7 In-Demand Data Analyst Skills to Get You Hired in 2022
Written by Coursera • Updated on
Transitioning to a career in data analytics can mean stable employment in a high-paying industry once you have the right skills.
Each year, there is more demand for data analysts and scientists than there are people with the right skills to fill those roles .In fact, according the US Bureau of Labor Statistics the number of job openings for analysts is expected to grow by 23-percent between 2021 and 2031, significantly higher than the five percent average job growth projected for all jobs in the country .
But, what skills are the most in-demand in the world of data?
These seven trending data science skills represent those with the most searches and enrollments by Coursera’s community of 87 million global learners (as of December 2021). To prepare for a new career in the high-growth field of data analysis, start by developing these skills.
Let’s take a closer look at what they are and how you can start learning them.
You can learn many of these data skills, including SQL, R, and data visualization, with the Google Data Analyst Professional Certificate on Coursera.Learn more about the programand how to get started for free.
Structured Query Language, or SQL, is the standard language used to communicate with databases. Knowing SQL lets you update, organize, and query data stored in relational databases, as well as modify data structures (schema).
Since almost all data analysts will need to use SQL to access data from a company’s database, it’s arguably the most important skill to learn to get a job. In fact, it’s common for data analyst interviews to include a technical screening with SQL.
Luckily, SQL is one of the easier languages to learn.
Get fluent in SQL: Develop SQL fluency, even if you have no previous coding experience, with the Learn SQL Basics for Data Science Specialization from UC Davis. Work through four progressive SQL projects as you learn how to analyze and explore data.
2. Statistical programming
Statistical programming languages, like R or Python, enable you to perform advanced analyses in ways that Excel cannot. Being able to write programs in these languages means that you can clean, analyze, and visualize large data sets more efficiently.
Both languages are open source, and it’s a good idea to learn at least one of them. There’s some debate over which language is better for data analysis. Either language can accomplish similar data science tasks. While R was designed specifically for analytics, Python is the more popular of the two and tends to be an easier language to learn (especially if it’s your first).
Learn your first programming language: If you’ve never written code before, Python for Everybody from the University of Michigan is a good place to start. After writing your first simple program, you can start to build more complex programs used to collect, clean, analyze, and visualize data.
3. Machine learning
Machine learning, a branch of artificial intelligence (AI), has become one of the most important developments in data science. This skill focuses on building algorithms designed to find patterns in big data sets, improving their accuracy over time.
The more data a machine learning algorithm processes, the “smarter” it becomes, allowing for more accurate predictions.
Data analysts aren’t generally expected to have a mastery of machine learning. But developing your machine learning skills could give you a competitive advantage and set you on a course for a future career as a data scientist.
Get started in machine learning: Andrew Ng’s Machine Learning Specialization from Stanford is one of the most highly-rated courses on Coursera. Learn about the best machine learning techniques and how to apply them to problems in this introductory class.
4. Probability and statistics
Statistics refers to the field of math and science concerned with collecting, analyzing, interpreting, and presenting data. That might sound familiar—it closely matches the description of what a data analyst does.
With a strong foundation in probability and statistics, you’ll be better able to:
Identify patterns and trends in the data
Avoid biases, fallacies, and logical errors into your analysis
Produce accurate and trustworthy results
Master modern statistical thinking: Get a refresher with the Probability and Statistics course from the University of London. If you’ve already picked up some programming, learn to apply your skills to statistical analysis through Statistics with Python from the University of Michigan or Statistics with R from Duke University.
5. Data management
Data management refers to the practices of collecting, organizing, and storing data in a way that is efficient, secure, and cost effective. While some organizations will have roles dedicated to data management—data architects and engineers, database administrators, and information security analysts—data analysts often manage data in some capacity.
Different companies use different data management systems. As you’re developing your skill set, it can help to gain a broad understanding of how databases work, both in physical and cloud environments.
Learn about data engineering: Get an overview of the modern data ecosystem with Introduction to Data Engineering from IBM. Learn more about the role data analysts, scientists, and engineers play in data management.
6. Statistical visualization
Gleaning insights from data is only one part of the data analysis process. Another fundamental part is telling a story with those insights to help inform better business decisions. That’s where data visualization comes in. As a data analyst, you can use charts, graphs, maps, and other visual representations of data to help present your findings in an easy-to-understand way.
Improving your data visualization skills often means learning visualization software, like Tableau. This industry standard piece of software empowers you to transform your analysis into dashboards, data models, visualizations, and business intelligence reports.
Get visual with Tableau: Once you’re comfortable working with data and data sets, practice creating powerful visualizations of your data with the Data Visualization with Tableau Specialization from UC Davis.
With econometrics, analysts apply statistical and mathematical data models to the field of economics to help forecast future trends based on historical data. Understanding econometrics is key for data analysts looking for jobs in the financial sector, particularly at investment banks and hedge funds.
Practice econometrics: Learn the three basic methods of econometrics and apply these models to problems in daily life with the Enjoyable Econometrics course from Erasmus University Rotterdam.
