There are four main types of aggregation in data analysis:
1. Sum:
- Definition: Adds up all values in a dataset.
- Example: Calculating the total sales revenue for a month.
- Practical Insight: Useful for understanding overall trends and performance.
2. Average:
- Definition: Calculates the mean value of a dataset.
- Example: Determining the average customer satisfaction score.
- Practical Insight: Provides a representative value for a dataset.
3. Count:
- Definition: Determines the number of occurrences of a specific value or event.
- Example: Counting the number of customers who purchased a particular product.
- Practical Insight: Helps understand the frequency of events or data points.
4. Minimum/Maximum:
- Definition: Identifies the smallest or largest value in a dataset.
- Example: Finding the lowest and highest prices for a product.
- Practical Insight: Useful for identifying outliers and understanding the range of values.
These four types of aggregation provide valuable insights into data by summarizing and condensing information. They are essential tools for data analysis and decision-making.
