Day 3 – Power BI Components and Power Query Editor (ETL Process)

⚙️ Day 3 – Power BI Components and Power Query Editor (ETL Process)

Introduction

On Day 3 of our Power BI Learning Series, we’ll explore the core components of Power BI and take a deep dive into the first and most important one — the Power Query Editor, which handles data cleaning and transformation (ETL: Extract, Transform, Load).

🔹 Components of Power BI

Power BI is built on five key components, each serving a unique purpose in the data analysis process.

🧩 Module 1: Power Query Editor (ETL – Extract, Transform, Load)

What Is Power Query Editor?

The Power Query Editor is an inbuilt ETL tool within Power BI Desktop. It allows users to connect, clean, and transform raw data before loading it into the model for reporting.

🔹 What Is the Use of an ETL Tool?

The ETL (Extract, Transform, Load) process helps clean and prepare data for analysis.
It converts unstructured data into a structured format — ready to be used in Power BI dashboards and reports.

🧼 Data Cleaning

Data cleaning ensures your dataset is error-free, consistent, and formatted correctly.
Power Query Editor provides several built-in options to perform these tasks quickly and efficiently.

🧭 Menu Tabs in Power Query Editor

The Power Query Editor interface includes several menu cards (tabs) for performing different operations:

1. Home

2. Transform

3. Add Column

4. View

5. Tools

6. Help

🔹 Data Transformation in Power Query Editor

Transformation refers to changing or shaping data to make it suitable for reporting. Below are some of the key transformation operations:

1. Use Headers as First Rows

2. Use First Rows as Headers

3. Transpose

4. Reverse Rows

5. Count Rows

6. Change Data Types

🔸 Data Types in Power BI

Understanding data types is essential for accurate calculations and visualization.

1. Number

• Decimal Number: 1.2

• Fixed Decimal Number: Used for currency values ($)

• Whole Number: 123

• Percentage: %

2. Text

• Includes letters, numbers, and special characters (A–Z, a–z, 0–9)

3. Date & Time

• Date: Calendar icon

• Time: Clock icon

• Date/Time: Calendar with clock

• Date/Time/Time Zone: Globe with clock

• Duration: Stopwatch icon

4. True/False (Boolean Type)

Used for logical conditions (e.g., Yes/No)

5. Binary

Represents data in 0 and 1 format.

🔹 Other Transformation Operations

7. Detect Data Type

8. Rename Columns

9. Replace Values

10. Fill: Up / Down

11. Move Columns: Left / Right / To Beginning / To End

12. Convert to List

13. Split Columns:

• By Delimiter

• By Number of Characters

• By Positions

• By Lowercase to Uppercase

• By Uppercase to Lowercase

• By Digit to Non-Digit

• By Non-Digit to Digit

14. Unpivot Columns: Convert columns into rows

15. Pivot Columns: Convert rows into columns

💡 Summary

In Day 3, we explored the core components of Power BI and began our first deep-dive into the Power Query Editor — the foundation for all data cleaning and transformation tasks.
Mastering ETL processes in Power Query is the first step toward building accurate and meaningful dashboards in Power BI.