Tips for learning data analysis skills
Data analysts leverage these and other technical skills to help inform decisions at their organizations. Putting in the time and effort to learn these skills can set you up for a successful career as a data analyst. Here are a few quick tips for getting started:
Set aside time to regularly work on your skills
Learn from your mistakes
Practice with real data projects(Video) RoadMap With Minimal Skills To Become Data Analyst In 2022
Join an online data community
Build your skills bit by bit
If you’re ready to start building your skill set, explore more tips on how to rise to the challenge.
In this video, we will listen to data professionals talk about what employers look for in a Data Analyst.
Introduction to Data Analytics
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How to include data analyst skills on your resume
As you add new skills to your data analyst toolbox, be sure to update them on your resume as well. Include a “skills” section with a bulleted list of around five of your top data skills. If you list a skill on your resume, be prepared to discuss it in your interview.
It’s also a good idea to incorporate your skills in context. When you include data analysis projects or previous roles, try to include a sentence on how you used a particular skill to complete a task (e.g. “Wrote a Python script to scrape data using the official Twitter API” or “used Tableau to visualize product sales over time”).
Hear from practicing data professionals about what they think employers look for when hiring data analysts.
Read more: Data Analyst Cover Letter: Sample and Guide
Get started with Coursera
Start building many of these data analyst job-ready skills with the Google Data Analytics Professional Certificate through Coursera. Learn how to clean and organize data with SQL and R, visualize with Tableau, and complete a case study for your portfolio—no prior experience or degree required. Upon completion, you can start applying for entry-level jobs directly with Google and more than 130 other US employers.
Google Data Analytics
This is your path to a career in data analytics. In this program, you’ll learn in-demand skills that will have you job-ready in less than 6 months. No degree or experience required.
1,124,152 already enrolled
Average time: 6 month(s)
Learn at your own pace
Skills you'll build:
Spreadsheet, Data Cleansing, Data Analysis, Data Visualization (DataViz), SQL, Questioning, Decision-Making, Problem Solving, Metadata, Data Collection, Data Ethics, Sample Size Determination, Data Integrity, Data Calculations, Data Aggregation, Tableau Software, Presentation, R Programming, R Markdown, Rstudio, Job portfolio, case study
Frequently asked questions (FAQ)
If you are just starting out in data analytics, there are several proactive steps you can take to get into the career. Some concrete steps you can take to improve your chances of landing an entry-level data analyst job include:
– Obtain a credential through an educational program, such as a degree or professional certificate.
– Work on developing your technical skills, either through in-person or online instruction.
– Create a portfolio consisting of either self-directed or group projects.
– Gain experience through an internship or volunteer opportunity.
Read: How to Become a Data Analyst (with or Without a Degree)
Yes and no. While data analysts should have a foundational knowledge of statistics and mathematics, much of their work can be done without complex mathematics. Generally, though, data analysts should have a grasp of statistics, linear algebra, and calculus.
Workplace skills (also called “soft” skills or people skills) are all the intrinsic skills you use to do your job well. While data analysts are prized for their technical skills, you should also strive to hone your workplace skills in order to do your job well. Some of these skills include:
– Problem-solving: Aata analysts must be adept problem solvers, capable of identifying strategies for finding the answers to the questions that they ask.
– Collaboration: Data analysts must often work with others to solve problems and ensure that their objectives are achieved. As a result, collaboration is a key skill that data analysts use every day.
– Storytelling and communication: While data analysts spend their time looking at data to glean useful insights, they must also communicate those insights to others. One of the most effective ways to communicate to non-experts is by using storytelling to convey just why your data insights are important and what they mean to others.
Read: Hard Skills vs. Soft Skills: What’s the Difference?
Written by Coursera • Updated on
This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.
Why should we hire you answer for data analyst? ›
“I have previous experience working with projects that had similar problems to yours. I also have excellent communication skills and further technical knowledge that would be an asset to your company. The mix of technical and team skills I bring to the table make me an ideal fit for this role.”
- Be able to tell a story, but keep it Simple. ...
- Pay attention to Detail. ...
- Be Commercially Savvy. ...
- Be Creative with Data. ...
- Be a People Person. ...
- Keep Learning new Tools and Skills. ...
- Don't be Afraid to make Mistakes, Learn from Them. ...
- Know when to Stop.
- Give examples with critical situations on your job that demonstrate those skills.
- Describe a specific process or method you use.
- Think of major achievements and breakthroughs made possible by your analytical skills.
A data analyst should be curious, strategy-minded, able to operate in a systematic and scalable manner, and have excellent communication skills. Curiosity is one of the skills Ste. Marie believes is most critical for data analysts to possess. “The only trait that you can't teach analysts is curiosity,” he says.How do I become a data analyst with no experience? ›
- Get a foundational education.
- Build your technical skills.
- Work on projects with real data.
- Develop a portfolio of your work.
- Practice presenting your findings.
- Get an entry-level data analyst job.
- Consider certification or an advanced degree.
