Top 10 concepts for Data Analyst interviews 👇👇

1. Data Cleaning: Techniques to handle missing, duplicate, and inconsistent data.


2. SQL: Strong knowledge of Joins, Group By, Window Functions, and Subqueries.


3. Excel: Proficiency in Pivot Tables, VLOOKUP, Conditional Formatting, and advanced formulas.


4. Visualization Tools: Expertise in Tableau, Power BI, or similar tools for dashboards and insights.


5. Data Wrangling: Extracting, transforming, and loading (ETL) data from various sources.


6. Statistics: Basic understanding of mean, median, standard deviation, correlation, and hypothesis testing.


7. Python/R: Ability to use libraries like Pandas, NumPy, and Matplotlib for analysis.


8. Business Acumen: Translate data insights into actionable recommendations for stakeholders.


9. Data Modeling: Create relationships between datasets and understand star/snowflake schema.


10. A/B Testing: Design and interpret experiments to compare group performance.

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