@alisq786 wrote:
To begin with something about myself: I am a senior statistician almost 50 years of age with over 20 years of experience in statistics. Have masters degree in statistics from University of Toronto and have been working in data driven business in senior leadership roles (Director and above levels) around the world. Have been using SAS for over 20 years with SAS advance programmer Certification (Note never used R; though I really wanted to).
Having said that, I really wanted to develop and improve my credentials/skills in Data Science (and/or big data analytics) with certifications in the end. Now here I want your help and guidance to understand following points:
- what exactly is the difference between data science and big data analytics (i.e. what are the commonalities and differences between those two intertwined domains)?
- for a senior statistician which one is more apt area to grow skills into? i.e. which one adds more value quickly (which ones could be consider as quick wins and the rest could be taken as knowledge/skills grow richer) keeping in mind I don’t have much time/energy?
- Please confirm, or otherwise, my understanding that data science, perhaps, is more logical path for someone like myself to grow skills into?
- please also guide me what would be the correct way forward i.e. step by step course needs to be taken for someone like myself (i.e. should I start with R, Python, hadoop, mapreduce, nosql,…. ?); which courses are considered foundation level courses for one or both domains (i.e. data science and Big data)
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