Interview Questions

Data Analyst Interview Questions

Data Analysts are usually responsible for transforming raw numbers into insightful information that help companies make better and more informed decisions.

Whether you're a job seeker preparing to be interviewed for the role of Data Analyst or an employer preparing to interview candidates for Data Analyst position, these Data Analyst interview questions will help you prepare yourself for the job interview session.

Data Analyst Interview Questions

Below are a list of some skill-based Data Analyst interview questions.

  1. What do data analysts do?
  2. Which data analysis software are you experienced in?
  3. Describe your most complex data project from start to finish. What were the most difficult challenges, and how did you handle them?
  4. Why did you go into data analysis?
  5. Your employer wants you to find all sales quota data from the past three months to see if recent incentives enhanced employee productivity. How does data cleaning factor into your analysis?
  6. Can you talk about a time where you couldn’t meet a deadline as a data analyst?
  7. Can you explain how you would estimate how many shoes could potentially be sold in Lagos each December? How do you reach a conclusion?
  8. What is your process when you start a new data analysis project?
  9. What is data modeling and how do you use it in your analysis?
  10. How would you define the Hierarchical Clustering Algorithm? When would you use it?
  11. Can you tell me how to use logistical regression when analyzing data sets?
  12. What is the difference between big data and data? Do you have experience working with big data?
  13. How many statistical methods are you familiar with? Can you provide me with a few examples?
  14. Are you comfortable using data analysis software? Which programs have you used in previous roles?
  15. How do you differentiate between data profiling and data mining? Can you give me an example of when you would use data profiling or data mining?
  16. How do you conduct an analysis when there are missing data figures? What does your process look like?
  17. How do you communicate technical information to someone without a technical background? Provide examples.
  18. Describe some of the projects you’ve worked on. What information did you look at? What impact did it have?
  19. What database software have you previously used?
  20. Describe your experience using statistical analysis tools, like SPSS and SAS.
  21. There is a bug in your data analysis software. How do you handle this situation?
  22. Describe the steps you would take to forecast quarterly sales trends. What specific models do you find the most appropriate in this case?
  23. Do you have previous experience developing data mining algorithms and databases from scratch?
  24. Have you ever delivered a cost reducing solution?
  25. How well do you understand the concepts of probability and risk?
  26. What’s the most difficult database problem you faced? How did you handle it?
  27. Do you have experience using SQL to query large data sets?
  28. What is data cleansing? How do you know you have collected enough data to build a model?
  29. What are some best practices for data cleaning? What are the steps you take?
  30. When analyzing large amounts of data, what is your process for prioritizing tasks?
  31. How do you ensure accurate predictions using data correlation? Which are the most effective methods?
  32. We want to improve our customer retention rates. What data would you need to analyze in order to make this decision?
  33. What experience have you had with managing large datasets?
  34. Describe your process for handling confidential data.
  35. What do you think is the most important aspect of data analysis?
  36. Do you have experience presenting reports and findings directly to senior management?
  37. Which data analysis tools do you wish you had more experience using?
  38. What is a sensitivity analysis in the decision making process and how can you perform one in a given situation? Can you explain this using an example?
  39. How would you go about finding errors in a spreadsheet?
  40. What is your experience with data visualization tools?
  41. If you discovered that your data was wrong, how would you react?
  42. What would you do if you were assigned a large data set and limited time to complete the analysis?
  43. What makes you stand out from other data analysts?
  44. What Is the Difference Between Data Analysis and Data Mining
  45. Define Outlier. Explain Steps To Treat an Outlier in a Dataset.
  46. What Is Metadata?
  47. What Is KNN Imputation?
  48. What Is Data Visualization? How Many Types of Visualization Are There?
  49. Do Data Analysts Need Python Libraries?
  50. What Is a Hashtable?
  51. How Would You Define a Good Data Model?
  52. What Is Collaborative Filtering?
