As new data analysts we like to focus on the hard skills like SQL and Power BI. Skills that can be learned through courses, formal schooling or self learning. While having the right technical skills is important so is having the soft skills. I've heard from hiring managers that a lot of people tend to forget about the soft skills. This is where new analysts can shine. While you may not have previous experience as a data analyst you have plenty of transferrable skills.
Below I'll be going into a few key soft skills necessary for a data analyst. For each skill I've included examples of how other roles use these skills. Hopefully this will help you brainstorm how you can explain your skills in an interview.
The Skills
Communication
Communication is the act of transferring information from one person to another (or a group). It's a necessary skill for data analysts. Because the main role of an analyst is to help a company make informed business decisions with data. To make an informed business decision analysts need to understand the business context. They have to communicate with their co-workers, supervisors or stakeholders. The data the analyst needs to present these findings and recommendations to other people. Being able to explain complex ideas to people with a non-technical background is vital.
Examples:
An office manager who delegates work well within the company.
A recruiter who keeps the potential hire up-to-date on the hiring process.
A photographer who asks the right questions of their client to ensure the photos turn out right.
Problem Solving
This is the ability to find solutions to difficult or complex issues. Someone who's good at this can identify reasons why a problem exists then execute a plant to resolve it. Problem solving is vital for analysts. Analyzing and cleaning data isn't easy. Things can go wrong in the database or code and an analyst must be able to troubleshoot the problem so they can continue their work. Other problems may come up and it's good to be able to think on your feet and be innovative.
Examples:
An administrative assistant who creates a more efficient filing system.
A volunteer at a non-profit who creates a database to improve donor outreach.
A cashier who quickly comes up with a way to take orders when their register shuts down.
Critical Thinking
Critical thinking is the ability to think clearly and rationally in order to understand connections between ideas and/or facts. People who are critical thinkers will often think more deeply about an issue, ensuring that an idea, policy, or product is thoroughly thought through. As a data analyst you need to be able to ask the right questions to get the right information. Most of the time the results won't be clear. Being able to analyze a problem and look at it at different angles is vital.
Examples:
A teacher who creates a lessen plan to fit the needs of their students.
A paralegal who researches previous cases and relevant laws when drafting a legal document.
A veterinarian technician who makes keen observations during patient exams to make sure the patient gets the best treatment.
Teamwork
Teamwork is the ability to work well with others. A person who's good at teamwork: supports their team, motivates others, and both giving and receiving feedback. Data analysts collaborate with a variety of people. Whether that's other analysts or people in other departments. These people can be web developers, engineers, data scientists along with internal and external stakeholders. Being able to work in a team with other people is a necessary skill for any analyst.
Examples:
A waiter who works under pressure with the other restaurant staff while making sure customers get the best experience.
A stagehand who works with a team to ensure that a stage is quickly and accurately set during a musical.
A construction worker who must work with others to complete a home in a timely manner.
Attention to detail
This is the ability to be thorough and accurate with a task. It lessens the likelihood of mistakes. Data analysts need to be detail-oriented in their work. They're working with data and presenting their findings, these need to be as accurate as possible. Whether that's through analyzing code or creating a data visualization.
Examples:
A bookkeeper who goes through the company's accounts to ensure all the financial records are in order.
An engineer who reads through and debugs the code.
A nurse who makes sure their paperwork for each patient is correct.
Sources:
Below are sources I used for this blog post:
Comments