Data Analyst Assessment Test: Assess a Candidates' Suitability for Data Analyst Roles

Data analysis technologies and processes are widely used in commercial and industrial aspects, enabling organizations to make more data-centric decisions. R is a standard language for performing data analysis and statistical operations. It is an essential tool for data analysts, enabling them to perform data analysis and visualization with incredible ease. 

A critical approach employed in data analytics using R is called exploratory data analysis,  which is all about summarization and visualization of data sets. The concept, introduced by John Tukey, focuses on analyzing basic data structures and variables to enhance understanding of the data set, understand how the data originated, and what statistical analysis approach would be suitable for data analysis. 

What is R?

R is a programming language and environment adapted by statistical experts for data analysis and developing statistical software. Even though there are different data analysis software like Python, analyzing data using R is a whole new ball game. A data analyst evaluating data using R would give written commands to the software to go about it. However, the best thing about using R is that it enables the analysts to collect large data sets, add multiple commands, and synchronously optimize all the commands together. 

What makes R indispensable in data analysis is its ability to process a large number of commands collectively. It autosaves all the data and work progress and allows analysts to correct minor mistakes quickly. They do not have a hard time shuffling through different commands to backtrace their steps and eventually find and fix the error. R is available for download for these platforms: Windows, Linux, Unix, or OS X.  

What is a data analyst test?

Data analysts perform quantitative testing that converts data into applicable insights and offers data-driven analytical support for critical projects. A data analyst who is well versed in R  should be a data visualization expert and can pull out and utilize that data. The data analyst assessment test helps you in evaluating:

• Candidates’ expertise in R language
• Fluency in using data science-based R libraries
• Understanding of MS SQL Server fundamentals
• The skills of writing MS SQL database queries
• R programming skills

Why should you use Mercer| Mettl’s data analyst assessment?

Mercer | Mettl's data analyst (with proficiency in R) test is a well-thought-out offering catering to the level of skills that a beginner to moderately experienced data analyst would be supposed to possess. The method of gauging candidates’ expertise through Mettl assessments is your best bet for securing the best professionals with exceptional analytical and data interpretation skills for the data analyst's role.

Key profiles the test is useful for:

• Big Data Analyst (using R Programming)
• Database Analyst

Section-wise Details:

Candidates with a work experience of 1-3 years are eligible to appear for the data analyst skills test

Difficulty level: Moderate

Answer to common queries:

Can candidates be benchmarked based on the internal sample set?

Yes, at Mettl, it can be done. Should you need any further information, please write to us, and we will be happy to assist you.

Is it possible to customize the report as per the need?

Yes, we can do it. We have already done it in the past for our clients. Should you need any further information, please write to us, and we will be happy to find the best solution for you.

What is a data analyst assessment?

This exam measures the candidates’ abilities to extract information by analyzing data and suggesting possible outcomes and their proficiency in using R. The data analysis online test is essentially used for pre-employment screening. Data analysts who use R for their daily work should know how to leverage the functionality given by R Packages to unveil powerful insights from data.

How to hire the best data analysts?

You can follow these simple steps to hire data analysts:

1) Write a well-thought-out job description

A well-explained job description can strike a responsive chord with data analyst aspirants. A thorough data analyst JD includes a well-written summary of the role, a list of responsibilities, and the required skills. You can have keywords that job seekers use to search for these jobs, such as:

• Business Analyst
• Financial Analyst
• Data Analyst

2) Pre-employment testing to assess data analysis skills and filter out ineligible candidates

A data analysis test is a form of a psychometric test prepared by subject matter experts to understand and assess a candidate's expertise in analyzing high-level quantitative data. The test outcome reveals how well the candidate will perform in the actual job. 

3) Interviewing candidates for data analyst positions

Potential candidates for these positions will be optimistic answering data analyst interview questions regarding:

• Advanced SQL and Excel 
• ETL processes
• Statistics
• Project management
• Interpersonal skills

What are the essential skills for data analysts?

Listed below are some must-have skills for data analysts:

• R or Python-Statistical Programming
• Data Visualization
• Critical thinking
• SQL
• Machine Learning
• Microsoft Excel
• Presentation skills

What jobs can a data analyst do?

The answer to this question varies based on the type of company and the level to which an enterprise has adopted data-driven practices for making decisions. However, the responsibilities of an analyst usually include the following:

• designing and maintaining databases and data systems; this includes task such as solving various data-related issues and coding errors 
• data mining from primary and secondary sources and compiling that data in a human and machine-readable format 
• employing statistical tools to explain data sets, putting particular emphasis on trends and patterns that offer opportunities for implementing diagnostic and predictive analytics
• exhibiting the relevance of their responsibilities with respect to global, national, and local trends that influence both their company and industry 
• creating reports for senior leaders to communicate trends, predictions, and patterns effectively based on relevant data
• teaming up with engineers, programmers, and executive leaders to find and discuss avenues for process modifications, system improvements, and data governance policies
• providing adequate documentation that enables stakeholders to comprehend the steps of the analysis process

Are data analysts in demand?

The demand for data analysts is at an all-time high, as stated by the World Economic Forum, highlighting that data analytics is among the top ten careers in 2020 and beyond.

Is data analytics the future?

Data analytics is undergoing continuous evolution; it all began with descriptive analytics. Now, we reached that stage where analytics can determine future outcomes through predictive analytics. The advent of technologies such as AI, ML, IoT, and cloud computing has enabled analytics to perform even more demanding operations. With the continuously evolving technology comes far more exciting forms of analytics that can make the impossible possible.   

What are the interview questions for data analysts?

After passing a data analyst test for interviews, candidates often grapple with the issue of what questions to look forward to and how to answer those. Even though interviews are a bit scary, you must be well-prepared to keep stress and nervousness at bay. Given below are some commonly asked interview questions :

• Why did you choose this career?
• Which area of expertise would you prefer to work at?
• What kind of analytics tool experience do you possess?
• What has been your most challenging analysis assignment to date?
• What are your strengths?
• Can you work under pressure?
• Why should we hire you?
• How would you estimate the number of tourists visiting Paris every June?

What are the different types of data analysis?

There are four types of data analysis

• Diagnostic
• Descriptive 
• Prescriptive
• Predictive 

Is data analysis a soft skill?

It would be wrong to assume that data analysis is a soft skill when it's a blend of hard skills(data analytics)and soft skills(business metrics)

What are the strengths of a data analyst?

Most people often think that what separates a good data analyst from a bad one. Are there some specific attributes, qualities, and traits that can make someone a competent analyst? If so, is there a way to imbibe these personal skills and put these into practice?  The answer to these questions is quite simple. Given below are some habits that one can master to achieve great success in their endeavor:

• Choose a storytelling approach, but keep it simple
• Your attention to detail matters
• Have a good understanding of the business operations
• Utilize data creatively
• Be a team player
• Always show a willingness to learn new skills and tools
• Make every mistake count
• Don't overdo it!

Do data analysts code?

Data analysts don't need to have exceptional coding skills, but they must be well-versed in data visualization software, analytics software, and data management processes. Data analysts should also have strong communication skills because they have to work with teams with different technical knowledge levels.

How it works:

step 1

Add this test to your tests

step 2

Share test link from your tests

step 3

Candidate take the tests

step 4

You get their tests report