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…
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…
A data analyst is someone who uses technical skills to analyze data and report insights.
On a typical day, a data analyst might use SQL skills to pull data from a company database, use programming skills to analyze that data, and then use communication skills to report their results to a larger audience.
It's a fulfilling job that pays well. Being a data analyst also provides experience that can be beneficial for stepping into more advanced roles like data scientist.
1Learn the technical skills (SQL and some data analysis with Python or R)
2Learn the fundamentals of statistics
3Build data analysis projects that showcase your hard and soft skills
So you've decided you want to be a data analyst. Or maybe your goal is to be a data scientist, but you know many entry-level jobs are analyst roles. In either case, you're going to need to master data analyst skills to get you where you want to go.
But what are those skills? What are the things you need to know? In this article, you'll learn the eight key skills you'll need to get a job as a data analyst.
We'll be focusing on skills and not on tools (like Python, R, SQL, Excel, Tableau, etc.) Our focus will be what you'll need to do as a data analyst, not how you do those things.
Tools — the how — will vary depending on the exact role, the company that hires you, and the industry you end up working in. You can take the data analyst skills from this article and apply them using the tools that you're learning with, or that suit the industry you're looking to break into.
The research for this article was taken from the planning for our Dataquest Data Analyst paths. To make sure we teach the right mix of skills, we did a lot of research to understand what data analysts really do.
This research included interviews with data analysts, data scientists, and recruiters/hiring managers for data roles. We also conducted a review of existing research on the topic.
Research shows that data cleaning and preparation accounts for around 80% of the work of data professionals. This makes it perhaps the key skill for anyone serious about getting a job in data.
Commonly, a data analyst will need to retrieve data from one or more sources and prepare the data so it is ready for numerical and categorical analysis. Data cleaning also involves handling missing and inconsistent data that may affect your analysis.
Data cleaning isn’t always considered “sexy”, but preparing data can actually be a lot of fun when treated as a problem-solving exercise. In any case, it's where most data projects start, so it's a key skill you'll need if you're going to become a data analyst.
It might sound funny to list “data analysis” in a list of required data analyst skills. But analysis itself is a specific skill that needs to be mastered.
At its core, data analysis means taking a business question or need and turning it into a data question. Then, you'll need to transform and analyze data to extract an answer to that question.
Another form of data analysis is exploration. Data exploration is looking to find interesting trends or relationships in the data that could bring value to a business.
Exploration might be guided by an original business question, but it also might be relatively unguided. By looking to find patterns and blips in the data, you may stumble across an opportunity for the business to decrease costs or increase growth!
A strong foundation in probability and statistics is an important data analyst skill. This knowledge will help guide your analysis and exploration and help you understand the data that you're working with.
Additionally, understanding stats will help you make sure your analysis is valid and will help you avoid common fallacies and logical errors.
The exact level of statistical knowledge required 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 need a much more rigorous understanding of those areas than you would otherwise.
Data visualizations make trends and patterns in data easier to understand. Humans are visual creatures, and most people aren’t going to be able to get meaningful insight by looking at a giant spreadsheet of numbers. As a data analyst, you'll need to be able to create plots and charts to help communicate your data and findings visually.
This means creating clean, visually compelling charts that will help others understand the data. It also means avoiding things that are either difficult to interpret (like pie charts) or can be misleading (like manipulating axis values).
Visualizations can also be an important part of data exploration. Sometimes there are things that you can see visually in the data that can hide when you just look at the numbers.
It's very rare to find data role that doesn't require data visualization, making it a key data analyst skill.
As a data analyst, you'll need to empower others within your organization to use data to make key decisions. By building dashboards and reports, you’ll be giving others access to important data by removing technical barriers.
This might take the form of a simple chart and table with date filters, all the way up to a large dashboard containing hundreds of data points that are interactive and update automatically.
Job requirements can vary a lot from position to position, but almost every data analyst job is going to involve producing reports on your findings and/or building dashboards to showcase them.
The ability to communicate in multiple formats is a key data analyst skill. Writing, speaking, explaining, listening— strong communication skills across all of these areas will help you succeed.
Communication is key in collaborating with your colleagues. For example, in a kickoff meeting with business stakeholders, careful listening skills are needed to 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 — you'll almost certainly need to write up your analysis and recommendations.
Being clear, direct, and easily understood 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 won’t be worth much unless you can explain what they mean and convince your colleagues to act on your findings.
Domain knowledge is understanding things that are specific to the particular 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. In contrast, if you're analyzing data about mechanical systems, you might need to understand those systems and how they work.
Domain knowledge changes from industry to industry, so you may find yourself needing to research and learn quickly. No matter where you work, if you don't understand what you're analyzing it's going to be difficult to do it effectively, making domain knowledge a key data analyst skill.
This is certainly something that you can learn on the job, but if you know a specific industry or area you’d like to work in, building as much understanding as you can up front will make you a more attractive job applicant and a more effective employee once you do get the job.
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 a key skill.
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 be innovative in how you approach a problem. The data you're using might be incomplete. Or 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.
