A data analysis report can help make sense of the data collected in an investigation or business project. It is a thorough examination of how the data is connected to and supports a hypothesis. It also aims to help inform conclusions and assist in making decisions.
Data analysis can be divided into two broad categories, descriptive analytics and inferential analysis. Descriptive analytics concentrate on what has happened in the span of time. For instance, the number of views and sales for the particular product. Diagnostic analytics, however, analyzes the reasons behind what happened. This typically involves more diverse data inputs, and some hypothesizing (e.g. how did the weather affect beer sales).
Before you begin data analysis, you need to cleanse the raw data, or “scrub” it. This involves removing duplicate observations and ensuring that the observations are complete and precise. It also includes standardizing formats and identifying potential mistakes.
The next step is to convert the data into Clicking Here a clear graphic format. This can be done using data mining or visualization software. It is important to consider your audience at this point, and. You may want to make a glossary or explain your method if your readers aren’t aware of the terms.