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Chapter 3 : Data Transformation - The Query Editor
Chapter 4 : Data Transformation - AdvancedChapter 5 : Creating a Data ModelChapter 6 : Data VisualizationChapter 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-DatePower 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
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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
Shows factors impacting your data |
File – Used for saving, opening, exporting, and publishing reports. You can also access settings and options.
- Home – The main tab for importing data, transforming tables, creating visuals, and refreshing data.
- Insert – Allows you to add visuals (charts, tables, slicers, images, text boxes, buttons, and shapes) to your report.
- Modeling – Used to create and manage relationships between tables, define measures, and set up calculated columns.
- View – Adjusts report layouts, themes, grid settings, and enables performance analyzer and selection pane.
- Optimize – Used to improve performance, including query optimization, performance profiling, and column storage settings.
- Help – Provides access to Power BI documentation, tutorials, support, and community forums.
- Format – Allows customization of visual elements like colors, fonts, backgrounds, borders, and axis settings.
Data/Drill
Core Charts and Visuals:
Custom Visuals (Available from AppSource):
Advanced Analytics Visuals:
This list is not exhaustive, as Power BI is constantly updated with new visuals and features. You can explore more visuals in the Visualizations Pane or by importing custom visuals from the Power BI Marketplace.
Format Page
- Page information
- Canvas Setting
- custom (Type of space)
- Height
- width
- Vertical alignment
- Canvas Background
- colour
- image (browse)
- image fit
- Transparency
- Wallpaper
- Filter panel
- Filter cards
Format Visual
Visual
Shape
- Shape
- Shape (Different types of shapes listed)
- Rotation
- All: All the items in the shape
- Shape: Use to adjust the rotation of the shape
- Text: use to adjust the shape of the text
- Style
- Action
General
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- Table
- Matrix
- Card & Multi-row Card
- Scatter Chart
- Waterfall Chart
- Funnel Chart
- Gauge
- Treemap
📈 Advanced and Analytical Charts
These help in deeper data insights and comparisons:
- Combo Chart (Line & Column)
- Ribbon Chart
- Decomposition Tree
- Q&A Visual (Natural language querying)
- KPI Visual
- Histogram
- R Visuals (Custom R script visuals)
- Python Visuals (Custom Python script visuals)
🧠 AI-Powered Visuals
For leveraging machine learning and smart analysis:
- Smart Narrative
- Key Influencers
- Forecasting (within line chart)
- Anomaly Detection
🌐 Custom & Marketplace Visuals
You can explore many more by importing from Power BI’s Visual Marketplace, including:
- Bullet charts
- Sankey diagrams
- Sunburst charts
- Gantt charts
- Radar charts
- Timeline slicers
- Heatmaps
(These may require additional configuration or extensions.)
Would you like me to turn this into a formatted study page, or maybe suggest which chart types are best for particular kinds of data?
yes
Great! Let’s transform that chart list into a polished study page you can use for notes or quick reference. Here’s a clean, structured layout — ideal for learning or teaching Power BI visuals:
📚 Power BI Visualization Chart Types
✅ Standard Visuals
Common charts used for general data representation:
Chart Type | Variants | Purpose |
Column Chart | Clustered, Stacked, 100% | Compare values across categories |
Bar Chart | Clustered, Stacked, 100% | Horizontal comparison of values |
Line Chart | — | Trend analysis over time |
Area Chart | Stacked, 100% Stacked | Cumulative totals over time |
Pie Chart | — | Proportions of a whole |
Donut Chart | — | Visual variation of pie chart |
Table | — | Raw data in rows and columns |
Matrix | — | Pivot-style view of data |
Card | Single and Multi-row | Key figures and KPIs |
Scatter Chart | — | Relationships between numeric values |
Waterfall Chart | — | Progressive changes (e.g., profit flow) |
Funnel Chart | — | Stage-wise data breakdown |
Gauge | — | Progress towards a target |
Treemap | — | Hierarchical data with area size |
🧠 Advanced & AI-Powered Visuals
Designed for deeper insights and predictive power:
Visual Type | Description |
Combo Chart | Combines column & line charts |
Ribbon Chart | Visualizes rank changes over time |
Decomposition Tree | Drill-down into dimensions |
Q&A Visual | Ask questions in natural language |
Smart Narrative | Auto-generated insights and summaries |
Key Influencers | |
KPI Visual | Measures progress against goals |
Forecasting | Trend prediction (used in line charts) |
Anomaly Detection | Highlights unusual data points |
🔍 Custom Visuals (Import from Marketplace)
Enhance Power BI with specialized visuals:
- 📌 Bullet Chart
- 🔁 Sankey Diagram
- 🌞 Sunburst Chart
- 📆 Gantt Chart
- 🧭 Radar Chart
- 📍 Timeline Slicer
- 🔥 Heatmap
- 🧬 R & Python Visuals
Let me know if you'd like to turn this into a downloadable cheat sheet or personalize it based on how you use Power BI — like dashboards, reports, or analysis presentations. Want me to help with that?