A report on data analysis can help clarify the raw information collected in an investigation or business project. It analyzes how the information helps and supports a hypothesis. It also seeks to inform conclusions and aid in decision-making.
Data analysis can be classified into two broad categories, descriptive analytics, and inferential analysis. Descriptive analytics are concerned with what has happened in the past. For instance, the number of views and sales of an item. Diagnostic analytics, on the other hand, look at the reasons for why something been happening. This usually involves a variety of data inputs, as well as some hypotheses (e.g. how did the weather affect beer sales).
Before you begin data analysis, you need to clean up the raw data or „scrub“ it. This involves removing duplicate observations, and ensuring the observations are complete and accurate. It also includes the standardization of formats and identifying potential errors.
The next step is converting the data into a graphical format that is easy to comprehend. This can be done using data mining software or visualization tools. It is crucial to think about your audience at this point, in addition. You might have to create a glossary of terms or explain your approach in case your readers are unfamiliar with the terminology.
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