A data analysis report helps interpret the raw data gathered during a research project or business project. It includes an examination of the way that this information is related to and supports a particular hypothesis. It also aims to help inform conclusions and aid in decision-making.
Data analysis can be divided into two broad categories – descriptive analytics and inferential analysis. Descriptive analytics focus on what has occurred over a time, such as the number of views or sales for a product. Diagnostic analytics, however, analyzes why something took place. This usually involves more diverse data sources and some speculation (e.g. what was the impact of the weather affect beer sales).
Before you begin data analysis, you need to cleanse the raw data and „scrub“ it. This includes removing duplicate observations, and ensuring that all the observations are complete and precise. This could also mean standardizing formats and identifying possible errors.
The next step is to convert the data into an easy-to-understand graphic format. This can be done by using data mining This Site software or data visualization tools. At this point, it is also important to think about the audience. You might have to create an alphabetical list of terms or explain your method in case your readers aren’t familiar with the terminology.