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Hello everyone,
I have a background in web programming, PHP in particular, and am recently completing my MPhil in Computer Science with a research focus on the use of decision trees and granular computing in predicting deficiencies in Nursing Home. I mostly use SPSS, Java and Weka data mining environment.

As I am graduating soon, I am thinking of applying my skills in data analysis and research because it is cool. But I am not sure how to proceed. In particular I am concerned about the following:

1) Which softwares to learn? There are different softwares out there such as SAS, SPSS and so one?
2) How,in general, would employers define a good data analyst: ability to communicate, research, bring forth new ideas, the number of certifications or the use of softwares?
3) While working as a data analyst what challenges can one face from day to day?
4) In general what advice would you give to a person aspiring to use data analysis in the welfare of the society?

I really appreciate all input. Thanks again for your time and effort.

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Hi, Salman:

With my experience at Dell, below are my thoughts for your bullet points:

1) Softwares: there are various software you can use for data analysis. Although you can use more advanced software like, JMP, Enterprise miner, or maybe SAS programming. (This may not sound impressing) But sometimes, the most convenient one is actually Microsoft Excel and Access. Access allows you to process large data set at your personal computer, and Excel provides a lot of built-in statistical functions and there are many add-ins you can obtain to provide further functionality. I believe, with your background, you won't have too much trouble learning these tools. If advanced tools are needed, companies may send you to the training. When you look for jobs, make sure you ask if they provide on-the-job training opportunity.

2) Soft skills: I think the purpose of hiring a data analyst is to uncover the hidden information. And most of people do data analysis possess very special skills that not many employees have in an organization. (I guess that's why we get the job, right?) Therefore, ability to explain the result and the impact of an decision making is pretty important. We have to explain the outcome in more common language so everyone can understand. Of course, in highly competitive market, research and innovation is also very important depending on which segments you are in. For example, how to figure out a model to extract most accurate trend in the market might very important because it will let the company make money and take more market share.

3) Challenge: Data Analyst needs DATA to do analysis, but data can be elusive sometimes. Missing data, no data at all, there are some projects I couldn't produce any conclusion because of that. Data hunting is the worst nightmare for me.

4) Society welfare: I think data analysis is the foundation of decision making. Since I was in supply chain segment, I think an informed decision can ensure cost effectiveness and eliminate waste, which requires accurate information from data analysis. For example, if we are to make a greener supply chain, we have to know many ways in order to select the most effective one. This cannot be done without good data analysis.

Thanks,
Deborah Deng, MSE OR/IE
www.linkedin.com/in/deborahdeng
Hello,
Thanks for your informative, thorough and profitable advice. I have the following comments to make:

1) I am already planning to read a book called "Data Analysis using SQL and Excel" because I believe that a lot of powerful analysis can be performed using these common tools. And it appears to me that ironically the job market is more concerned with learning more tools rather than 'mining' the most out of the present software. I am assuming that on-the-job training will be provided by large companies rather than small, am I correct?

2) With respect to explaining results what ways of presentation have you seen to work the best? Also, what problems usually come up when results are not properly explained?

Thanks again for your comments.

Sincerely,
Salman
Glad that you find my comment helpful and sorry for the late reply.

I think your comment on "mining" part is right. Some job descriptions may state certain tools required, but I think transferable skills also apply. Large companies tend to pay more attention to employees' career development. But I think if a tool is useful/valuable, it is still possible to convince the management for that. (That is, doing so and so can increase productivity, improve efficiency, or bring in profits etc.) You will be the expert on those things when you get into the field.

For the second one, I will say it's all by experience. If something is not properly explained, the audience will not believe it. Getting feedback will be the best thing to do when you start working on something.

Hope all the best for you.

Regards,
Deborah

PS. I wanted to recommend you to check out free tutorial at www.sas.com, but they changed the website so I couldn't find it anymore. For data/statistical analysis, SAS is always the best tool to learn. You can probably check back sometime later. I would like to learn Enterprise Miner and I guess I'll start with their manual. :D
Thanks a lot for your reply. I will keep your advice in mind. It helped a lot.
Thanks Dirk, I was thinking about that myself, to focus on business first.
I would also suggest that you learn SQL, database manipulation, and a lot of Excel. In some organizations, that is the starting point for all analysis.

-Ralph Winters
Thanks Ralph. I was wondering have there been times when SQL is used to do Chi-square tests and other statistical tests? I ask this because I am reading a book that teaches how to do it but it is complicated.

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