Interview Questions for Data Analyst Role

Here are 50 multiple-choice interview questions for a Data Analyst position.
These questions can serve as a preparation kit or a quick refresher before you appear in a Data Analyst interview.

(Refer the answer key at the end)

1. What is the primary goal of data analysis?
   a) To prepare data for machine learning
   b) To extract valuable insights from data
   c) To clean and store data
   d) To create data visualizations
2. Which statistical measure provides information about the spread of data values?
   a) Mean
   b) Mode
   c) Median
   d) Variance
3. What is the role of data preprocessing in data analysis?
   a) Developing predictive models
   b) Summarizing data using descriptive statistics
   c) Cleaning and transforming data
   d) Creating data visualizations
4. What is data imputation used for in data analysis?
   a) Removing outliers from a dataset
   b) Replacing missing values in data
   c) Calculating summary statistics
   d) Data visualization
5. Which data visualization technique is best for showing the distribution of a single continuous variable?
   a) Bar chart
   b) Scatter plot
   c) Line chart
   d) Histogram
6. What does the P-value indicate in statistical hypothesis testing?
   a) A confidence interval
   b) A measure of central tendency
   c) A measure of effect size
   d) The probability of observing a test statistic as extreme as or more extreme than the one computed from the sample data
7. What is the purpose of a correlation coefficient in data analysis?
   a) Creating data models
   b) Measuring the strength of a linear relationship between variables
   c) Testing hypotheses
   d) Handling missing data
8. Which programming language is commonly used for data analysis and statistical modeling?
   a) Python
   b) C++
   c) Java
   d) R
9. What is the primary goal of exploratory data analysis (EDA)?
   a) Building predictive models
   b) Data visualization
   c) Understanding data’s underlying structure and relationships
   d) Data cleaning
10. In data analysis, what does the term “outlier” refer to?
    a) A common data distribution
    b) A data visualization technique
    c) A variable with natural order
    d) An extreme or unusual data point that deviates from the overall pattern
11. Which type of data is represented by categories or labels and lacks a natural numerical order?
    a) Ordinal data
    b) Ratio data
    c) Interval data
    d) Nominal data
12. In data analysis, what is a scatter plot used for?
    a) Visualizing data over time
    b) Showing the relationship between two continuous variables
    c) Comparing different categories in a dataset
    d) Displaying the distribution of a single variable
13. What is a data mart in the context of data analysis and data warehousing?
    a) A data transformation algorithm
    b) A data cleaning technique
    c) A smaller, specialized subset of a data warehouse
    d) A data visualization tool
14. Which statistical test is suitable for comparing means of two independent groups in data analysis?
    a) Regression analysis
    b) ANOVA
    c) Chi-squared test
    d) T-test
15. In data analysis, what does “data wrangling” refer to?
    a) The process of data cleaning and preparation
    b) Building predictive models
    c) Analyzing time series data
    d) Creating data models
16. What is the purpose of data normalization in data analysis?
    a) Handling missing data
    b) Removing outliers from a dataset
    c) Scaling data to a standard range
    d) Summarizing data using descriptive statistics
17. In data analysis, what does the acronym SQL stand for?
    a) Statistical Query Language
    b) Structured Query Language
    c) Sequential Query Language
    d) Simple Query Logic
18. Which type of data is represented by categories with a natural order or ranking?
    a) Interval data
    b) Ratio data
    c) Nominal data
    d) Ordinal data
19. What is the primary purpose of data profiling in data analysis?
    a) Data visualization
    b) Data imputation
    c) Creating data models
    d) Assessing the quality and structure of data
20. In data analysis, what does “data silo” refer to?
    a) A data cleaning technique
    b) A statistical hypothesis test
    c) A data visualization tool
    d) A system or department that stores and manages data independently from the rest of the organization
21. What does “BI” stand for in the context of data analysis?
    a) Big Information
    b) Business Intelligence
    c) Binary Input
    d) Basic Investigation
22. In data analysis, what does the term “confounding variable” refer to?
    a) A variable that influences the outcome and is of interest in the study
    b) A variable that is difficult to measure
    c) A variable that may falsely appear to influence the outcome
    d) A variable that is not related to the study
23. Which type of data analysis is focused on understanding the causes and effects of an event or outcome?
    a) Descriptive analysis
    b) Predictive analysis
    c) Prescriptive analysis
    d) Causal analysis
24. What does “OLAP” stand for in data analysis?
    a) Online Logical Analysis and Processing
    b) Onset of Logical Analysis and Projections
    c) Online Analytical Processing
    d) Outside Layered Approach to Processing
25. In data analysis, what is the primary purpose of data enrichment?
    a) To reduce the size of a dataset
    b) To combine data from various sources to enhance its quality and value
    c) To conduct A/B testing
    d) To perform statistical analysis
26. What is the primary objective of data governance in an organization?
    a) To make data easily accessible to all employees
    b) To protect and manage data assets effectively
    c) To clean and preprocess data
    d) To create data models
27. Which statistical measure is not affected by outliers in a dataset?
    a) Mean
    b) Median
    c) Range
    d) Standard deviation
28. In data analysis, what does the term “data granularity” refer to?
    a) The extent to which data is detailed or fine-grained
    b) The speed of data retrieval
    c) The type of data encoding used
    d) The size of data storage devices
29. In data analysis, what is the primary purpose of time series analysis?
    a) To compare two or more datasets
    b) To explore patterns and trends in time-ordered data
    c) To conduct A/B testing
    d) To create data visualizations
30. What is the purpose of data sampling in data analysis?
    a) To remove outliers from a dataset
    b) To calculate summary statistics
    c) To select a subset of data for analysis
    d) To build data models
31. What is the primary purpose of data visualization in data analysis?
    a) To hide information from viewers
    b) To make data more complex and difficult to understand
    c) To impress stakeholders with artistic charts
    d) To convey information and insights effectively
32. In data analysis, what is the primary goal of data transformation?
    a) To calculate summary statistics
    b) To remove duplicate data records
    c) To reshape and prepare data for analysis
    d) To conduct hypothesis testing
33. What does “BI” stand for in the context of data analysis?
    a) Big Information
    b) Business Intelligence
    c) Binary Input
    d) Basic Investigation
34. What is the primary use of a pivot table in data analysis?
    a) To encrypt data
    b) To create data visualizations
    c) To summarize and aggregate data in a tabular format
    d) To store metadata and data definitions
35. In data analysis, what does “data profiling” refer to?
    a) The analysis of time series data
    b) Assessing the quality and structure of data
    c) The use of regression analysis
    d) The process of data cleaning
36. What is the purpose of a histogram in data analysis?
    a) To display the distribution of a single variable
    b) To compare two groups
    c) To visualize relationships between multiple variables
    d) To measure the strength of a correlation
37. Which type of data analysis is focused on understanding the causes and effects of an event or outcome?
    a) Descriptive analysis
    b) Predictive analysis
    c) Prescriptive analysis
    d) Causal analysis
38. In data analysis, what is the primary purpose of a scatter plot?
    a) To create data models
    b) To visualize relationships between multiple variables
    c) To display the distribution of a single variable
    d) To compare two groups
39. In data analysis, what does “data granularity” refer to?
    a) The extent to which data is detailed or fine-grained
    b) The speed of data retrieval
    c) The type of data encoding used
    d) The size of data storage devices
40. In data analysis, what is the primary purpose of time series analysis?
    a) To compare two or more datasets
    b) To explore patterns and trends in time-ordered data
    c) To conduct A/B testing
    d) To create data visualizations
41. In data analysis, what is the primary purpose of data enrichment?
    a) To reduce the size of a dataset
    b) To combine data from various sources to enhance its quality and value
    c) To conduct A/B testing
    d) To perform statistical analysis
42. What is the primary purpose of data sampling in data analysis?
    a) To remove outliers from a dataset
    b) To calculate summary statistics
    c) To select a subset of data for analysis
    d) To build data models
43. Which statistical measure is not affected by outliers in a dataset?
    a) Mean
    b) Median
    c) Range
    d) Standard deviation
44. In data analysis, what does the term “data granularity” refer to?
    a) The extent to which data is detailed or fine-grained
    b) The speed of data retrieval
    c) The type of data encoding used
    d) The size of data storage devices
45. What is the primary purpose of data mining in data analysis?
    a) To explore patterns and trends in time-ordered data
    b) To conduct A/B testing
    c) To extract valuable insights from data
    d) To create data models
46. What is the primary objective of data governance in an organization?
    a) To make data easily accessible to all employees
    b) To protect and manage data assets effectively
    c) To clean and preprocess data
    d) To create data models
47. In data analysis, what does the acronym EDA stand for?
    a) Estimated Data Analysis
    b) Exploratory Data Analysis
    c) Effective Data Aggregation
    d) External Data Access
48. What is the purpose of a histogram in data analysis?
    a) To display the distribution of a single variable
    b) To compare two groups
    c) To visualize relationships between multiple variables
    d) To measure the strength of a correlation
49. Which of the following is not a common database model in data analysis?
    a) Relational database
    b) NoSQL database
    c) Hierarchical database
    d) Entity-Attribute-Value (EAV) model
50. In data analysis, what is the primary purpose of data transformation?
    a) To calculate summary statistics
    b) To remove duplicate data records
    c) To reshape and prepare data for analysis
    d) To conduct hypothesis testing

