How to prepare for a Data Analyst Interview 
5 Things to prepare before a Data Analyst interview:
In this video, we will go through the 5 things you need to prepare before a data analyst interview. Data analyst interview questions and answers & more.
1 – Research the Company & the Role
The first thing you should do, is simply go to the company’s website and read about the company. You should make notes about:
• What does the companies do?
• When it was founded and by whom?
• Who runs the company now; CEO name?
• What is the company’s mission & vision?
• What are the company’s core values?
• What industry is the company operating in? (tech? retail? Finance, etc)
• Who is the company trading with? Who are their clients / customers?
• Learn about what the analytics team you are about to join does
2 – Prepare for the most universal & frequently asked questions
There are some “universal” interview questions which apply to all roles (not just Data Analysts) and are almost always asked in interviews. Make sure you prepare for the following questions:
• Tell me about yourself?
o Talk about your academic background and focus on the data related modules / projects. Talk about your work experience with a focus on the analytical tasks you were performing. Close with a reason “why you are there”; which is obviously going to be that you love analytics and you love that company 😊.
• Why you want to join this company?
o Pick the “thing / project” that the company completed from their website and talk about how that “thing / project” excites you and makes you want to work for that firm
• Why you want to become a Data Analyst or pursue a career in data analytics?
o Pick a data related project or a data related task you were doing that you love doing it and talk about that
• What do you know about this company?
o Talk about what I mentioned in Step 1 (beginning of the article)
• Why should I hire you?
o Talk about all the data related skills you have and make sure you link them with what the Job Description asks the candidate to have. This “link” is crucial
• What are your strengths?
o Pick 2 / 3 data related strengths and talk about times you applied them
• What are your weaknesses?
o Pick a weakness which is not a major in data analytics like “I get nervous speaking in large groups” and make sure you talk about the steps you are taking / took to overcome this.
3 – Brush your technical skills
The majority of the data analyst interviews require you to take some sort of test; which is usually an Excel test. If you are applying to an experienced data analyst job then you will probably need to brush your SQL skills too. For the Excel test, make sure you practice the following:
• Creating / sorting / filtering tables
• Aggregating data
• Summarizing data
• Creating graphs / charts
• Pivot Tables
4 – Prepare to speak about a “Data” project you completed
Even if you are not asked, try to find a way to talk about a data project you have completed either at University, on-line or during work experience. This is an opportunity to show the interviewer that you have experience working on data projects. Talk about the “problem formulation” phase, the data gathering phase, the cleaning phase, the transformation phase, the tools used for the analysis, the techniques you used for the analysis and the outcome of the project.
5 Bonus tip – Link all your answers with data related skills / tasks
Since you cannot possibly prepare for all possible questions, especially the ones about your previous work experience, you will need to make sure that you link all your answers to data related skills. For example, if the interviewer asks you to tell him about your work experience, make sure you flash out skills like communication skills, management skills, speak about the analytical tasks you were performing daily and the related tools like Excel. Don’ just say “I used to work as a “barman” and my job was to serve drinks. Expand on data related skills. I have made a video where I speak about the data related skills (link in the description).
Data Analytics Course Link: http://ipidata.teachable.com/
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Source. First Published on YouTube
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