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Kindly sequence the steps,
a. Analysis the available data.
b. Consult with field experts.
c. Conduct survey and interviews.
d. Read research paper on the subjects.
Kindly note, any steps can be repeated more than once.
1. clear understanding of the situation
2. handsome knowledge about how to handle the situation
3. good exposure of techniques used in analysis(comparative analysis).
the order of sequence you suggested will be as
d, b,c,b,d,a
Collect the available data regarding the issue or problem to be resolved. Collecting data includes discussing with fild experts and teams,conducting surveys. Studying booklets and articles on the issue to have more feasible solutions. later on arriving on possible reasons. based on collected data pin point the root cause of the problem. Take appropriate and mistake proof remedy to rectify this problem permanenetly or minimse its occurence. Foe analysis we can follow why-why chart which will help to find the root cause of the problem to make our research esay for rectfying the problem.
for a good data analysis you have to be best in data visualization so after cleaning the data from outlires and you can also use certain transformations to make data ready for analysis
then the next step is the critical visualization of data to understand the relations in data.
then after having compact information and knowledge about data you can run an analysis on data.
Collect data, compile the data, summarizing then start analysis
Every analysis should begin with taking a broad view of the subject of whom analysis is being done. Analysis should begin by viewing the subject from the top (having3D view) rather than looking at the subject from one point and proceeding linearly (one dimensional view) to the other point. Any other approach that provides limited view of the subject (2 dimensional) should also be avoided in the beginning.The holistic view or bird's eye view of the subject/data will provide you meaningful and better clues about which relationships are to be studied/explored to draw meaningful conclusions from the data.
