Though they appear to be the same thing, it defies logic to give them two distinct names when they are used so indiscriminately. Therefore, what distinguishes them most from one another?
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A Data Scientist typically works on designing and constructing new processes for data modeling and production using prototypes, algorithms, predictive models, and custom analysis. They often have advanced skills in statistical analysis, machine learning, and programming.
On the other hand, a Data Analyst usually focuses on processing and performing statistical analysis on existing datasets. They often use tools like SQL, R, or Python to mine data sources, clean data, and prepare reports.
If you throw machine learning into your analytics, you might be a data scientist.
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A data scientist seeks to create novel approaches for posing and responding to such queries. Statistical tools, database software, and business intelligence packages are all necessary for a data analyst. A data scientist manipulates and analyzes data using Python, Java, and machine learning.