When it comes to reporting and analytics, the quality of your insights depends on the quality of your data. In our recent session, the spotlight was on unpivoting, combining, cleaning, and transforming data in Excel and Power BI—skills every data enthusiast needs in their toolkit.

Let’s walk through the highlights 👇

🔄 Unpivoting: Turning Columns into Rows for Better Reporting

The session began with a deep dive into unpivoting—a process that restructures your data for accurate analysis.

• Why it matters: Many raw datasets come with month names or other categories as columns, which makes analysis tricky.

• How it works: Highlight the relevant columns → click “Unpivot Columns” → transform them into a clean, analysis-ready structure.

• Real-life example: Converting month columns in a financial statement into a single “Month” column for dynamic reporting.

📑 Managing Multiple Tables in Excel & Power BI

Working with multiple tables? The key is formatting.

• In Excel: Format each dataset as a table before importing it.

• In Power BI: Load each table independently for better data control and accuracy.

• Pro Tip: Use consistent naming and structure to make merging and transformations smoother.

📂 Combining Data from Multiple Sheets

When your data lives across multiple sheets, there are two main strategies:

1. Manual Combining: Load each sheet, then append them together.

2. Folder Approach: Store all Excel files in a folder → use Power BI’s “Combine & Transform Data” to merge them in one go.

Why it works: This ensures consistency and reduces repetitive manual work. Selecting the right sample file during the process guarantees all relevant data is included.

🛠 Data Transformation & Cleaning Techniques

Data is rarely perfect—but Power BI gives you powerful tools to fix that.

• Splitting Columns: Use delimiters to break data into separate fields (e.g., splitting a “Description” column into multiple parts).

• Merging Columns: Combine related fields like “City” and “Country” into one.

• Handling Null Values: Decide when to keep or remove nulls—sometimes they carry meaning!

➕ Creating Custom Columns

For more tailored analysis, create custom columns—such as calculating total sales after discounts.

• Ensure correct formula syntax for accurate results.

• Use AI tools like ChatGPT to help write complex formulas faster.

🔗 Merging Queries the Right Way

Combining datasets? Choosing the right join type is crucial:

• Left Outer Join: Keeps all records from the first table and matches from the second.

• Always match join type to your reporting needs to avoid missing or duplicated data.

💾 Saving & Organizing Your Power BI Projects

Data projects grow fast—keep them organized!

• Save projects with clear names and folder structures.

• Maintain an archive for previous versions so you can revisit past work when needed.

📅 The Road Ahead: Data Modeling

The next step? Data modeling in Power BI. By structuring relationships between your tables, you’ll unlock even deeper insights. The takeaway? Practice today’s techniques now so you’re ready for the next big leap.

✨ Your Action Plan:

1. Practice unpivoting and combining data in Power BI.

2. Try formatting multiple tables in Excel and importing them.

3. Experiment with creating and merging custom columns.

🚀 Ready to level up your skills?

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