Data_Analyst_Presentation for engineering

data analytics

1. Data Analyst Role, Skills, and Career Path

2. Introduction What is a Data Analyst?

3. Importance of Data Analysis Why organizations need analysts.

4. Types of Data Analysis Descriptive, Diagnostic, Predictive, Prescriptive.

5. Key Responsibilities Collecting, cleaning, analyzing, and visualizing data.

6. Technical Skills Excel, SQL, Python/R, Power BI/Tableau.

7. Soft Skills Communication, problem-solving, critical thinking.

8. Popular Tools Excel, SQL, Tableau, Power BI, Python, R.

9. Data Collection Sources and methods.

10. Data Cleaning & Preparation Importance and techniques.

11. Exploratory Data Analysis (EDA) Detecting trends, patterns, outliers.

12. Data Visualization Charts, dashboards, and storytelling.

13. Case Study Example How data analysis improved business decisions.

14. Data Analyst vs Others Data Scientist vs Data Engineer vs Data Analyst.

15. Career Path Entry → Mid → Senior → Specialist roles.

16. Industries Hiring Finance, healthcare, retail, IT, etc.

17. Challenges Data quality, privacy, big data issues.

18. Future Trends AI, machine learning, automation.

19. Tips for Success Learning & portfolio building.

20. Conclusion Summary of the role and importance.