8 Data Analyst Skills Employers Need to See in 2023

What is a Data Analyst?

A data analyst is someone who uses technical skills to analyze data and report insights.

On a typical day, a data analyst might use the following skills:

• SQL skills to pull data from a database
• Programming skills to analyze that data
• Communication skills to report their findings

However, which skills are the most important to land a data analysis job? To answer that question, we performed many hours of research, including interviews with data analysts, data scientists, and hiring managers.

Here’s what we learned.

What Skills Does a Data Analyst Need?

Because the data science tools you will use vary depending on the role, the company, or the industry, we learned to focus on skills and not on tools (like Python, R, SQL, Excel, Tableau, Power BI, etc.). 

Here’s what you’ll need to do as a data analyst (not how to do it).

Here are the eight most important data analyst skills:

• Data cleaning and preparation
• Data analysis and exploration
• Statistical knowledge
• Creating data visualizations
• Creating dashboards and reports
• Writing and communication
• Domain knowledge
• Problem solving

And here’s an explanation of each . . .

1: Data Cleaning and Preparation

Research shows that data cleaning and preparation will consist of about 80% of the work of most data professionals. That means this skill is vital.

A data analyst will commonly need to retrieve data from one or more sources and prepare it for numerical and categorical analysis. Data cleaning also involves resolving missing and inconsistent data that may affect analysis.

In data analytics, data cleaning isn’t always exciting, but preparing data can be fun and challenging when treated as a problem-solving exercise.

Interested in this skill? Check out our beginner-friendly data cleaning courses.

2: Data Analysis and Exploration

It might sound strange to mention “data analysis” in a list of required data analyst skills, but analysis as a specific skill is necessary.

Fundamentally, data analysis involves taking a business question or a need and analyzing relevant data to develop an answer to that question.

Another form of data analysis is exploration. Data exploration involves looking for interesting trends or relationships in the data that could bring value to a business.

A business question might guide exploration, but it also might be relatively unguided. By looking to find patterns in the data, you may stumble across an opportunity for the business to decrease costs or increase growth.

Interested in this skill? Check out our list of data analyst courses.

3: Statistical Knowledge

Probability and statistics are important data analyst skills. This knowledge will guide your analysis and exploration and help you decipher the data.

Additionally, understanding statistics will also help you ensure your analysis is valid, and it will help you avoid common fallacies and logical errors.

The exact level of statistical knowledge necessary will vary depending on the demands of your particular role and the data you’re working with. 

For example, if your company relies on probabilistic analysis, you’ll want a much more rigorous understanding of those areas than you would otherwise need.

Interested in this data analytics skill? Check out our probability and statistics courses.

4: Creating Data Visualizations

Data visualizations clarify data trends and patterns. Humans are visual creatures — that means most people will understand a chart or a graph more quickly than they will understand a spreadsheet.

This means creating clean, visually compelling charts that will help others understand your discoveries. It also means avoiding things that are either difficult to interpret (like pie charts) or that can be misleading (like manipulating axis values).

Visualizations can also be an important part of your data exploration. Sometimes, there are things that you can see visually in the data that can hide when you look only at the numbers.

(Image source)

It’s very rare to find a data science role that doesn’t require data visualization, which makes it a key data analyst skill.

Interested in this skill? Check out our data visualization courses.

5: Creating Dashboards and Reports

As a data analyst, you’ll need to empower others to use data to make key decisions. By building dashboards and reports, you’ll give others access to important data by removing technical barriers.

This might take the form of a simple chart and a table with date filters, or it might be a sophisticated dashboard containing hundreds of interactive data points.

Job descriptions and requirements can vary from position to position, but almost every data analyst job is going to involve producing reports on your findings or building dashboards to showcase them.

Interested in this skill? Learn how to create dashboards and reports with our Power BI courses.

6: Writing and Communication

The ability to communicate in multiple formats is another key data analyst skill. Writing, speaking, explaining, and listening are all communication skills that will help you succeed in any data analytics role. 

Communication is key when collaborating with your colleagues. For example, in a kickoff meeting with business stakeholders, careful listening skills help you understand the analyses they require.

Similarly, during your project, you may need to be able to explain a complex topic to non-technical teammates.

Written communication is also incredibly important — especially when you’re writing a summary of your analysis or explaining a discovery in your data exploration.

Communicating clearly and directly is a skill that will advance your career in data. It may be a “soft” skill, but don’t underestimate it.

The best analytical skills in the world are worthless if you can’t explain what they mean and if you can’t convince your colleagues to act on your discoveries.

7: Domain Knowledge

Domain knowledge is understanding topics that are specific to the industry and company that you work for. 

For example, if you’re working for a company with an online store, you might need to understand the nuances of e-commerce.

By contrast, if you’re analyzing data about mechanical systems, you might need to understand how those specific systems work.

No matter where you work, if you don’t understand what you’re analyzing, it’ll make executing your job significantly more difficult.

This is certainly something that you can learn on the job. However, if you know a specific industry or area you’d like to work in, then building as much understanding as you can up front will make you a more attractive job applicant — and a more effective employee once you get the job.

8: Problem-Solving

As a data analyst, you’re going to run up against problems, bugs, and roadblocks every day. Being able to problem-solve your way out of them is another key skill that will be valuable as a data analyst. 

Here are a few potential scenarios: 

• You might need to research a quirk of some software or coding language that you’re using.

• Your company might have resource constraints that force you to innovate how you approach a problem.

• The data you’re using might be incomplete.

• You might need to perform some “good enough” analysis to meet a looming deadline.

Whatever the circumstances, strong problem-solving skills are going to be an incredible asset for any data analyst.

Other Data Analyst Skills

The exact definition of “data analyst” varies depending on whom you ask, so it’s possible not all of these skills will be necessary for every data analyst job.

Similarly, there may be skills some companies will require that aren’t on this list. Our focus here was to find the set of skills that most data analyst roles require in order to build the very best data analyst learning paths for students.

Getting Hired as a Data Analyst

If you want to build the technical skill-set you need to successfully get a data analyst job, check out our interactive online data analysis courses. You’ll write real code directly in your browser to analyze real-world data.

Dataquest's unique pedagogy and project based learning style will help you learn quickly, retain concepts, and grow confidence.

Specifically, the data analyst skills we’ve covered in this article are the basis for our two “data analyst” learning paths:

• Data Analyst in Python
• Data Analyst in R

Completing these courses will improve your data analyst resume (and portfolio), which will help you stand out as a candidate. You can start both paths for free and begin your journey to becoming a data analyst today.