Your Power BI Data is a Mess. Let's Fix It.

• Your Power BI Data is a Mess. Let's Fix It.

Why Clean Data?

• Clean data builds trust in your reports
• Accurate data leads to better business decisions
• It prevents errors and misleading visuals
• Saves time during analysis and troubleshooting
• Forms a solid foundation for all your metrics
• It is the most crucial step in any project

Remove Duplicate Rows

• Find the option in the Home or Transform ribbon
• Power Query identifies duplicates across all columns
• Select specific columns to check for duplicates only there
• Review the preview before removing to avoid mistakes
• Removes all but the first instance of a duplicate entry
• Essential for accurate count and sum calculations

Unpivot Your Data

• Turns columns into rows for proper analysis
• Fixes data spread across many column headers
• Select the columns you want to keep as identifiers
• Choose the columns to unpivot (often date or category columns)
• Creates two new columns: Attribute and Value
• Transforms wide, messy data into a tall, clean format

Split Columns Easily

• Break one column into multiple new columns
• Use by delimiter like a comma, space, or hyphen
• Choose to split at each occurrence or a specific number
• Split by number of characters for fixed-width data
• You can split into rows instead of columns
• Perfect for separating full names or product codes

Text Transformation Tricks

• Use Trim to remove leading and trailing spaces
• Clean eliminates non-printable characters
• Change case to Upper, Lower, or Proper for consistency
• Extract text before, after, or between delimiters
• Replace values to fix typos or standardize categories
• Add a conditional column for custom text rules

Date & Time Fixes

• Change data type to Date to ensure proper recognition
• Use the culture setting to fix day/month mix-ups
• Extract year, quarter, month, or day name for grouping
• Calculate age or duration using date subtraction
• Create a date table from a simple list of dates
• Fix invalid dates that would cause load errors

Filter & Replace Values

• Apply filters to remove blank or null entries
• Replace errors with a null or a default value
• Replace specific values across the entire column
• Use the fill feature to handle missing data
• Filter out irrelevant rows early to improve performance
• Preview changes immediately in the query editor

Apply & Refresh

• All steps are recorded in the APPLIED STEPS pane
• You can edit or delete any step at any time
• Changes are applied only when you click Close & Apply
• Your data model updates with the clean results
• Set up scheduled refresh to automate the cleaning
• Your reports now run on perfect, analysis-ready data