Types of Data Analysis

Data analysis can be broadly categorized into four types:

Descriptive analysis: This data analysis is used to describe the data. It involves summarizing the data to understand the distribution, central tendencies, and dispersion of the data.
Exploratory analysis: Exploratory analysis is used to understand the relationships between different variables in the data. It helps identify patterns and trends in the data.
Inferential analysis: Inferential analysis makes predictions or inferences based on the data. It uses statistical techniques to draw conclusions from a sample of data that can be applied to a larger population.
Predictive analysis: Predictive analysis predicts future events or behaviors based on past events or data. For this, machine learning and statistical models are used to make predictions.

These types of data analysis differ in their objectives, methods, and results. And businesses use the type of data analysis best suited for their use case. For example, if you want to understand customer behavior, you can use descriptive and exploratory data analysis.

To predict customer churn, you will use predictive data analysis. Likewise, if you want to use a sample set to make predictions about a larger population, you will use inferential or statistical analysis. As per the data analysis type, there will also be different data analysis tools.

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