Post #2552

Top 100 Data Analyst Interview Questions ✅ Data Analytics Basics 1. What is data analytics? 2. Difference between data analytics and data science? 3. What problems does a data analyst solve? 4. What are the types of data analytics? 5. What tools do data analysts use daily? 6. What is a KPI? 7. What is a metric vs KPI? 8. What is descriptive analytics? 9. What is diagnostic analytics? 10. What does a typical day of a data analyst look like? Data and Databases 11. What is structured data? 12. What is semi-structured data? 13. What is unstructured data? 14. What is a database? 15. Difference between OLTP and OLAP? 16. What is a primary key? 17. What is a foreign key? 18. What is a fact table? 19. What is a dimension table? 20. What is a data warehouse? SQL for Data Analysts 21. What is SELECT used for? 22. Difference between WHERE and HAVING? 23. What is GROUP BY? 24. What are aggregate functions? 25. Difference between INNER and LEFT JOIN? 26. What are subqueries? 27. What is a CTE? 28. How do you handle duplicates in SQL? 29. How do you handle NULL values? 30. What are window functions? Excel for Data Analysis 31. What are pivot tables? 32. Difference between VLOOKUP and XLOOKUP? 33. What is conditional formatting? 34. What are COUNTIFS and SUMIFS? 35. What is data validation? 36. How do you remove duplicates in Excel? 37. What is IF formula used for? 38. Difference between relative and absolute reference? 39. How do you clean data in Excel? 40. What are common Excel mistakes analysts make? Data Cleaning and Preparation 41. What is data cleaning? 42. How do you handle missing data? 43. How do you treat outliers? 44. What is data normalization? 45. What is data standardization? 46. How do you check data quality? 47. What is duplicate data? 48. How do you validate source data? 49. What is data transformation? 50. Why is data preparation important? Statistics for Data Analysts 51. Difference between mean and median? 52. What is standard deviation? 53. What is variance? 54. What is correlation? 55. Difference between correlation and causation? 56. What is an outlier? 57. What is sampling? 58. What is distribution? 59. What is skewness? 60. When do you use median over mean? Data Visualization 61. Why is data visualization important? 62. Difference between bar and line chart? 63. When do you use a pie chart? 64. What is a dashboard? 65. What makes a good dashboard? 66. What is a KPI card? 67. Common visualization mistakes? 68. How do you choose the right chart? 69. What is drill down? 70. What is data storytelling? Power BI or Tableau 71. What is Power BI or Tableau used for? 72. What is a data model? 73. What is a relationship? 74. What is DAX? 75. Difference between measure and calculated column? 76. What is Power Query? 77. What are filters and slicers? 78. What is row level security? 79. What is refresh schedule? 80. How do you optimize reports? Business and Case Questions 81. How do you analyze a sales drop? 82. How do you define success metrics? 83. What business metrics have you worked on? 84. How do you prioritize insights? 85. How do you validate insights? 86. What questions do you ask stakeholders? 87. How do you handle vague requirements? 88. How do you measure business impact? 89. How do you explain numbers to managers? 90. How do you recommend actions? Projects and Real World 91. Explain your best project. 92. What data sources did you use? 93. How did you clean the data? 94. What insight had the most impact? 95. What challenge did you face? 96. How did you solve it? 97. How did stakeholders use your dashboard? 98. What would you improve in your project? 99. How do you handle tight deadlines? 100. Why should we hire you as a data analyst? Double Tap ♥️ For Detailed Answers