{ "media_type": "text", "post_content": "What are the general pros and cons of a data scientist role versus an information architect role? I understand both roles can be very broad, but I think these titles are associated with certain functions, work, and responsibilities.", "post_id": "5f91a1f572006b0028123640", "reply_count": 5, "vote_count": 1, "bowl_id": "5ace5097be6e660013abcc42", "bowl_name": "Data & Analytics Consultants" }

What are the general pros and cons of a data scientist role versus an information architect role? I understand both roles can be very broad, but I think these titles are associated with certain functions, work, and responsibilities.

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Data scientist is analysis focused, architect is system design focused. The first uses data, the second anticipates data pipeline problems and coordinates building the -general- infrastructure to prevent later difficulties. This includes thinking about data access, integrity, etc. Contrasts with a data engineer, who may work with both to execute needed data manipulations.

I accidentally posted twice. Please ignore this chain and instead discuss on the other.

What is an Information Architect now? Is the role on lines of Data base designers and ETL processes or how the Tech stack is architected?

I’d say they’re involved in analytics at a high level, working across systems and problems.

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