It is an attractive and essential question of how to turn your learning and credential into an interesting career and well-paid job. In past months I talked with my friends, read the posts on different websites and communities and try to figure out relevant solutions. As a preliminary summary, I prepare this post, which may mix some errors and misunderstandings. If you find something wrong or impropriate please correct. If you have further suggestions and valuable views please advise. If you have a success story please share. If it can integrate many friendly contributions it may turn out an instructive essay for beginners and I am willing to eventually turn it into an article. I think 4 steps to shape your profile and prepare a career targeting data analysis. 1. Basis for data analysis. There are three levels of SAS programs to build your profiles: Base SAS for program specialist, Advanced SAS credentials and SAS for data science and analysis. Advanced SAS credentials include skills in SAS Macros, SQL and advanced programming techniques and efficiency. SAS for data science and analysis will focus on statistic analysis and modelling. Last not least, math knowledge on probability and statistics. Advanced Microsoft Excel skills will be an important plus. 2. Skills for practical analysis. Skills in visual tools are critical since you need to communicate with other technical divisions and management. some suggested training on Tabeaun and Spotfire, and name a few others. 3. Big data and machining learning For lots of opening jobs, it is required skills in big data and machine learning. Certainly, SAS advances in these fields are preferred. Meanwhile, Python or R is demanded. 4. Building your experience Lots of job descriptions require experience, it is a challenge for beginners to accumulate them. Join the SAS community and listen to the success stories may be a start point. Some administrative have suggested publishing an article in the SAS library. Volunteers in the local nonprofit societies involving in database construction and management can be another practical way. To target a remoting partial-time job could also ease the difficulties to fix the first job. Any comments and supplements?
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