This session introduced learners to the core fundamentals of Power BI, with a strong emphasis on data extraction, transformation, and basic visualization techniques. The focus was on building a solid foundation for working with real-world datasets using Power Query, enabling participants to confidently move from raw data to meaningful insights.

🔧 Technical Setup & Environment Readiness

The session began with a technical setup walkthrough, ensuring all participants had:

• ✅ The correct version of Power BI Desktop installed

• 📁 Access to the practice datasets

• 📦 Proper extraction of downloaded files

A key concept highlighted early was Power BI’s philosophy of working with tables and structured data, rather than individual Excel cells—an essential mindset shift for effective BI development.

🔌 Connecting to Multiple Data Sources

Participants explored how Power BI connects to a wide range of data sources, including:

• 📊 Excel workbooks and folders

• 🗂️ Shared OneDrive directories

• 🗄️ Databases and cloud platforms

The importance of choosing the right data source (tables vs sheets) was emphasized to avoid data inconsistencies and transformation errors.

🔄 Data Transformation with Power Query

A major part of the session focused on Power Query, the engine behind data preparation in Power BI. Learners practiced:

• 🧹 Cleaning and shaping data

• ➕ Appending queries from multiple files

• 🔗 Combining datasets from folders

• 🧠 Managing data types and metadata

• ⚠️ Identifying and handling errors

The difference between duplicating queries and referencing queries was clearly explained, helping participants understand performance optimization and dependency management.

🧩 Understanding References, Duplicates & Data Flow

Participants learned:

• 📌 Duplicates create independent copies of queries

• 🔁 References remain linked to the original query and update automatically

They also explored how Power BI behaves as a data receptor, meaning source changes require manual refreshes rather than automatic updates.

☁️ Data Integration & Automation Strategies

The session covered practical approaches to:

• 📁 Automate weekly and monthly reports using shared folders

• 🔄 Refresh datasets with minimal manual effort

• 🏗️ Understand data maturity levels—from Excel-based workflows to data warehousing

Cloud concepts like DirectQuery were introduced as preferred solutions for handling large datasets efficiently.

📈 From Data to Visuals: Scatter Chart Exercise

To conclude, participants applied their learning in a hands-on exercise:

• 📊 Transformed data was visualized using scatter charts

• 🔄 Data refresh and source updates were tested

• 🛠️ Common visualization issues were identified and resolved

Despite minor technical challenges during screen sharing, learners successfully connected data preparation with visualization outcomes.

🎯 Key Takeaways

• Power Query is the backbone of clean, scalable Power BI reports

• Structured data and templates save time and reduce errors

• Automation and folder-based reporting enable real-time insights

• Visualization becomes easier when data is properly prepared

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