DATA ANALYSIS The process of examining, cleaning, transforming and modeling data in order to find useful information, arrive at conclusions and support the decision-making process is called Data Analysis. The purpose of data analysis is to obtain useful information from the data and to make decisions based on data analysis. Data Analysis Methods Descriptive (Descriptive) Analysis: It is the simplest and easily understandable type of data analysis by everyone. It allows such conclusions as “Age December” and “Quantity” to be drawn quickly and easily from the data used for analysis. Exploratory Analysis: Exploratory analysis is used to understand the direct or indirect relationships between the data used in the analysis process. Decisional analysis is used to understand the direct or indirect relationships between the data used in the analysis process. Inferential Analysis: Using a small amount of data, inferential analysis is used to be able to comment on or make decisions about a larger amount of groups. Predictive Analysis: Predictive analysis is used to comment on another group or event using data from one group or event. Why is Data Analysis Important? Today, the data analysis method, which is one of the preferred methods of most enterprises on the way to achieving success, has an important place. Analyzing the right data with the right methods can bring great benefits to the company. When it comes to making more accurate decisions going forward, the method used is data analysis. In this way, companies can evaluate the information they have more effectively and determine their future strategies more accurately. On many issues such as growth, sales and investment, companies use data to see ahead. One of the benefits of data analysis is its contribution to applications aimed at increasing customer satisfaction. Thanks to data analysis, feedback received from customers is evaluated more accurately, and thanks to this, services and products can be offered that effectively ensure customer satisfaction.