Data Science Titles | Data Scientist, Data Engineer, Data Analyst, and Business Intelligence Devs
One of the biggest problems in Data Science is the misuse of terminology. Referring to things by another thing's name and calling something by fifteen different names cause so many problems that could simply be avoided if it just didn't happen, but it does.
In American English, dogs are called dogs, hounds, pups, pooch, canine, and man's best friend (even though women like them too). Dogs are also often referred to by their breed name in random native conversation. With new breeds coming out all the time, a list of possible references is ever growing.
Conversely, the debate over whether an object is a food turner or a spatula is equally everlasting.
Thankfully we have machine learning partnered with search automation to help with both.
The problem is so large that it affects what to actually call your data science employee. Is that person a data scientist or a data analyst? Do you know? I hope to help you understand over the next twenty minutes.
Data Scientist - Largely working with advanced mathematics to understand, test for, and prove correlation and accuracy of data. Often works with predictive analytics as well.
Accuracy and Prediction
Data Engineer - Usually build the system to properly process data for easier consumption by Data Scientists, Analysts, and Business Intelligence Developers.
Efficiency and Security
Data Analyst - Primarily works in data visualization but may also with with tools like SSRS to build template reports.
Generalist
Business Intelligence Developer - Understands data and is a pretty good Data Analyst, but has a better understanding of your business and/or business in general so is capable of generating data stories specific to your business.
Understandable
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