June 7, 2022
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Accenture Data Analyst Interview Preparation Tips

The Accenture interview process for the data analyst role consists of three rounds; Know how to clear the interview with our mentor & senior analyst @Accenture Akash Dongre.

Most companies and major businesses in all industries now rely on using data to make key business decisions. These companies are therefore on a hiring spree. As per our estimates, there will be more than a million data analyst job/internship openings in the second half of 2021 alone!

The average annual salary of a data analyst ranges from Rs.5.3 lakhs (for fresher) to Rs.8.2 Lakhs (for senior analysts). Glassdoor reports that the national average salary for a Data Analyst is Rs.5 Lakhs.

So, wouldn’t it be nice to land your dream job as a Data Analyst in one of the big companies?

That is where we are going to help you :)

Recently, we reached out to Akash Dongre, a Senior Data Analyst at Accenture. In our discussion, he shared some valuable insights into what a Data Analyst does and explained the Accenture interview process. He concluded by providing some key tips and suggestions for job seekers to follow.

So, let’s get to it.

The Role of a Data Analyst at Accenture

Data Analysts, to put it simply, make sense of raw data and help in making them presentable in a way that they can be used to make data-driven decisions. This role requires the amalgamation of advanced technical, logical, and leadership skills.

According to Akash, a typical data analyst role at any company involves:

👉 Designing and maintaining data systems and databases.

👉 Capturing data with ETL tools

👉 Interpretation of data sets using statistical tools, finding out patterns and trends for predictive analytics efforts.

👉 Making use of SaaS, Python, and R programming to mine relevant data from primary and secondary resources.

👉 Making use of Data Visualization tools like Spotfire, Tableau, and Qlikview to present data in a comprehensible way.

The Prerequisites to applying for a Data Analyst role

Akash explains that the prerequisites for Data Analyst roles differ from company to company. Anyone pursuing a degree in Data Analytics or passing out from other disciplines must possess some rudimentary training of a few programming languages, data mining tools, and testing systems.

He further adds that a typical Data Analyst role requires a candidate to have:

☑️ Bachelor's Degree in a quantitative discipline (Economics, Engineering, Computer Science, Math, Statistics)

☑️ 1-2 years experience in analytics or management consulting

☑️ Proficiency in using SQL and querying relational databases

☑️ Experience in at least one statistical programming language (SAS, R, Python)

☑️ Experience in at least one data visualisation tool (Spotfire, Tableau, Qlikview)

☑️ Experience with project management.

☑️ Knowledge of spreadsheet tools like Google Sheets and Excel.

The Interview Process at Accenture

Akash explains that all Accenture interviews consist of three rounds provided, it is not a project-specific hiring or managerial acquisition. The main three rounds (along with the resume sorting round) are:

  1. Verbal Ability
  2. Technical Interview
  3. HR and Behavioural Interview

🟢 Resume Sorting

Your resume and cover letter land right in the hands of the recruiter who then matches the said resume with the posted job description and matches the prerequisites with the candidate’s qualifications.

If your resume fits the role, you will be scheduled for an initial screening interview and the Accenture team will directly contact you. If the resume was not the right fit, you will be notified by email directly. The Accenture Recruitment team keeps your details for any future opportunities at the company.

One of the Senior Recruitment Specialists at Accenture Toronto has clarified about-What happens to a resume after you click “Submit”

What does the recruiter look for in a resume for data analyst roles?

🔹 Relevant work experience i.e. experience (ideally 1-2 years) that corresponds with the role you have applied for

🔹 Number of projects you have managed or been a part of previously

🔹 Statistical Knowledge (helps to have a strong stats-maths background)

🔹 Proficiency in SQL, R and Python

🔹 Whether the resume is concise and to the point

🔹 Educational Background (helps to be from STEM background)

Check out these 8 powerful resume tips and the article by Will Hillier on How to write a great Data Analyst Resume?

🟢Aptitude/Verbal Ability/ Written:

This round comprises three different sections in the form of analytical aptitude, verbal ability, and attention to detail. Akash adds that each candidate gets 55 questions to answer in 60 minutes. These questions test your command of English, logical reasoning, and analytical aspects to the fullest.

Candidates clearing this round proceed to the second round- The Technical Interview. You can find some interview question examples for the 1st round, here.

🟢 Technical Interview:

According to Akash, there is no fixed pattern as to which questions can be asked by the panel. You will be questioned about each of the hard skills mentioned in your resume along with a few puzzles. The technical aspects will also be tested with a few functional problems like performing a Bubble sort, Binary Search, or an Insertion Sort.

Candidates with CS educational background will be expected to write codes during the interview.

The line of questions in this round is mostly based on key programming concepts for C++, Java, Python, and SQL. Therefore, you should be prepared with Data Structures and Algorithms, Operating Systems, and a programming language of your choice.

Learn to Solve Common Questions based on DSA from Experts

Candidates who can back their skills and answer most of the tricky puzzle questions with aplomb proceed to the next round.

