🎯 What You'll Learn

📋 Before You Begin

🗝️ Which Connectors Can You Try Right Now?

⚡ Beginner ⏱ ~3 min

Not all connectors need a paid subscription. Use this table to pick the easiest ones to start with today.

#ConnectorAccount NeededDifficulty
2Google BigQueryGmail (free)● Easy
4OData Feed — NorthwindNone● Easy
5GitHub APINone● Easy
8Python ScriptPython installed● Medium
1SnowflakeFree trial (30 days)● Medium
7SharePoint FolderMicrosoft (work/school)● Medium
9PDF ExtractionNone (any PDF URL)● Medium
6SQL ServerAzure free tier or local● Hard
3Azure Open DatasetsAzure free trial● Hard
10Microsoft Fabric / OneLakeFabric trial (60 days)● Hard

🔌 10 Connector Exercises

⚡ Intermediate ⏱ ~25 min

Use the tabs to browse connectors by category, then expand each exercise.

1 ❄️ Snowflake: The Cloud Data Warehouse
SOURCESign up for a Snowflake Free Trial (30 days). Find "Snowflake Public Data" in the Snowflake Marketplace.
TASKIn Power BI: Get Data → Snowflake. Enter your server URL from the Snowflake account details page.
GOALConnect to FINANCIAL_MARKET_DATA and create a KPI Card showing the latest USD → EUR Foreign Exchange rate.
Cloud DBGet DataVisualise
2 🌐 Google BigQuery: Public Data (Free)
SOURCEGet Data → Google BigQuery. Sign in with Gmail. First 1 TB of processing per month is free.
TASKNavigate to bigquery-public-data and find the covid19_jhu_csse dataset.
GOALUse the Map visual to show "Confirmed Cases" by Country. Darker = more cases.
Cloud DBVisualise
3 🌤️ Azure Open Datasets: Real-Time Weather
SOURCESearch "Azure Open Datasets" and look for NOAA Integrated Surface Data. Get the Azure Blob URL.
TASKUse Get Data → Azure → Azure Blob Storage. Paste the NOAA dataset URL to connect.
GOALA Line Chart showing temperature fluctuations over the last 24 hours. Time on X-axis, temp on Y-axis.
AzureVisualise
4 📋 OData Feed: Northwind Traders (No Account Needed)
SOURCEGet Data → OData Feed → paste URL: https://services.odata.org/V3/Northwind/Northwind.svc/
TASKSelect the Orders and Order_Details tables. In Model View, link them by OrderID.
GOALA report showing Total Sales by Employee. This is a classic relational data exercise — two tables, one relationship.
OData APIModelVisualise
5 🐙 GitHub API: Repository Commit History
SOURCEGet Data → Web → paste: https://api.github.com/repos/microsoft/powerbi-desktop-samples/commits
TASKPower BI loads JSON. In Power Query: Convert to Table → expand the "commit" column → expand "author" to get name and date.
GOALA Table Visual listing the last 20 contributors who committed code to that repository.
REST APIJSONClean Data
6 🗄️ SQL Server: AdventureWorks + DirectQuery
SOURCEUse SQL Server on Azure Free Trial or install SQL Express locally. Restore the AdventureWorks sample database.
TASKGet Data → SQL Server. Import the Sales table. Then try connecting again in DirectQuery mode.
GOALUnderstand the key difference: in DirectQuery, Power BI sends SQL queries live — data never loads into the .pbix file.
SQL ServerDirectQuery
7 📁 SharePoint Folder: Auto-Combine Files
SOURCEGet Data → SharePoint Folder. Enter your school or work SharePoint/OneDrive URL.
TASKUpload 3 identical Excel files (Sales Jan, Sales Feb, Sales Mar) to one folder. Use "Combine Files" in Power Query.
GOALAdd a "Sales Apr" file to the folder and click Refresh in Power BI — the new month appears automatically in all charts. No re-importing needed.
SharePointAuto-Refresh
8 🐍 Python Script: Generate Data with pandas
SOURCEGet Data → Python script
TASKPaste the script below into the editor. Power BI will run it and load the resulting DataFrame as a table.
GOALCreate a Bar Chart from this script-generated table. The same technique works for ML model outputs.
python
import pandas as pd
data = {
    'Name': ['Alice', 'Bob', 'Carol', 'David'],  # list of names
    'Score': [95, 80, 88, 72]                     # corresponding scores
}
df = pd.DataFrame(data)  # Power BI reads this df variable
Result in Power BI
A table with 4 rows: Name (Text) | Score (Decimal Number)
PythonpandasCustom Data
9 📄 PDF Data Extraction: Annual Reports
SOURCEGet Data → PDF. Use a URL to a company's Annual Financial Report (public PDFs work perfectly).
TASKPower BI scans the PDF for tables. Select the "Balance Sheet" table. In Power Query, remove "Totals" rows (filter out rows where column = "Total").
GOALA Waterfall Chart showing income and expense categories — visually reveals where money comes from and where it goes.
PDFClean DataVisualise
10 🏗️ Microsoft Fabric / OneLake: Live Connection (2026 Standard)
SOURCEGet Data → Microsoft Fabric → Lakehouses. Requires a Fabric-enabled Microsoft tenant (60-day trial available).
TASKCreate a "Lakehouse" in Fabric. Upload a CSV there. Connect Power BI to it using Live Connection mode.
GOALZero data loading — Power BI "sees" the data where it lives in OneLake. This is the most modern architecture for Power BI in 2026.
FabricOneLakeLive Connection

⚡ Import vs. DirectQuery — What's the Difference?

⚡ Intermediate ⏱ ~4 min

This is one of the most important architectural decisions you'll make in Power BI.

AspectImport ModeDirectQuery Mode
Data locationCopied into the .pbix fileStays in the database
SpeedFast (data is local)Slower (live SQL queries)
FreshnessOnly fresh on RefreshAlways live / real-time
File sizeCan get largeVery small (.pbix)
DAX supportFull DAX supportLimited DAX functions
Best forStatic/daily data, complex DAXReal-time dashboards, large DBs

🧠 Practice Quiz

⚡ Intermediate ⏱ ~5 min

Q1. You paste the GitHub API URL into "Get Data → Web". Power BI loads it as JSON. What is your FIRST step in Power Query?

Q2. In DirectQuery mode, what happens when you click a slicer on your report?

Q3. You upload "Sales Jan", "Sales Feb", and "Sales Mar" as identical Excel files to a SharePoint folder. After using "Combine Files", you add "Sales Apr". What do you do in Power BI to see April's data?

Q4. In the Python script connector, what variable name must your DataFrame use so Power BI can read it?

Q5. What visual type best shows income and expense categories in a financial report to reveal where money flows?

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🏁 Key Takeaways — Part 2