The exact definition of “data analyst” varies a lot depending on whom you ask, so it's possible not all of these skills will be required 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 our students.
So far in this article, we've looked at critical skills for data scientists from a broad perspective. Now, let's dig a little deeper into some of the specifics.
If you're looking for a job as a data analyst, what kinds of things will you need on your resume? And how much can you expect to get paid if you get the job? Let's take a look at some of the specifics.
Generally speaking, employers will expect data analysts to have a bachelors degree in something, and a degree in a quantitative/STEM field may help. However, a degree is not required. Data analysts are in high demand, and employers are concerned primarily with an applicant's actual skills — if you have the right skills and the projects to prove it, you can get a data analyst job without a degree.
People often ask whether some kind of data science certificate is required or helpful for getting jobs in data. The answer is no. Employers are primarily concerned with skills, and when we spoke to dozens of people who hire in this field, not a single one of them mentioned wanting to see certificates.
Certificate programs can be helpful if they teach you necessary skills, but employers aren't going to be scanning your resume looking for a data analyst certificate. Nor are they likely to care much about any certificates you've earned. They'll be looking for proof of actual skills.
Above, we've talked about the skills data analysts need, and we've explained why you probably don't need any paper qualifications to become a data analyst.
What you do need, though, is proof of the skills you have. Simply listing that you know SQL and Python on your resume is not enough, even if those are the job requirements listed in the job posting. You need to prove you have those skills.
The easiest way to do this is with prior work experience, of course — if an employer can see you've already worked as a data analyst, and call up your old boss for confirmation, you're in good shape.
But if you're reading this article, you probably don't have prior experience in the field. In that case, what you need is a portfolio of data analysis projects that potential employers can peruse. Having an active Github account with relevant projects (and linking to this account from your resume) is probably the quickest and easiest way to set up a portfolio.
The projects you showcase should be your best, and they should demonstrate that you have the skills listed in this article. Use a format like a Jupyter Notebook or R Markdown document to showcase your code along with written explanations and charts that a non-technical hiring manager or recruiter can understand. (Remember, you need to be showcasing your communication skills in addition to the technical skills you used to do the analysis).
The more relevant you can make these projects to the companies where you're applying, the better your chances will be of getting a call back.
According to Indeed.com as of April 6, 2021, the average data analyst in the United States earns a salary of $72,945, plus a yearly bonus of $2,500.
Experienced data analysts at top companies can make significantly more, however. Senior data analysts at companies such as Facebook and Target reported salaries of around $130,000 as of April 2021.
We looked at some open "Data Analyst" jobs (as of April 2021) and pulled together some lists of the technical and non-technical skills they list. As you can see, what's required does vary a bit from company to company.
Major Insurance Company:
Major Political Organization:
Major Car Company:
Popular Social Media Platform:
Major University System:
That's just a tiny sample of what's available. And of course, we've simplified these job postings, boiling them down to just the most essential listed skills.
Even though there are differences, it's clear the same skills are required for many of these jobs:
If you're serious about becoming a data analyst and you're starting from scratch, don't worry! You can do this. It helps to take a step-by-step approach.
1Learn the basics of programming in R or Python. At Dataquest, our data analyst learning paths in Pythonand R are designed to help you start from scratch, even if you've never written a line of code before.
2Start building projects. As early as possible, start putting together data projects. These early projects will help you solidify the skills you're learning and keep you motivated. You should keep building projects of increasing difficulty and complexity as you work through the later steps here (Dataquest's learning paths have built-in guided projects to help with this).
3Learn SQL (and other technical skills). Different data analyst jobs will have different specific requirements, but almost any analyst job will require some SQL skills. We've written a bit about why SQL skills are critical, so don't skip that, but there are other technical skills that can make your life easier, too. At Dataquest, our data analyst learning paths will take you through all of these skills in a logical sequence, so each skill builds on the previous one and you don't have to worry about what to learn next.
4Share your work and engage with the community. This will help you learn, collaborate, and start building a "personal brand" as a data analyst. Sharing your work can feel intimidating, but you never know what kinds of job offers can come from the right person happening to come across a cool project you've shared.
5Push your boundaries. Once you've mastered the basics, be sure you keep pushing with your projects so that you're learning new skills. Don't fall into the trap of doing similar projects over and over again because you're comfortable doing them. Try to include at least one thing you've never done before in each new project, or go back to old projects and try to improve them or add complexity.
In this article, we’ve covered what you need to learn to become a data analyst. If you want to learn the how, and build the technical skill set you need to successfully get a data analyst job, check out our interactive online data analysis courses.
Without ever leaving your web browser, you’ll write real code to analyze real-world data as you learn interactively using our proven approach.
At Dataquest, our vision is to become the world's first option for learning data skills. In order to achieve that, we craft our curriculum to teach the students the skills students they need to get jobs in data.
Specifically, the data analyst skills we’ve covered in this article are the basis for our two “data analyst” learning paths:
You can start both paths for free and start your journey to being a data analyst today!
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