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What is the difference between a data analyst, data scientist and data engineer?
A data analyst answers business questions with reports and dashboards. A data engineer builds and maintains the pipelines and warehouses that deliver reliable data. A data scientist builds predictive models. Small companies often need analyst and engineering skills first, and may rely on one person or an outside team for both.
Roles overlap, especially in smaller organisations.
- Analyst: SQL, BI tools, business understanding, communication
- Engineer: pipelines, databases, cloud infrastructure, data quality
- Scientist: statistics, machine learning, experimentation
Hiring a data scientist before the engineering and analytics foundations exist is a common and expensive mistake, because they end up spending most of their time cleaning data instead of modelling. Knowing which role you actually need avoids paying for skills you cannot yet use.
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