To become a data analyst one need to be good at maths, basically numbers and visuals are two things every data analyst must know about. In my experience I believe domain knowledge and understanding the business is one of the key factor one would be needing to sort out pattens or analysis from the business data. Until and unless I don't know what my details is telling to me how I can be sure what to analyse. After all these basically a series of tool is important so that the work of analyst becomes easy, let's say tools like Excel, SQL , visualisation (tableau, powerbi), cloud computing (azure,AWS), modules in python like matplotlib, scikit learn, seaborn, pandas are some of the basic necessities that need to be fullfill. Some guidelines if I have to say is: 1) always try with clean data, then move to dirty data(mostly wrong columns values, mismatch column values, redundant data) 2) making quick visuals are always a better approach to increase confidence and skill in the path 3)...