Data Cleaning in Tableau

Why Clean Data?

Dirty data = Wrong results. Always clean your data first!

Common Data Problems

• Missing values
• Wrong data types
• Duplicate rows
• Inconsistent names (NY vs New York)
• Extra spaces

Cleaning in Data Source Tab

1. Rename Columns

• Right-click column header
• Select "Rename"
• Type new name

2. Change Data Types

• Click data type icon
• Select correct type

3. Hide Unused Columns

• Right-click column
• Select "Hide"

4. Split Columns

For "John Smith" to "John" and "Smith":

• Right-click column
• Select "Split"

Using Data Interpreter

Tableau can auto-clean Excel files:

1. Connect to Excel
2. Check "Use Data Interpreter"
3. Tableau removes headers, footers, etc.

Filtering Bad Data

Remove unwanted rows:

1. Go to Data Source tab
2. Click "Add" under Filters
3. Set your filter conditions

Handling Nulls

Null = Missing value

Options:

• Filter out nulls
• Replace with 0
• Replace with average

To replace nulls:

1. Create calculated field
2. Use: IFNULL([Field], 0)

Fixing Inconsistent Names

"USA", "U.S.A", "United States" should be same:

1. Right-click the field
2. Select "Aliases"
3. Map different names to one value

Pivot Data

Convert columns to rows:

1. Select columns to pivot
2. Right-click
3. Select "Pivot"

Good for:

• Months as columns → Months as rows
• Years as columns → Years as rows

Quick Cleaning Checklist

• Check data types
• Remove duplicates
• Handle missing values
• Fix inconsistent names
• Remove unnecessary columns

Summary

Clean data before analyzing. Use Data Source tab for renaming, filtering, and fixing issues!