Data Transformation Techniques

Data transformation techniques involve changing data from one format or structure to another. Common techniques include:

• Cleaning: Handling missing values, correcting errors, and removing duplicates.
• Filtering: Selecting specific data based on defined criteria.
• Aggregation: Summarizing data (e.g., calculating sums, averages, counts).
• Joining: Combining data from multiple sources based on related fields.
• Pivoting: Rotating data to change rows into columns or vice versa.
• Normalization/Standardization: Scaling numerical data to a specific range.
• Data Type Conversion: Changing the data type of a field (e.g., string to integer).

Visit the following resources to learn more:

• @article@Data Transformation
• @video@What is Data Transformation? (Types of Data Transformations and Examples!)