🟢 HR and Behavioural Interviews:

In this round, your soft skills will be assessed by the interviewers. They will ask you questions about your current company and role (if any) or will ask you to say something about yourself (the usual “Tell me about yourself” prompt).

This is the round where you will need to explain your experience at the previous company and why you want to join Accenture. The key tip here is to describe projects in a descriptive manner highlighting your role in the smooth completion of the same. Basically, in this round, the panel will delve deep into your resume so, it is important to be able to back everything you have added there.

For a fresher, it helps to have a few internships and projects under your belt before you apply for a job at Accenture. Then, this round becomes much more about your projects and your industry know-how and level of expertise in the programming languages.

Here are some of the common questions asked:

✪ Tell me about yourself

✪ Why Accenture?

✪ How do you see yourself five years from now?

✪ What are your strengths and weaknesses?

✪ Questions from resume- regarding hard skills and portfolio

✪ Questions from Internship/prior projects

Common Mistakes Made by Candidates & How to Avoid Them

Though some mistakes are usually trivial nature, they can have a lasting impression on the recruiter.

Some of these mistakes listed below can give you a better idea of what exactly not to do :)

🟠 Listing technologies/programming languages that are not relevant to data analytics:

Akash explains that many candidates often list projects and skills in languages like CSS, HTML, and testing systems that are not considered relevant to an interviewer for a Data Analyst role.

Despite the importance of the aforementioned technologies in the market, the world of data analytics demands proficiency in R Programming, Python, and SQL and, projects involving the use of the same as well.

🟠 Lying on the resume:

Many candidates end up listing many programming languages and other hard skills just to get to the interview round. Some candidates also list AI and Machine Learning to leverage the boom of the said technologies, to land the interview. This doesn’t work because, in the technical round of the interview, each candidate is bombarded with tricky questions about each technology or language they have listed. So, at one point during the interview, your frailties will catch up to you.

🟠 Lack of effective communication:

In many cases, the candidates know what an “element” in a programming language like R does but, they can’t explain the correct definition and the work done by an “element”. In most cases, candidates actually know the answer but they are not able to communicate the thought process behind it, properly.

This is due to either a lack of clarity in your concepts or a lack of practice before the interview. Either way, going over your materials for data analyst interviews should help. Upskilling with a few additional courses should also help you learn new languages and technologies with ease.

🟠 Long Resumes:

With virtual hiring, a 4-5 pages-long resume doesn’t work as there are many submissions to Accenture from all over the country. A clean and concise resume is the way to go. There you should be listing all of the hard skills you possess that match the job description and its requirements. Moreover, you need to keep working on improving your cover letters all the time. Here’s a helpful guide.

Do Mock Interviews help in improving verbal skills?

Akash explains that nowadays, many services offer industry-specific practice interviews or mock interviews as known in common parlance.

The mentors you choose for the mock interview sessions will bombard you with all the questions that will be asked in your actual data analyst job interview.

Moreover, in these sorts of interviews, real interview challenges and rounds will be simulated by the people who have gone through the same and are now employed as a Data Analyst at your dream company.

Before mock interviews, candidates used to prepare the top questions but ended up getting confused during the actual interview. In a comprehensive research by Macrothink Institute, there was a severe lack of confidence reported in interview candidates. Giving mock interviews regularly can help solve this problem with aplomb.

Prepare with an Accenture mentor for your next Data Analyst interview!

Tips for Virtual Data Analyst Interviews at Accenture

  1. Proper internet connection
  2. Reach out to HRs on LinkedIn for online interviews
  3. Focus on shortening your resume
  4. Keep all of your files, projects and certificates ready for presenting
  5. Use proper headphones having a microphone.

Tips for aspiring Data Analysts:

🔹 You should be able to read and understand data on your own

🔹 You should know what exactly a data analyst role entails

🔹 Master SQL and a few programming languages as much as you can

🔹 You should attain proficiency in data mining and visualisation tools

🔹 Develop lots of projects

🔹 Keep learning and keep yourself updated with the latest trends in Data Analytics

🔹 Upskill by learning new programming languages all the time

🔹 Connect with top Data Analysts on LinkedIn or any other such platforms

And, always remember...

Data has a better idea- glow-sign

Good luck!

Get to know Akash Dongre:

Akash has been working at Accenture since the start of 2021 as a Senior Analyst. He completed his graduation from SVCE Indore in 2015.

He started his work life as a Data Reporting Analyst for IQVIA (formerly Qunitiles and IMS health) and worked there for more than 2 years. He then joined Tata Consultancy Service (TCS) in the same designation and worked there for 2 & a half years. At TCS he was a part of multiple projects and gained expertise in Tibco Spotfire, Python and Tableau.

In January, he decided to join Accenture. He has been eager to make use of his 5 years of experience in this field to mentor young data analysts to land their dream jobs. You can connect with him through his linked In LinkedIn profile or choose him as your mentor.