How to Become a Data Analyst

Data as an industry has been gaining traction rapidly over the past 10 years. With that comes huge career opportunities.

Now more than ever, companies are looking for specialists who can analyze data and present it in a digestible and solution-oriented manner. Data drives business decisions, and having experts define that data is crucial.

If you're interested in becoming a data analyst, here's how to become one, the most critical skills to thrive in a data analyst role, how much a career in data could earn you, and so much more.

What Is a Data Analyst?

So what exactly is a data analyst? The truth is there are many different interpretations of what it means to be a data analyst, depending on the niche.

According to Daphne Cheung, a senior data analyst for Disney streaming services, data analysts use data to derive some kind of insight that then provides business value for the company. In short, they perform statistical analyses on large datasets. An analyst is concerned with pulling data, understanding it, and then telling a story from that data.  

Cait Moran, a director of data science and data analytics instructor, explains that a data analyst is someone who relies on evidence to drive business decisions or actions. Their role is to understand data and tell important hidden stories that solve problems. 

Data science, while closely related to data analysis, is slightly different. Data scientists focus on things like machine learning and statistical modeling. They build entire projects based on machine learning models and utilize more sophisticated techniques, automation, and advanced algorithms to solve the problems they're looking for. Analysts work primarily on data visualization, insights, and storytelling. The technical skills required for data science positions are valuable in an analyst role.

What Does a Data Analyst Do?

A typical day in the life of a data analyst can vary depending on the company or the field.

These days, data analysts can really span a lot of different job titles, including product data analyst, business intelligence, technical data analyst, people analytics, and the list goes on. Data analysts can also be found in almost every domain that exists, including marketing, HR, supply chain, and more.

According to Moran, data analysts follow a typical roadmap and workflow that's pretty standard across industries. Data analysts break down the question they're seeking to answer by looking for data sources and then defining a strategy to execute based on those metrics. 

Once they retrieve data, they create a dataset, clean it, analyze it (look at different angles and perspectives that the data gives them), and then acknowledge the limitations and biases. Once they have determined an objective and tactical way to deliver the message of the data, they make a recommendation to the stakeholder, company, or person on how they should move forward. 

Cheung explains that a typical day could look like being left to your own devices and independently running analytics all day, or it could look like back-to-back meetings and ad hoc analyses.  

Either way, data analysis requires collaboration and strong communication skills. A data analyst meets with stakeholders, understands their needs, and then turns to their computer to figure out how to pull the data the stakeholder is interested in. They then figure out the best way to turn all of that data into a digestible story that provides business value.  

Besides ad hoc analyses, data analysts' routine tasks may include pulling data to keep track of monthly or quarterly performances or working with other analysts on bigger research projects.

What Skills Does a Data Analyst Need?

There are tons of hard skills, soft skills, and technical skills that are valuable in data analysis.

According to Moran, the most important technical skills are SQL and Python. She says to "get very good at querying things."

Someone looking to become a  data analyst must become familiar with tools and programs.

Data Analysis Tools and Programs:

"Having a skill set in some core technologies like Google's BigQuery or Amazon Redshift is really going to allow you to find specific positions with companies that may have already invested in these products," says Moran.

It's also important to stay open and interested in evolving data technology and understanding cloud technologies. Databases, primarily data warehouses, are the central place where data analysts spend their time, especially in larger enterprises. Moran also advises aspiring data analysts to familiarize themselves with APIs. Doing so opens doors at a variety of larger companies. 

In terms of soft skills, knowing how to tell a great story and understanding how to piece together insights in a way that benefits the people you're working with is crucial. For this reason, written and verbal communication skills are extremely important.

On top of that, knowing how to prioritize is key. Data analysis is in such high demand that you can be flooded with many requests throughout your work day. Knowing how to prioritize and organize those tasks is crucial.

Here are some key soft skills for data analysts:

What Qualifications Do You Need to Become a Data Analyst?

Transitioning into a data analyst role is a bit of a Catch-22 in that you don't get hands-on experience until you get the job. However, there are several things you can research or practice to meet the necessary qualifications.

As we mentioned earlier, it's important to be skilled in one or more programming languages and database querying languages. Familiarity with data warehousing, SQL databases, and data cleaning are also must-haves. Data analysts should also be well-versed in SAS, R, or SPSS.

