👁️ Power BI Power Query “View” Tab – Full Walkthrough for Clean Data Insights

🖥️ By TechTown.in
📅 Updated: June 2025
🔍 Keywords: Power Query View tab, Data preview options, Column profiling, Power BI data quality, Query dependencies

sample data:

techtown_sales_dataDownload

🔰 Introduction

Before analyzing any data in Power BI, it’s crucial to inspect and understand your dataset inside Power Query Editor.

That’s where the “View” tab steps in.

It gives you powerful tools for profiling, debugging, and analyzing the structure and health of your data — all visually. From column quality to query dependencies, this tab helps ensure your data is accurate and clean before loading it into your model.

📸 What You See in the Screenshot

  • Green/Red indicators for each column (Valid/Error/Empty)
  • Distinct/Unique values per column
  • Column statistics and value distribution
  • Options like Query Dependencies, Formula Bar, Column Profile, and more

Let’s explore each part.

🔍 Full Breakdown of the “View” Tab Options

📋 1. Formula Bar

✅ Toggle ON/OFF to show the formula (M code) behind every transformation step.

📌 Example (visible in your image):

Table.TransformColumnTypes(...)

Helps you:

  • Understand Power Query logic
  • Edit or tweak steps manually
  • Debug faster

🧾 2. Column Quality

Shows data health via colored dots above each column:

  • 🟢 Valid = Correct data
  • 🔴 Error = Invalid values (e.g., divide by zero)
  • ⚪ Empty = Missing values (null)

In your screenshot:
✅ All columns are 100% Valid (clean dataset)

📊 3. Column Distribution

Displays a bar chart showing:

  • How often each value appears
  • Total count of distinct values
  • Total count of unique values

📌 Example from your image:

  • CustomerID: 10 distinct, 10 unique
  • ProductCategory: 5 distinct, 0 unique (shows duplicates)

This helps:

  • Spot duplicates
  • Detect skewed data
  • Understand frequency

📈 4. Column Profile

When enabled, it shows detailed statistics for each column in a separate section (bottom panel).

Includes:

  • Data type
  • Count
  • Distinct count
  • Min/Max
  • Average (if numeric)
  • Error count

🧠 From your screenshot, Date column profile shows:

  • 10 values
  • 10 unique
  • 0 errors
  • Distribution chart

📦 5. Show Whitespace

Highlights leading or trailing spaces in string columns.

Useful to:

  • Identify invisible formatting issues
  • Clean up imported CSV/Excel data
  • Avoid joins failing due to hidden spaces

🗃️ 6. Go to Column

Quick navigation tool. If your table has 50+ columns, this is a life-saver.

Lets you jump to any column by name instead of scrolling endlessly.

📐 7. Advanced Editor

Opens the entire query script in M language.

  • View the full transformation logic
  • Edit multiple steps at once
  • Copy-paste transformations to another query

🧠 Use it if you want full control or are working with reusable templates.

🔗 8. Query Dependencies

A visual diagram of how queries are connected in Power BI.

Shows:

  • Which tables depend on which source
  • Merges, joins, or references
  • Data flow between queries

📌 Example use:
If your Sales query pulls from Product and Customer, dependencies map it clearly.

🧪 9. Parameters (if any exist)

If you have defined parameters (like file paths or filter values), they’ll appear here for editing or inspection.

This is dynamic and only visible if parameters exist in your PBIX or Query file.

🎓 Real-World Example from Your Data

Looking at your dataset techtown_sales_data_jan2025, here’s what the View tab reveals:

ColumnValidDistinctUniqueEmptyUse Case
Date✅ 100%10100%Clean date analysis
OrderID✅ 100%10100%Track orders uniquely
CustomerID✅ 100%10100%Join with customer table
ProductCategory✅ 100%500%Great for grouping
ProductName✅ 100%10100%Use for tooltip/details

This quick view helps you:

  • Spot missing values instantly
  • Understand uniqueness
  • Prepare for relationship modeling

✅ Benefits of Using the “View” Tab

  • ✅ No need to write code — visual profiling
  • ✅ Catch errors before they break reports
  • ✅ Great for large datasets
  • ✅ Ideal for beginner and pro Power BI users
  • ✅ Keeps data quality front and center

🧠 Pro Tips

  • Always enable “Column Quality + Profile + Distribution” when working with new datasets
  • Use Query Dependencies before combining queries
  • Turn on Formula Bar permanently for better debugging
  • Use Whitespace Check to fix join issues early

🛠️ Learn More

🏁 Conclusion

The View tab in Power Query Editor is not just for “viewing” — it’s for validating, cleaning, and mastering your data. Before writing DAX, creating visuals, or publishing dashboards — ensure your data is error-free, structured, and trustworthy.

👉 Master this tab to become a Power BI data detective!