Data Analytics Interview Questions

So you have an interview for a Data Analytics role or a Business Analytics role? Standard interview questions will likely be asked in your interview; however, there will be a large focus on technical questions to make sure you have a thorough understanding of the job you want to undertake.

Here are some of the basic Data Analytics questions that may be asked of you. Mostly, they will ask you what is necessary in the role and for the specific company, so don’t be overwhelmed, you likely won’t be asked all these questions! If you think something more specific might come up talk to your Peoplebank consultant who can help you understand exactly what you need to know.

  • What do you consider the key skills required for a Data Analyst?
  • What’s the difference between Data Mining and Data Analysis?
  • What is your process for Data Analysis?
  • What are the various steps that you usually go through in an analytics project?
  • What is the difference between Data Mining and Data Profiling?
  • What is your skill level in terms of pulling data into an easy-to-digest report for the business?
  • Are you confident in your skills to translate technical information into knowledge that everyone can understand?
  • What is data cleansing and what are the best ways to practice this?
  • Can you list some of the best tools that are useful for data analysis?
  • Can you explain logistic regression?
  • What would you say is the criteria that can determine whether a developed data model is good or not?
  • What is the criteria for a good data model?
  • When should a business retrain the model?
  • What are the most important steps in the data validation process?
  • What are some common problems you encounter whilst performing analysis?
  • What are the most common missing patterns you have observed?
  • What is the KNN imputation method?
  • What is the name of the framework developed by Apache for processing large dataset for an application in a distributed computing environment?
  • Tell me about the data validation methods you most commonly use?
  • Explain to me the process around suspected or missing data?
  • Tell me about how you deal with multi-source problems?
  • What is an Outlier?
  • Can you explain what is K-mean Algorithm?
  • Can you explain a Hierarchical Clustering Algorithm?
  • What is collaborative filtering?
  • Do you have a clear understanding of KPIs, design of experiments and the 80/20 rule?
  • What are the main tools you are familiar with for Big Data?
  • What statistical methods are helpful for you as a data analyst?
  • Can you explain what Clustering is? What are the properties for clustering algorithms?
  • Tell me about Map Reduce.
  • What is time series analysis?
  • Tell me about correlogram analysis?
  • What is a hash table?
  • What is a hash table collision and what technique do you use to avoid this?
  • Tell me about imputation, please list different types of imputation techniques.
  • Which method of imputation is most beneficial?
  • Can you explain to me what an N-gram is?
  • Would you describe your experience in Excel as intermediate or highly skilled?
  • Do you have much experience dealing with Differential and Inferential Statistics?
  • What is your experience level with SAS?
  • What level would you consider your SQL skills are? Beginner, intermediate or highly skilled?

You may also get questions about key technology that is applicable to the job specifically. It’s important to keep an eye out for what technology is mentioned directly in the job ad, make sure you have knowledge about what is precisely listed. Often these will be listed under ‘Technical Skills’ and/or ‘Desired Experience’.