Data Analytics Career Paths & What to Learn 
1. Data Analyst 
Tools: Excel, SQL, Power BI, Tableau Skills: Data cleaning, data visualization, business metrics Languages: Python (Pandas, Matplotlib) Projects: Sales dashboards, customer insights, KPI reports
2. Business Analyst Tools: Excel, SQL, PowerPoint, Tableau Skills: Requirements gathering, stakeholder communication, data storytelling Domain: Finance, Retail, Healthcare Projects: Market analysis, revenue breakdowns, business forecasts 3. Data Scientist Tools: Python, R, Jupyter, Scikit-learn Skills: Statistics, ML models, feature engineering Projects: Churn prediction, sentiment analysis, classification models
4. Data Engineer Tools: SQL, Python, Spark, Airflow Skills: Data pipelines, ETL, data warehousing Platforms: AWS, GCP, Azure Projects: Real-time data ingestion, data lake setup
5. Product Analyst Tools: Mixpanel, SQL, Excel, Tableau Skills: User behavior analysis, A/B testing, retention metrics Projects: Feature adoption, funnel analysis, product usage trends
6. Marketing Analyst Tools: Google Analytics, Excel, SQL, Looker Skills: Campaign tracking, ROI analysis, segmentation Projects: Ad performance, customer journey, CLTV analysis
7. Analytics QA (Data Quality Tester) Tools: SQL, Python (Pytest), Excel Skills: Data validation, report testing, anomaly detection Projects: Dataset audits, test case automation for dashboards
Tip: Pick a role → Learn tools → Practice with real datasets → Build a portfolio → Share insights
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