Data analysis can be defined as the process of cleaning, transforming, and sculpting data to draw out useful information for making decisions, forming conclusions and understanding the data.

The most common problem that every scholar faces is not the lack of data but “what to do with the data?”  The answer to this question lies in the following points-

1.  The first important thing is to have the right questions in order to get the right data. The questions should be very clear about what answers you are seeking to see if these answers are fulfilling the goal of providing the suitable data for the analysis of your choice.

2.  Then comes data collection, you should be very sure of how you will collect the data and what method will be used to make sure that the data is collected properly.

3.  Once the data is collected your next step should be sorting the data, cleaning the data and omitting the unrequired data.

4.  Thy next step involves data analysis. Here you decide which tool will be used for analyzing the suitable aspect. You should be very clear of your measurement priorities.

5.  Now, you are qualified to interpret the results.

6.  When you interpret your results you can decide how you want to represent your results- whether through tables, pie charts, bar graphs or through any other form of visualization of your data.