What is the difference between a data analyst and a data scientist?

A data scientist is a data analyst, but data analyst is not a data scientist by definition.

Data Analyst

A data analyst uses data and converts it into information by laying out connections.This information is then analyzed and translated into knowledge. As a by-product it can also produce more data, which can then be analyzed again.

Data scientist

A data scientist also performs data analysis, but uses scientific methods.Where the data analyst uses data analysis to acquire knowledge, the data scientist goes one step further and uses this knowledge to generate new models and algorithms, as shown in the diagram below.

Image: Wikipedia


The data analyst will probably, like the data scientist, develop new models and algorithms and implement them in the data analysis process or convert them into a new product or knowledge.

However, the data scientist will generally be better trained in handling and developing scientific methods, and publishing scientific research.

Publishing research is not a requirement for the data analyst.

The term “data scientist” is freely translated from the (English) term Data Scientist.I myself have had both positions as Data analyst and Data Scientist and the biggest differences in these roles lie mainly with the output you deliver.

As a Data analyst, I had to provide valuable insights based on mainly descriptive statistics and visualizations.Every day I was mainly concerned with looking at, translating and interpreting information.

Where a Data analyst is mainly involved in analyzing, a Data Scientist is mainly concerned with generating the data, visualizations, statistics that can then be interpreted by an analyst.When generating these insights, different types of skills are shown that differ to programming skills, statistics/linear algebra and domain knowledge.

In short, as a Data scientist (as Data Scientist), you are plodding something more with the underlying data and code to deliver the insights.As a Data analyst, you interpret this data, try to find critical information and translate it into valuable actions for the organization. In my opinion, one role is no more difficult than the other.Data Science is only a bit newer and there is a combination of skills to look at.

The below ven diagram you regularly come across to describe the skills of a Data Scientist.

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