Answer Key:

1. b) To extract valuable insights from data
2. d) Variance
3. c) Cleaning and transforming data
4. b) Replacing missing values in data
5. d) Histogram
6. d) The probability of observing a test statistic as extreme as or more extreme than the one computed from the sample data
7. b) Measuring the strength of a linear relationship between variables
8. a) Python
9. c) Understanding data’s underlying structure and relationships
10. d) An extreme or unusual data point that deviates from the overall pattern
11. d) Nominal data
12. b) Showing the relationship between two continuous variables
13. c) A smaller, specialized subset of a data warehouse
14. d) T-test
15. a) The process of data cleaning and preparation
16. c) Scaling data to a standard range
17. b) Structured Query Language
18. d) Ordinal data
19. d) Assessing the quality and structure of data
20. d) A system or department that stores and manages data independently from the rest of the organization
21. b) Business Intelligence
22. c) A variable that may falsely appear to influence the outcome
23. d) Causal analysis
24. c) Online Analytical Processing
25. b) To combine data from various sources to enhance its quality and value
26. b) To protect and manage data assets effectively
27. b) Median
28. a) The extent to which data is detailed or fine-grained
29. b) To explore patterns and trends in time-ordered data
30. c) To select a subset of data for analysis
31. d) To convey information and insights effectively
32. c) To reshape and prepare data for analysis
33. b) Business Intelligence
34. c) To summarize and aggregate data in a tabular format
35. b) Assessing the quality and structure of data
36. a) To display the distribution of a single variable
37. d) Causal analysis
38. b) To visualize relationships between multiple variables
39. a) The extent to which data is detailed or fine-grained
40. b) To explore patterns and trends in time-ordered data
41. b) To combine data from various sources to enhance its quality and value
42. c) To select a subset of data for analysis
43. b) Median
44. a) The extent to which data is detailed or fine-grained
45. c) To extract valuable insights from data
46. b) To protect and manage data assets effectively
47. b) Exploratory Data Analysis
48. a) To display the distribution of a single variable
49. c) Hierarchical database
50. c) To reshape and prepare data for analysis