  53. What Is Data Wrangling?
  54. What Is Time Series Analysis?
  55. What Is the Difference Between Time Series Analysis and Time Series Forecasting?
  56. What Is Clustering? List the Main Properties of Clustering Algorithms.
  57. What Is Univariate, Bivariate, and Multivariate Analysis?
  58. What Is a Pivot Table?
  59. What Is Logistic Regression?
  60. What Is Linear Regression?
  61. What Is the Role of Linear Regression in Statistical Data Analysis?
  62. Explain Kmeans Clustering.
  63. What Do You Mean by Hierarchical Clustering?
  64. Explain Data Warehousing.
  65. How Do You Differentiate Between a Data Lake and a Data Warehouse?
  66. What Are the Different Data Validation Methods in Data Analytics?
  67. Explain the essential steps in the data validation process.
  68. Name the Statistical Methods That Are Highly Beneficial for Data Analysts.
  69. What Is an N-Gram?
  70. What Is the Difference Between Variance, Covariance, and Correlation?
  71. What Is a Normal Distribution?
  72. Do Data Analysts Need Version Control? If yes, what are the benefits of using version control?
  73. Can a Data Analyst Highlight Cells Containing Negative Values in an Excel Sheet?
  74. How Do You Differentiate Between Overfitting and Underfitting?
  75. You Have 10 Bags of Marbles With 10 Marbles in Each Bag. All but One Bag Has Marbles Which Weigh 10g Each. The Exception’s Marbles Weigh 11g Each. How Would You Determine Which Bag Has 11g Marbles Using a Scale Only Once?
  76. What is the difference between the true positive rate and recall?
  77. Estimate the number of weddings that take place in a year in Nigeria?
  78. What is a data collection plan?
  79. What is an Affinity Diagram?
  80. Name some of the essential tools useful for Big Data analytics.
  81. Mention some problems that data analysts face while performing the analysis?
  82. Explain how to deal with multi-source problems?
  83. Explain KPI, the design of experiments, and the 80/20 rule.
  84. What do you mean by Hadoop Ecosystem?
  85. What is MapReduce?
  86. What is imputation? Explain different types of imputation techniques.
  87. What is the ANYDIGIT function in SAS?
  88. What is interleaving in SAS?
  89. Which questions should you ask the user/client before you create a dashboard?
  90. What is the condition for using a t-test or a z-test?
  91. What is the difference between standardized and unstandardized coefficients?
  92. What is the difference between R-squared and adjusted R-squared?
  93. What is the Truth Table?
  94. How will you handle slow Excel workbooks?
  95. Why is ‘naïve Bayes’ naïve?
  96. What is the difference between factor analysis and principal component analysis?
  97. What is A/B Testing?
  98. How is joining different from blending in Tableau?
  99. What are the different connection types in Tableau Software?
  100. How would you go about measuring the business performance of our company, and what information do you think would be most important to consider?
  101. How would you explain your findings and processes to an audience who might not know what a data analyst does?
  102. What is a Gantt Chart in Tableau?
  103. What are the different types of sampling techniques used by data analysts?
  104. In Microsoft Excel, a numeric value can be treated as a text value if it precedes with what?
  105. Explain the Type I and Type II errors in Statistics?
  106. What are the different types of Hypothesis testing?
  107. What is the difference between COUNT, COUNTA, COUNTBLANK, and COUNTIF in Excel?
  108. How do you make a dropdown list in MS Excel?
  109. Can you provide a dynamic range in “Data Source” for a Pivot table?
  110. What is the function to find the day of the week for a particular date value?
  111. How does the AND() function work in Excel?
  112. Explain how VLOOKUP works in Excel?
  113. What function would you use to get the current date and time in Excel?
  114. How do you subset or filter data in SQL?
  115. What is the difference between a WHERE clause and a HAVING clause in SQL?
  116. How are Union, Intersect, and Except used in SQL?
  117. What is a Subquery in SQL?
  118. How do you write a stored procedure in SQL?

Data Analyst Interview Questions and Answers

Every interview is different and the questions may vary. However, there are lots of general questions that get asked at every interview.

Below are some common questions you'd expect during Data Analyst interviews. Click on each question to see how to answer them.

  1. What Is Your Greatest Accomplishment?
  2. Why Should We Hire You?
  3. Do You Have Any Questions for Us?
  4. What is Your Greatest Strength?
  5. Are You a Leader or a Follower?
  6. What is Your Greatest Weakness?
  7. What is Your Salary Expectation?
  8. Tell Me About Yourself
  9. Why Do You Want To Leave Your Current Job?
  10. Why Do You Want This Job?