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What is the difference between Data Engineer, Data Scientist, and Data Analyst?
Lately, I’ve been getting a lot of questions like this from friends who are curious about the growing demand for data-related jobs. Companies, articles, and YouTube videos sometimes use these terms interchangeably, but if you’re thinking of diving into this field, it’s important to take a closer look and understand the distinctions. Let’s break down the meanings step by step.
What Does a Data Scientist Do?
The goal: Analyzing and interpreting data to extract valuable insights and understanding trends, patterns, predictions, and opportunities from data.
Data analysis: Utilizing various data analysis techniques and algorithms to explore data and build models.
Statistics and machine learning: Applying statistical and machine learning techniques to analyze data and develop predictive models.
Interpreting results and visualization: Interpreting analysis results for business decisions and presenting them visually.
Common areas: Engaging in various fields such as business analysis, marketing analysis, healthcare analysis, etc.
