| Primary Focus |
Analyzing and interpreting data insights |
Building and managing data infrastructure |
Developing predictive models and insights |
| Key Skills |
SQL, Excel, Data Visualization, Statistics |
SQL, Python, Data Warehousing, ETL |
Python, Machine Learning, Statistics, AI |
| Main Tools |
Excel, Power BI, Tableau |
Hadoop, Spark, Airflow, SQL Databases |
Jupyter, Scikit-learn, TensorFlow, Python |
| Role in Data Pipeline |
Extract and analyze data for insights |
Build, test, and optimize data pipelines |
Develop algorithms and predictive models |
| Data Processing |
Works with structured data |
Handles structured and unstructured data |
Uses structured, semi-structured data |
| Outcome |
Reports, dashboards, and insights |
Stable, scalable data architectures |
Predictive models, advanced analytics |
| Coding Level |
Moderate (mainly SQL) |
High (SQL, Python, Java, Scala) |
High (Python, R, SQL) |
| End-User Interaction |
Directly works with business stakeholders |
Limited direct interaction |
Some interaction, mostly focused on insights |
