A data analysis report helps understand the data collected in a research project or business project. It focuses on the way that this information is related to and supports a 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 are concerned with what has happened in the past. For example the number of views or sales of the particular product. Diagnostic analytics however look at the reasons for the reasons behind what has taken place. This typically involves more diverse data sources and some speculation (e.g. how did the weather affect sales of beer?).
Before you begin the analysis of data, you must clean the raw data, or “scrub” it. This means removing duplicate observations and ensuring that each observation is complete and accurate. This can also include standardizing formats, as well as identifying any errors that could be caused by the format.
The next step is to convert the data into a simple visual format. This can be accomplished by using data mining or visualization software. It is crucial to think about your audience at this point, and. It is possible to develop a glossary page of terms or explain your strategy in case your readers are unfamiliar with the terminology.