Data Science: What is the difference between business analyst, data analyst, data scientist, business intelligence analyst, business systems analyst, and product manager?

So, there is a lot of confusion regarding the terminologies, but more or less they all overlap. Another point to mention here, it really doesn't matter since they keep on changing! Well, I have never discussed much about BSA and PM, and therefore will refrain myself from making guesses! The demand of most businesses in today's time is, in context of the question asked, data collection, data cleaning, reporting and gathering insights/ answering business problems/ suggesting methods and ways to boost business. And so it comes down to two broad categories Business Intelligence and Data Warehousing, and Business Consulting. Business Intelligence Analyst, Data Analyst and Data Scientist- This person is going to perform almost all the tasks except the data collection and delivering insights part. They will work on crude data using the many tools available in the market to clean data, generate reports/ dashboards. That's how they play, give them loads of data and they'll draw graphs/ charts out of that textual stuff and present it over to the client. Also, technically this profile is a part of Data Warehousing and Business Intelligence domain, now you can attach some more meaning. Business Analyst- This guy kind of performs the 'after BI' part. The BI guy sends over the impeccable graphs and dashboards but then who is going to tell the client what is to be done, what does this mean, what should you do .. blah blah i.e. every nuance dealing with the clients Business aspect. So this is the most important task of the BA guy, to deliver relevant business insights that can be implemented and that helps answer the question posed by the client, which a dashboard or an excel report rarely do. Also, the BA profile comes under the Business Consulting Domain. As you might also infer that Business Consulting needs the support of BI to generate their insights (mostly), and so they go hand in hand. Yes, at the front end a BA shines more than a BI guy, but then what can a BA do alone!

With the exception of product manager, these are all jobs that fall under the umbrella of data science. If you love data science, and have experience in any of these fields, an MBA with an emphasis on analytics will help you get any of these jobs. An MBA alone is not enough of a pedigree to get into the highly competitive field of data science.If you do not have experience in data science, but love it, then I'd go back for a bachelor's in data science while working on an MBA with emphasis on analytics. This will give you the solid background in the field that will make up for your lack of experience. An MBA is de rigueur for a product manager position, but not for the other jobs you list. If data analysis is your thing, then consider an MS in data science, followed by a PhD. This is the shortest path to a data scientist position compared to putting in years of haphazard learning in the corporate world. It will guarantee you the highest salary and most rewarding assignments.SOURCE: Analyzing the Analyzers: An Introspective Survey of Data Scientists and their Work. http://cdn.oreillystatic.com/oreilly/radarreport/0636920029014/Analyzing_the_Analyzers.pdf

Resources you can read to learn more about the careers you are interested with based on the career and salary research site, PayScale:http://bitly.com/18rAeeZ http://bitly.com/12Rd7kHhttp://bitly.com/1xCyW9nhttp://bitly.com/1v65yp2http://bitly.com/1ZbgUJshttp://bitly.com/1Ewyflz

Data Scientists are people who are Socrates, Homer, Euler, Steve Jobs, Da Vinci, Fischer and have skills of all of the above mentioned names. Which is why they are also extraordinarily well paid.The rest of them use IT skills in various degree to help corporations achieve their end goals, by improving process, or optimizing platforms, building web analytics, etc.