Data analytics involves the use of techniques and tools for quantitative and qualitative data analysis, so a data analyst is expected to work on huge amounts of data for the benefit of the company. Doing this requires proficiency in skills like data handling, statistics and problem-solving. Today, if you browse for jobs in India that require a candidate who meets the data analytics job description, you will find ample job openings on Indeed, LinkedIn and Owing to vast opportunities in data analytics jobs, we see a good number of candidates applying for data analytics interviews. In this blog, we will discuss what do interviewers expect from you, what exactly do you need to prepare for and how to crack the interview. Generally, a data analytics interview testx your problem-solving skills and lateral thinking capability by including logical reasoning questions, puzzles and problems on lateral thinking.

6 Tips to Crack a Data Analytics Interview

Data analytics jobs require in-depth knowledge and skills in statistical concepts and data handling tools. But before you get into that, you must know some basic tactics for clearing the interview. Do you know how people successfully crack a data analytics interview and become expert data analysts? Here’s how…

1. Job positions that suit you: The Data Analytics domain has multiple job positions and roles. Before you decide to apply for jobs, you must decide which job positions you’re passionate about, and then seek such opportunities. Here are a few jobs that require data analytics skills:

  • Systems Analyst in IT: Systems analysts typically design/develop systems to solve real-world problems. To provide a solution to your organisation’s IT problems, you must have a good knowledge of data analytics and business issues.
  • Data Analytics Consultant: If you want to broaden your horizons, you could be providing consultancy for data analytics solutions. This way, you could be your own boss, serving multiple clients at the same time and providing insights to their business problems. 
  • Data Analytics Manager: This position is also in demand. If you love technology and leadership at the same time, then you should look forward to becoming a Data Analytics Manager. Your technical proficiency along with social skills go a long way in making you successful in this domain.

2. Applying for jobs: Now that you have a fair idea about which Data Analytics job roles might suit you, it’s time to search for jobs on the right platforms and apply. The popular job portals enlist numerous jobs for data analytics. For example, has more than 500 Data Analytics manager job postings. Similarly, Indeed and Glassdoor list more than 1000 jobs for Data Analytics Consultants. Go through the job postings carefully, and apply for the ones that you think would suit your skills the most.

3. Leverage your experience; present case studies: Prior work experience is always an icing on the cake when you attend a job interview. So, brush up on the business processes that you implemented, how you analysed data and what approach you followed to get to the solution. More often than not, interviewers look for your knowledge and capability in business analytics, apart from your expertise in data analytics tools. So be ready with business case studies and real-time problems. You can pick up case studies from your past projects or refer to case studies from sites like, and Explain the business problem, the data processing steps followed, algorithms used, how you arrived at the solution and how you resolved the challenges. This will showcase your competence in data processing and analysis and prove your worth to your potential employers.

4. Be prepared with thorough technical knowledge required for the job: Basic knowledge of analytical tools like R or SAS (or as specified in the data analytics job description) is necessary if you’re attending a data analytics interview. Brush up your knowledge on concepts related to data import and manipulation, such as reading non-standard data, performing heavy-duty processing (SQL or macros), efficiently combining multiple datasets, and the same. 

Apart from concept-related questions, you may also be asked questions around R, SAS or Python programming, correlation, probability and regression, as well as on distributed computing frameworks like Spark, Hadoop, etc. The questions can revolve around the following –
– Python models
– Syntax style used when writing SAS codes
– Commissioning nodes into the Hadoop cluster
– Global and local variables in Python
– The difference between Hadoop and RDBMS
– Performing regression testing, etc.

5. Study the Basics of Statistical Concepts: There are chances that you’ll be asked questions on analytical algorithms, which is in turn related to statistical concepts. So, you might as well review statistical concepts like model validation measures, hypothesis testing outcomes, rejection criteria, statistical assumptions for algorithm implementation, etc. before the interview.

6. Impress the interviewers with your knowledge about the organisation: Before you appear for the interview, make sure that you study about the organisation’s primary business and the work that they do in the domain you’re applying for. This bit of homework will go a long way in impressing your employers. This also gives you the advantage of showcasing your skill sets against the real-world issues that the organisation is trying to solve, and you will be able to convince your potential employers about how you are prepared to contribute to the growth of the business.

So now you know a fair bit about cracking a Data Analytics interview. If you are a fresher, and you want to make a career in Data Analytics, enrolling in Springboard’s 1:1 mentorship-led online Data Analytics program will teach you everything that’s required for Data analytics jobs and helps fast track your career with a job guarantee. 

In addition to the aforementioned points, here are a few common tips that you need to take care of while appearing for a data analytics interview.

  • Your CV is the first thing that interviewers look at, so make sure to highlight your skills and achievements to grab their attention. Including your work experience, key projects, certifications, skills, contact details, educational background and active interests will make it an effective resume. Springboard has just the right blog for you to aid in creating the perfect Data Analyst resume.
  • Data analytics interviewers generally ask puzzles to test your problem-solving and analytical skills. In order to solve such problems and explain your rationale to the interviewer, you must practice as many puzzles as possible and get used to following a structured approach, while focusing on the data provided.
  • It’s best to be prepared to answer some common data analytics related questions, to show the interviewer that you have a good hold on the subject. Some such questions include, what’s the difference between data analysis and data mining, what’s data cleansing and the best practices followed in the process, common issues faced during analysis, how to decide if a developed model is bad or perfect, what steps will you follow if you’re starting a new data analytics project, and so on. 
  • Effective communication is the key to cracking interviews in any field. Ample homework, with poor communication skills is as good as not being prepared. Brush up on your English-speaking skills as well so that you’re confident throughout your interview. Additionally, asking the interviewers genuine questions about the job in a straightforward manner shows them that you’re open to discussions and you don’t believe in beating around the bush.

Data Analysis Job Description 

A typical data analytics job description requires you to perform the following set of tasks:

  • Collect, review, interpret and analyse data collected from internal and external data sources, by using statistical techniques/tools.
  • Build a system for database maintenance and develop methodologies for effective data management.
  • Conduct verification of collected data, find the problem(s) and develop solutions for them.
  • Present the data and ideas to different business units for identifying possible risks and opportunities, which further helps in making decisions for the company’s overall benefit.
  • Assist in database design, administration, security and maintenance, while also preparing statistical reports related to operational performance.
  • Interact with the company’s clients and understand their information requirements.

Data analytics jobs are best for you if you’re a quick and efficient problem-solver, with a knack for finding solutions through data analysis. Springboard offers a data analytics career track program that comes with a 1:1 mentoring-led, project-driven approach along with a job guarantee to help you build your dream data analytics career and earn a high data analyst salary. This course ensures that you master strategic thinking and job-ready skills; they provide assignments on real-time case studies and projects and make you qualified for the job by offering 1:1 coaching from industry experts. You can also read various blogs on Springboard such as the difference between a Data Analyst Vs Data Scientist and What Does a Data Analyst Do to gain more knowledge on the subject. Good luck!