Here are just a few places where you can practice your coding skills:

Beyond the technical, creative thinking and curiosity are essential skills to have. Because data can span various industries and companies, you must take the time to diligently read and dissect the data analyst job description. Search for keywords and see what gaps you need to fill. 

If you're currently in a non-data role and looking to transition, be proactive within your role. See where you can collect your own data and make an Excel spreadsheet. Present your visualizations in stakeholder meetings. You may not necessarily be asked to do this in your current job, but it's a great way to show initiative and leverage what you can at your current company.

Do Data Analysts Need Advanced Degrees or Certifications? 

The typical education required to become a data analyst is a bachelor's degree in information technology, computer science, math, or statistics. But it's certainly not limited to those three degrees.

For example, Cheung got a bachelor's degree in digital media and the internet with interactive systems as a concentration. The combination of visualization and art combined with programming and technical skills set her up for success in data analytics. Most entry-level data analyst jobs require at least a bachelor's degree but that trend is starting to change.

A master's degree in data science, data analytics, or big data management isn't necessary, but as with any other advanced degree, it will offer more job opportunities down the line.

Can You Get a Data Analyst Job With No Experience?

Besides a bachelor's or master's degree, there are several other great learning resources that you can utilize to build up your technical knowledge and experience. 

Completing certificate programs is especially great if you're looking to start your career in data. Earn your cloud certifications from AWS Certified Data Analytics, Azure, Google, or Oracle. 

Moran recommends looking for university professional development certificates like this bootcamp from the University of Kansas or this data science and visualization bootcamp offered by Northwestern. 

Self-Paced Online Data Analysis Courses:

Data analysis is growing increasingly popular. While this means that the industry is growing increasingly more complex, it also means that data analyst roles are in high demand. If you don't have any experience, you can use this to your advantage. You most likely already possess many transferable skills like problem-solving, attention to detail, teamwork, and verbal and written communication skills. 

To stand out as a stronger candidate, develop your portfolio. You can do this by taking on freelance projects, completing mock cases, and volunteering for data-related projects at your current position. Make sure to update your resume to reflect all of your relevant experience. Always remember to tailor your resume to each data analyst job that you apply for.

Where Can You Find a Data Analyst Job?

As is true with many job in tech, there isn't a single linear career path for finding a data analyst job. 

Search for data analyst job postings on websites like Angel.co and LinkedIn.

Connect with others and send some cold messages. Networking is the biggest job search resource, and informational interviews are your best friend. Follow influencers and thought leaders within the industry and join professional communities like DATAcated and DataOps Manifesto.

Also, make sure you are making it easy for hiring managers and recruiters to find you. Optimize your LinkedIn profile, create a personal portfolio website, and host your projects on GitHub. Make sure to articulate your relevant work experience through the lens of data. Highlight your critical thinking, collaboration, and organization skills whenever you can. 

How to Prepare For a Data Analyst Job Interview

A data analyst job interview usually comes down to two parts: a behavioral interview and a technical interview. On the behavioral side, the company is looking for things like company culture fit, as well as things like how you navigate conflict, communication, prioritization, and organization. To prepare, review common job interview questions and see where you can weave in storytelling. 

Technical interviews can look like live coding exercises or a technical showcase in which you complete a take-home assignment. You may be given data for which you are required to perform an exploratory analysis which you will then turn into a presentation. 

To study for your interview, Moran advises you to write up a bunch of mock cases—make them up or find them online from other companies. Draw out a diagram of all the various metrics that you could use to potentially respond to an interview question about the case. Make sure your response is data-oriented. Prepping for a case interview can be as simple as making up your own case and then asking yourself, how would I solve this problem using specific data sets?

As with any job interview, ensure you have researched the company. Knowing the business objectives of the company you are applying for will help you understand what kind of potential problems they are trying to overcome using data. Then, tailor your responses to provide the solutions they are looking for.

Data Analyst Salary 

Now the fun part: salary.

The average salary for a data analyst can range depending on your location, niche, and company. The U.S. Bureau of Labor Statistics puts the median data analyst salary at $82,360 annually.