https://apcslonline.com/2023/06/09/what-is-data-analysis/
Data analysis is the process by which data are inspected, cleansed, transformed, and modeled with the goal of discovering useful information and formulating conclusions. It also supports decision-making. Data analysis entails a variety of methods, including descriptive statistics, inferential statistics (modeling relationships between variables) and cluster analysis.
Data analytics combines raw data and shines a spotlight on trends and patterns. This allows executives to make informed decisions. Data analysis can improve performance across every department including sales, marketing and supply chain management, to finance and HR.
The initial step of data analysis is collecting, organizing and storing the data. This includes identifying and eliminating duplicates from the dataset. This is crucial since duplicates can alter the results of an analysis by giving greater importance to certain values. Also, it is crucial to note any missing data in the dataset. Data that is missing can also affect results by causing uncertainty about the final result. This can be prevented by statistical methods like imputation or by removing rows with missing values.
After the information has been gathered after which an inferential analysis is performed to determine if the data has any significant patterns. Comparing the data to other data, like the past or historical trends, can help you do this. This can help identify factors that determine success or failure and also optimize processes. Regression analysis can be used to predict future trends or behaviors by determining the relationship between independent and dependent variables. Other popular predictive techniques include multivariate linear or binomial regression or decision trees, as well binary or linear regression.