Data Analytics Mindset: Tip 1 - Unpivot Columns

Key Principle:

Think minimal, automated, and perpetual

• Minimal: Keep your data tidy and free from unnecessary complexity.

• Automated: Build processes that minimize manual intervention.

• Perpetual: Ensure your solution works seamlessly over time without frequent updates.

Recognize Patterns That Need Unpivoting:

Your subconscious mind should act like a data detective. If you notice similar data in multiple columns, ask yourself:

1. Why are these in different columns?

2. Can I organize them into one column to simplify analysis?

Examples:

1. Years as Columns: Columns named 2021, 2022, 2023, etc., indicate that years are attributes and should be in a single column like Year, with a corresponding column for Value.

2. Products as Columns: Columns named Apple, Banana, and Orange with sales figures are also attributes that belong in a single column, such as Product.

Why Unpivot?

1. Simplifies Analysis: Centralizing data makes it easier to filter, group, and analyze without manual adjustments.

2. Enhances Automation: Unpivoted data works better with Power BI’s native features like slicers, visuals, and DAX calculations.

3. Avoids Duplication: Redundant data structures increase the risk of errors and manual fixes.

Tools for Unpivoting:

Power Query offers three options to unpivot:

1. Unpivot Columns:Use when you want to unpivot specific columns while keeping the rest of the table intact.

2. Unpivot Other Columns:Use when you want to unpivot all columns except selected ones.

3. Unpivot Selected Columns:Use when you need to unpivot only a subset of columns without affecting others.

Caution!

• Avoid Duplication: If you unpivot once and then attempt to unpivot additional columns, you might accidentally duplicate data. Always inspect your data structure to prevent this.

• Plan Ahead: Ensure that your data model won’t require re-unpivoting later, as this adds complexity.

Outcome:

By unpivoting data, your Power BI dashboards and calculations become:

1. Less manual.

2. More scalable.

3. Easier to maintain.

Always strive for clean, organized, and efficient datasets.