Data Cleaning

Pro

Clean and transform your data with 14+ built-in operations. Fix messy columns, parse dates, remove duplicates, and more.

Pro Feature

Data cleaning is available on Pro, Business, and Enterprise plans.Upgrade to Pro

Why Clean Your Data?

Real-world data is messy. Common issues include:

✗Inconsistent date formats (01/15/2024 vs Jan 15, 2024)
✗Mixed data types in columns (numbers stored as text)
✗Duplicate rows from data imports
✗Extra whitespace and inconsistent capitalization
✗Missing values that need default values

DATIRA's data cleaning tools help you fix these issues so your reports are accurate and meaningful.

Getting Started with Data Cleaning

1
Open a data source
Click on any data source in your workspace
2
Click "Clean Data"
Or click the icon in the toolbar
3
Select a transformation
Choose from the list of 14+ cleaning operations
4
Configure and preview
Set options and preview the result before applying
5
Apply the transformation
Click "Apply" to save. All transformations are tracked in history.

Transformation Reference

Here are all available data cleaning operations:

Split Column

Split one column into multiple columns using a delimiter (comma, space, etc.)

"John Smith" → "John" | "Smith"

Merge Columns

Combine two or more columns into one with a separator

"First" + "Last" → "First Last"

Rename Column

Change column names to something more meaningful

"col1" → "Customer Name"

Change Data Type

Convert columns to text, number, date, or boolean

"123" (text) → 123 (number)

Parse Dates

Convert date strings to proper date format

"2024-01-15" → Date object

Format Dates

Standardize date display format

"Jan 15, 2024" → "2024-01-15"

Find & Replace

Replace specific values with new values

"N/A" → "" (empty)

Trim Whitespace

Remove leading/trailing spaces from text

" hello " → "hello"

Change Case

Convert text to uppercase, lowercase, or title case

"HELLO" → "Hello"

Remove Duplicates

Delete duplicate rows based on selected columns

100 rows → 85 unique rows

Filter Rows

Keep only rows that match specific conditions

Status = "Active"

Sort Rows

Reorder data by one or more columns

Sort by Date descending

Fill Empty Values

Replace blanks with a default value or adjacent value

Empty → "Unknown"

Extract Text

Extract part of a text value using patterns

Extract domain from email

Cleaning Recipes

DATIRA tracks all your transformations as a "recipe" that can be:

Reapplied — Update your data source and re-run the same cleaning steps
Reverted — Undo any or all transformations to get back to original data
Viewed — See the history of all transformations applied

How recipes work

When you upload new data to the same source, DATIRA can automatically reapply your cleaning recipe. This is perfect for recurring data imports — clean once, refresh automatically.

AI-Powered Reports & Dashboards

Use AI to pivot your data, generate reports, and build dashboards with natural language.Learn more about AI Assistant →

Best Practices

1. Clean before creating reports

Apply transformations before building pivot tables. This ensures your reports reflect clean data.

2. Preview before applying

Always check the preview to verify the transformation does what you expect.

3. Parse dates early

Convert date columns to proper dates so you can group by year, month, quarter, etc.

4. Remove duplicates carefully

Select the right columns to identify duplicates. Sometimes duplicate values in one column are valid.

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