Data analysts use programming languages like SQL, Python, and R, as well as data visualization software and statistical analysis, to analyze data and disseminate it throughout their organizations. Data analysts need to collaborate with cross-functional stakeholders and work with structured data sets to create visualizations that are easily digestible for those without deep technical knowledge or the time to parse a lot of information in a short time.
Working as a data analyst requires a deeper understanding of parsing complex data than the average person may have. It’s also a role that requires you to communicate complex concepts in an easy-to-understand way. Last but not least, data analysts must refine their intuition for predicting behavior and outcomes. Once you’ve mastered all of that, you can potentially unlock any number of rewarding career paths, along with a sizable salary.
(Before we begin, it's also noting that this role isn't interchangeable with 'data scientist.' In general, data scientist jobs are much more strategic, and they often take a more holistic approach to the company’s data.)
But how does one actually become a data analyst? We spoke to a few experts on what it takes to get started (and remain working) in this role.
What education is necessary to become a successful data analyst?
“A data analyst is someone who studies data and information to help organizations make better decisions,” says Boris Jabes, CEO at Census. “Generally, the most successful analysts have at least a bachelor's degree in a field such as mathematics, statistics, computer science, or economics. Many data analysts also have experience working with databases and programming languages. In addition, strong critical thinking and problem-solving skills are essential for success in this role.”
Jabes has a degree in math and computer science from Waterloo University, along with a Master's in Information Networking from Carnegie Mellon University. However, he adds, “some data analysts may also choose to pursue degrees such as a Master's in Data Science. These programs can provide additional training in areas such as data mining, machine learning, and predictive analytics.”
Justin Logerfo, principal consultant at Final Approach Consulting LLC, tells Dice: “To become a data analyst, you’ll need an undergraduate degree in business, math, science, or engineering and be quantitatively focused.”
But Neetha Sindhu, director of data and analytics at Envoy Global, disagrees that a STEM degree is critical. “I would never say a certain degree is required to become a data analyst, although in my opinion a formal education in programs that include information systems or software engineering combined with a hint statistical modeling lays a great foundation for someone to become a successful Data Analyst.
Over the years, Sindhu adds, “I have encountered a few brilliant data analysts who never had a formal education in any of the areas I mentioned. So yes, formal education or not, it is possible to learn acquire the skills required to be a successful data analyst.”
What skills are necessary to have a successful career?
The list of necessary skills for data analysts is actually quite long. “Basic office skills like MS Office, Google Suite, and Excel,” Logerfo says. “From a technical standpoint, having SQL coding ability for relational database access in platforms like AWS, Snowflake, Teradata, and MySQL matters. R and Python for deep statistical analysis and data visualization are other hard skills that a data analyst should start to become familiar with.”
Those who succeed in this role must inevitably master data visualization tools such as:
In addition, they’ll need to master presenting the visualizations and results from those tools to stakeholders at all levels of an organization, including executives. That demands not only communication skills, but also critical thinking. Keep in mind that, once you’ve mastered these skills, it’s key to list them on your data analyst resume: automated resume-scanning software will often check for their presence before sending your resume to a real human being.
The overall workflow looks like this, Logerfo adds: “A data analyst must be able to understand what data they need for an analysis, how to clean, prep the data for analysis, begin the analysis, identify key insights, and provide recommendations on what happened, why it happened and what to do next.”
Which skills should I focus on?
“I would break this down to two categories—technical and non-technical skills,” Sindhu adds. “At minimum, a data analyst would require to be fluent in at-least one querying language like SQL, one data manipulation language like Python, one BI tool like Tableau, and last but not the least—must be proficient with Excel. That cover technical skillset and as for non-technical skills, a successful data analyst is one who has a good business sense and can translate data into actionable insights.”
Jabes agrees that programming language proficiency, database management, and data interpretation matter, adding: “One of the most important skills for a data analyst is the ability to interpret data. This data can be in the form of numbers, text, images, or even video. A data analyst will need to be able to understand this data and extract meaning from it. This can be used to help make decisions for businesses or organizations.”
“A data analyst will often have to deal with complex problems that require creative solutions,” Jabes continues. “This means that critical thinking skills are essential for this job. A data analyst will need to be able to think outside the box in order to find the best solution for a problem.” During the job interview process, hiring managers and recruiters will nearly always ask you about data analysis challenges you’ve overcome using your skills; come prepared with stories that put your skills, knowledge, and problem-solving in the best possible light.
Is there any specific training a data analyst should go through?
“I highly recommend training in data modeling, data warehousing concepts, data analytics and BI (reporting), and data science,” Sindhu tells Dice. “Even though a data analyst is not building a data warehouse and is only a consumer of it, I believe understanding the concepts of how a data warehouse is designed and built is extremely crucial for someone to succeed as an analyst.”
Many data-analysis platforms will offer free training via their websites, often for free. Learning at your own pace is a great way to fail and learn from your mistakes without any consequences.
