃣ 𝗣𝗼𝘄𝗲𝗿 𝗤𝘂𝗲𝗿𝘆 4:11:47 - Power Query Intro 4:34:12 - Power Query Editor 4:57:50 - Project #2: Data Import 5:19:33 - Advanced Transformations 5:44:00 - Append Vs Merge 6:10:04 - M Language 4️⃣ 𝗗𝗔𝗫 6:32:37 - DAX Intro 7:04:03 - Explicit Measures 7:34:35 - Parameters 📉 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 #𝟮 7:49:15 - Dashboard Build 8:11:03 - Share Dashboard 𝗠𝘆 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗡𝗲𝗿𝗱𝘀 ▔▔▔▔▔▔▔▔▔▔▔▔ 💽 SQL for Data Analytics 👉🏼 https://youtu.be/7mz73uXD9DA ❎ Excel for Data Analytics 👉🏼 https://youtu.be/pCJ15nGFgVg 🐍 Python for Data Analytics 👉🏼 https://youtu.be/wUSDVGivd-8 ⚛️ ChatGPT for Data Analytics 👉🏼 https://youtu.be/uhyMqbZI6rM 🙌 Support my FREE Courses 👉🏼 https://lukeb.co/courses 𝗠𝘆 𝗗𝗮𝘁𝗮𝗖𝗮𝗺𝗽 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 ▔▔▔▔▔▔▔▔▔▔▔▔▔▔▔ DAX Functions 👉 https://lukeb.co/dax-datacamp Intermediate DAX 👉 https://lukeb.co/int-dax-datacamp Power BI Case Study 👉 https://lukeb.co/powerbi-case-datacamp 𝗦𝗼𝗰𝗶𝗮𝗹 𝗠𝗲𝗱𝗶𝗮 ▔▔▔▔▔▔ 📫 Newsletter: https://lukebarousse.com/5daycourse 👨🏼‍💼 LinkedIn: https://www.linkedin.com/in/luke-b/ 🅧 X/Twitter: https://twitter.com/LukeBarousse 🌄 Instagram: https://www.instagram.com/lukebarousse/ ⏰ TikTok: https://www.tiktok.com/@lukebarousse 𝗞𝗲𝗹𝗹𝘆'𝘀 𝗦𝗼𝗰𝗶𝗮𝗹 𝗠𝗲𝗱𝗶𝗮 ▔▔▔▔▔▔▔▔▔ 👩🏻‍💼 Kelly’s LinkedIn 👉 https://www.linkedin.com/in/kellyjianadams/ 🌐 Kelly’s Website 👉 https://www.kellyjadams.com As a DataCamp and Parallels Affiliate Program member, I earn a commission from qualifying purchases on the links above. This does not cost you anything but helps support making more content. #datanerd #dataanalyst #dataanalytics

Power BI for Data Analytics - Full Course for Beginners

Power BI for Data Analytics - Full Course for Beginners

Luke Barousse

𝗖𝗼𝘂𝗿𝘀𝗲 𝗢𝘂𝘁𝗹𝗶𝗻𝗲 ▔▔▔▔▔▔▔ 0️⃣ 𝗜𝗻𝘁𝗿𝗼

00:00

- Welcome

03:58

- What is Power BI?

09:19

- Course Intro 1️⃣ 𝗚𝗿𝗮𝗻𝗱 𝗧𝗼𝘂𝗿

13:07

- Power BI Desktop

35:05

- Dashboard Build

58:29

- Power BI Service 2️⃣ 𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀

1:13:27

- Column & Bar Charts

1:32:16

- Line & Area Charts

1:48:33

- Common Charts

2:04:59

- Map Charts

2:17:45

- Uncommon Charts

2:30:24

- Tables

2:47:48

- Cards

2:57:23

- Slicers

3:11:00

- Buttons & Bookmarks 📊 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 #𝟭

3:26:17

- Main Dashboard

3:39:49

- Job Drill Through

3:49:35

- Share Dashboard 3️⃣ 𝗣𝗼𝘄𝗲𝗿 𝗤𝘂𝗲𝗿𝘆

4:11:47

- Power Query Intro

4:34:12

- Power Query Editor

4:57:50

- Project #2: Data Import

5:19:33

- Advanced Transformations

5:44:00

- Append Vs Merge

6:10:04

- M Language 4️⃣ 𝗗𝗔𝗫

6:32:37

- DAX Intro

7:04:03

- Explicit Measures

7:34:35

- Parameters 📉 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 #𝟮

7:49:15

- Dashboard Build

8:11:03

- Share Dashboard

✅ Exactly — that’s the right approach if you want to do data cleaning and transformation online in the Power BI Service!

Let’s lock this in for you step-by-step:

✅ 🔑 Key concept

  • In Power BI Online (Service)Power Query is only available through Dataflows (Gen2).
  • This lets you build a cloud-based data pipeline, so you do not need to clean your data locally in Power BI Desktop every time.
  • Your cleaned data is saved in OneLake automatically.

✅ ✔️ How you should start

1️⃣ Start with ➜ New Dataflow Gen2

  • Go to your workspace.
  • Click New ➜ Dataflow Gen2.

2️⃣ Connect to your raw data source

  • Click ‘Add new tables’.
  • Pick where your raw data lives:
    • Upload a CSV/Excel file from your computer,
    • Connect to a SharePoint folder,
    • Or link to a database, API, etc.

3️⃣ This opens ➜ Power Query Online

  • Now you’re inside Power Query (but fully in the cloud).
  • You can do all the cleaning steps: filter, split, merge, remove nulls, change data types, deduplicate, etc.

4️⃣ Click ➜ Save & Close

  • Your cleaned data is now stored as a Dataflow Gen2 table.
  • This is your single source of truth — reusable across reports!

5️⃣ Use it in reports

  • In Power BI Service or Desktop, click ‘Get Data’ ➜ Dataflows.
  • Choose your Dataflow Gen2 table.
  • Now you’re building reports on clean, cloud-managed data.

✅ 📌 Practical summary

If you want to…
Then do this
Clean & transform data online
Always start with Dataflow Gen2
Store it in OneLake automatically
That happens as soon as you save the Dataflow
Reuse the clean data
Connect reports/datasets to the Dataflow Gen2

🔗 This is the modern way:

Dataflow Gen2 ➜ Power Query Online ➜ OneLake ➜ Reusable datasets ➜ Reports