Top 5 Data Cleaning Methods in Power BI

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Data cleaning is a crucial step in ensuring the quality and accuracy of your analysis and reports in Power BI. These are the top five data cleaning methods you can use in Power BI as per my opinion:

1. Removing Duplicates

• Why: Duplicate records can skew analysis and lead to incorrect insights.
• How: Go to the Power Query Editor. Select the column(s) where you want to remove duplicates. Right-click and choose Remove Duplicates.

2. Handling Missing Values

• Why: Missing values can disrupt calculations and visualizations.
• How: Replacing Nulls: In the Power Query Editor, select the column with missing values. Right-click and choose Replace Values. Replace null values with a default value (e.g., 0, "Unknown"). Removing Rows with Nulls: Select the column with null values. Right-click and choose Remove Rows > Remove Blank Rows.

3. Transforming Data Types

• Why: Correct data types ensure that operations and calculations are performed correctly.
• How: In the Power Query Editor, select the column you want to change. Go to the Transform tab. Choose the appropriate data type (e.g., Text, Whole Number, Date).

4. Splitting Columns

• Why: Sometimes data is stored in a single column but needs to be split for better analysis (e.g., splitting full names into first and last names).
• How: In the Power Query Editor, select the column to split. Go to the Transform tab. Click on Split Column and choose the appropriate delimiter (e.g., space, comma).

5. Trimming and Cleaning Text

• Why: Extra spaces and unwanted characters in text data can lead to inconsistent data and errors.
• How: Trimming: In the Power Query Editor, select the column you want to trim. Go to the Transform tab. Click on Format and choose Trim to remove leading and trailing spaces. Cleaning: Select the column you want to clean. Go to the Transform tab. Click on Format and choose Clean to remove non-printable characters.

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