Interview questions for Data Analytics

1. Define the term ‘Data Wrangling in Data Analytic?

Data Wrangling is the process wherein raw data is cleaned, structured, and enriched into a desired usable format for better decision making. It involves discovering, structuring, cleaning, enriching, validating, and analyzing data. This process can turn and map out large amounts of data extracted from various sources into a more useful format. Techniques such as merging, grouping, concatenating, joining, and sorting are used to analyze the data. Thereafter it gets ready to be used with another dataset.

2. What are the various steps involved in any analytics project?

This is one of the most basic data analyst interview questions. The various steps involved in any common analytics projects are as follows:
Understanding the Problem
Understand the business problem, define the organizational goals, and plan for a lucrative solution.
Collecting Data
Gather the right data from various sources and other information based on your priorities.
Cleaning Data
Clean the data to remove unwanted, redundant, and missing values, and make it ready for analysis.
Exploring and Analyzing Data
Use data visualization and business intelligence tools, data mining techniques, and predictive modeling to analyze data.
Interpreting the Results
Interpret the results to find out hidden patterns, future trends, and gain insights.

3. What are the different types of sampling techniques used by data analysts?

Sampling is a statistical method to select a subset of data from an entire dataset (population) to estimate the characteristics of the whole population.
There are majorly five types of sampling methods:
• Simple random sampling
• Systematic sampling
• Cluster sampling
• Stratified sampling
• Judgmental or purposive sampling

4. Describe uni variate, bi variate, and multivariate analysis?

Univariate analysis is the simplest and easiest form of data analysis where the data being analyzed contains only one variable.
Example – Studying the heights of players in the NBA.
Univariate analysis can be described using Central Tendency, Dispersion, Quartiles, Bar charts, Histograms, Pie charts, and Frequency distribution tables.
The bivariate analysis involves the analysis of two variables to find causes, relationships, and correlations between the variables.
Example – Analyzing the sale of ice creams based on the temperature outside.
The bivariate analysis can be explained using Correlation coefficients, Linear regression, Logistic regression, Scatter plots, and Box plots.
The multivariate analysis involves the analysis of three or more variables to understand the relationship of each variable with the other variables.
Example – Analysing Revenue based on expenditure.
Multivariate analysis can be performed using Multiple regression, Factor analysis, Classification & regression trees, Cluster analysis, Principal component analysis, Dual-axis charts, etc.

5. How would you work with a difficult stakeholder?

As a business analyst, you will likely deal with many different personalities occupying a variety of positions. Situational questions like this one measure your problem-solving skills, communication skills and ability to resolve difficult situations. This question assesses whether you can successfully navigate interactions with many different stakeholders.
Provide a direct answer and explain a related challenge you faced in past work. You can use the STAR interview response framework to structure your answer by addressing the following:
• Situation: Briefly explain the issue you were dealing with in a positive, constructive way.
• Task: Explain your role in the situation.
• Action: Explain what you did to resolve or address the situation.
• Result: Explain your learnings and how your actions resulted in a positive impact for the business.

6. Describe a time when you had to advise a client toward a different course of action.

As a business analyst, it is your job to make recommendations both in the interest of the client and the organization. Your perspective should be based on the collected data as you interpret it. Should a client pursue a certain course of action you do not feel is in their best interest, you may be required to present the data in new and interesting ways to convince them otherwise.
In your answer, you should explain the ways you can apply your problem-solving skills to navigate potentially difficult situations with clients and other important stakeholders.
Example: “Once, I had a client who was looking to expand a product line for their store. At the same time, they were already struggling to sell many of the products they already carried. I used a detailed sales analysis to show them why they should focus on selling their current products instead of investing in new ones, and offered both suggestions about how they might increase sales along with areas in which they are already succeeding.

7. What tools do you consider the most important for a business analyst to do their job well?

This question allows an interviewer to test your basic technical skills and familiarity with standard business analytics applications as well as those they may use at the company. BAs commonly use tools like the Microsoft Office Suite, though you may have used other tools or programs in your work. Tailor your answer to highlight your own unique experience and skills.
Example: “I commonly use tools like Word, Excel, PowerPoint, MS Visio and Rational tools. I also have advanced SQL skills—using SQL is helpful when I need to analyze items like customer purchases that would overwhelm Excel.”

8. Describe how you typically approach a project?

Understanding a candidate’s workflow can help employers gauge their teamwork, project management and organizational skills. To answer, explain general phases you work through with standard deliverables you typically produce instead of listing specific processes or tasks the interviewer may not be familiar with. Focus on your actual experience to describe your skills and how you use them.
For example, if you worked on the planning stages of a project, you could mention deliverables such as a communication plan, a work breakdown structure (WBS), a requirements management plan and a business analysis approach, including whether it is plan-driven or change-driven.

9. How do you treat outliers in a dataset?

An outlier is a data point that is distant from other similar points. They may be due to variability in the measurement or may indicate experimental errors.
The graph depicted below shows there are three outliers in the dataset.
To deal with outliers, you can use the following four methods:
• Drop the outlier records
• Cap your outliers data
• Assign a new value
• Try a new transformation