📊 Power Query – Data Type, Fill, Replace Value & Move | Episode 12
Welcome to Episode 12 of the complete Power Query tutorial series by Dr. Banshilal Patidar.

🎬 Download dataset :- https://drive.google.com/drive/folder...

In this practical episode, we will learn some of the most useful Power Query transformation and data-cleaning functionalities:
🔹 Data Type
🔹 Fill Up / Fill Down
🔹 Replace Values
🔹 Replace Errors

These tools are essential for preparing messy datasets and creating clean, reliable data models in Power BI.
📌 In this episode, you will learn:
✅ Understanding Data Types in Power Query
✅ Text, Whole Number, Decimal Number and Date data types
✅ Date/Time and other commonly used data types
✅ How to change a column's Data Type
✅ Why choosing the correct Data Type is important
✅ Fill Down functionality
✅ Fill Up functionality
✅ Filling missing values using previous records
✅ Filling missing values using following records
✅ Replace Values functionality
✅ Replacing text values
✅ Replacing numeric values
✅ Replacing errors and unwanted values
✅ Finding and replacing incorrect data
✅ Move Column functionality
✅ Move columns Left / Right
✅ Reordering columns for better data organization
✅ Understanding Applied Steps
✅ Understanding the M code generated by Power Query
✅ Common mistakes and best practices

🔢 1. Data Type
We will understand why Data Type is one of the most important concepts in Power Query.
For example:
Sales → Decimal Number
Quantity → Whole Number
Order Date → Date
Customer Name → Text
Using the correct data type helps Power Query and Power BI perform calculations and analysis correctly.

⬇️ 2. Fill Down & Fill Up
Many real-world Excel and report files contain blank cells where the value is intended to continue from the previous or next row.
You will learn how to use:
📌 Fill Down – Fill blank cells using the value above.
📌 Fill Up – Fill blank cells using the value below.
This is particularly useful when cleaning hierarchical reports, departmental data and exported Excel files.

🔄 3. Replace Values
We will learn how to replace incorrect, inconsistent or unwanted values.
For example:
Gujrat → Gujarat
M → Male
F → Female
N/A → null
You will also learn how replacing values can help standardize data before creating Power BI reports.

↔️ 4. Move Columns
We will learn how to organize columns using the Move functionality.
You can move columns:
➡️ To the Left
➡️ To the Right
This helps create a logical and easy-to-understand dataset structure.
🎯 Practical Classroom Example
We will take a messy Sales Dataset and perform the following transformations:
1️⃣ Correct the Data Types
2️⃣ Fill missing category values
3️⃣ Fill Down department information
4️⃣ Replace incorrect spellings
5️⃣ Replace unwanted values
6️⃣ Move important columns into the required order
7️⃣ Review the Applied Steps
8️⃣ Check the final cleaned dataset
By the end of this episode, you will be able to use these important Power Query tools to clean, standardize and organize real-world data.

👨‍🏫 Instructor:
Dr. Banshilal Patidar

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💡 Question for you:

Which Power Query functionality do you use most often — Fill Down, Replace Values, Data Type, or Move Columns?
Comment your answer below! 👇

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