For starters, I have all the skills and experience listed in the job description, and I'm confident that I can make an immediate impact on your company. It's not just my background in leading successful projects for Fortune 500 companies, but also my passion for the industry that drives me to succeed.Why should we hire you for this role *? ›
I'm a good hard worker and self-motivated person based on my qualifications and experience you can hire us. Sir, I am a good hard worker and self-motivated, and it helps me to showcase my skills and knowledge in our company which helps in the growth of the company.How would you describe yourself as a data analyst? ›
"I've always had a knack for working with numbers, collecting data, and finding trends and patterns that others miss. Being a data analyst is a bit like being a detective—tracking the clues within the numbers to find the culprit is always rewarding.Which is best tool for data analysis? ›
Microsoft Excel is the most common tool used for manipulating spreadsheets and building analyses. With decades of development behind it, Excel can support almost any standard analytics workflow and is extendable through its native programming language, Visual Basic.What is data analytics in simple words? ›
Data analytics (DA) is the process of examining data sets in order to find trends and draw conclusions about the information they contain. Increasingly, data analytics is done with the aid of specialized systems and software.
How do you explain analytical skills in an interview? ›
- Gather data to inform your decisions.
- Assess both positive and negative situations to improve your processes.
- Are able to develop processes.
- Evaluate information through critical thinking.
- Think through problems to find solutions.
- Set and achieve goals.
“I think the two biggest traits that are important for successful data analysts to have are extensive technical knowledge and strong communication skills. Technical knowledge is needed to complete the majority of a data analyst's responsibilities.How can I be the best stand out candidate as a data analyst? ›
As a standout data analyst you will need effective communication skills in order to present the reports you have made, some of the people you present to may not understand the technical jargon, so you should be able to explain your analysis to non-technical people.What is your goal as a data analyst? ›
Your primary goal in a data analyst career is to take large volumes of complex data, extract insights, and help solve problems. Skills you'll need to thrive in a data analytics career are, but not limited to, SQL, Microsoft Excel, critical thinking, and basic programming knowledge.What do data analysts do all day? ›
A data analyst reviews data to identify key insights into a business's customers and ways the data can be used to solve problems. They also communicate this information to company leadership and other stakeholders.What is the first step a data analyst should take? ›
The first step in any data analysis process is to define your objective. In data analytics jargon, this is sometimes called the 'problem statement'. Defining your objective means coming up with a hypothesis and figuring how to test it. Start by asking: What business problem am I trying to solve?What does a data analyst do in a day? ›
Generally speaking, a data analyst will retrieve and gather data, organize it and use it to reach meaningful conclusions. “Data analysts' work varies depending on the type of data that they're working with—for example sales, social media, inventory, etc.Is data analyst difficult to learn? ›
Data analysis is neither a “hard” nor “soft” skill but is instead a process that involves a combination of both. Some of the technical skills that a data analyst must know include programming languages like Python, database tools like Excel, and data visualization tools like Tableau.Can I get a data analyst job without coding? ›
Data analysts are also not required to have advanced coding skills. Instead, they should have experience using analytics software, data visualization software, and data management programs. As with most data careers, data analysts must have high-quality mathematics skills.Is it hard to find a job as a data analyst? ›
In short: Data analysts are in high demand, putting newcomers in a great position. The jobs are there; as long as you've mastered (and can demonstrate) the right skills, there's nothing to stop you getting a foot in the door.
What qualities make you a good candidate? ›
- Leadership. Even in entry-level positions, most employers look for evidence of leadership qualities. ...
- Teamwork. ...
- Communication and Interpersonal Skills. ...
- Analytical Skills. ...
- Dependability and a Strong Work Ethic. ...
- Maturity and a Professional Attitude. ...
- Adaptability and Flexibility. ...
- Good Personality.
“I see this opportunity as a way to contribute to an exciting/forward-thinking/fast-moving company/industry, and I feel I can do so by/with my …” “I feel my skills are particularly well-suited to this position because …” “I believe I have the type of knowledge to succeed in this role and at the company because …”How do you handle stress and pressure? ›
- Decide what you can do. Pinpoint which parts of the situation you have the power to change or influence for the better. ...
- Get support. Find someone to talk to about your situation. ...
- Care for yourself. Take especially good care of yourself when stress in your life is high.
Think about: your enthusiasm for the profession and the employer and your desire to make your mark. your personal qualities, such as your drive and willingness to learn. the skills the employer seeks and how you have demonstrated them in the past – your answer should show why you would be competent in the job.Why should we hire you best answer for freshers? ›
“As a fresher, I bring a lot to the table in terms of skill and ability. I am very flexible and adaptive to learning new things, which means I will be able to contribute something capable to the growth of the company. My last project in Operations taught me how to be a team player.How do you introduce yourself in data analyst Interview? ›
How to Answer - Tell Me About Yourself - for data analysts - YouTubeWhat should a data analyst wear to an interview? ›
On the day of the interview, dress just a bit better than you observed. For example, if the dress is business casual, wear a sport coat and tie. Arrive for the interview early, take a minute or two to check your appearance, then go in with a positive attitude, knowing you are well prepared.How do I ace my data analyst interview? ›
- Showcase your skills. Develop your portfolio to highlight your data analysis skills.
- Answer interview questions with confidence. Practice answering interview questions and completing take-home assessments.
- Navigate the data professions.
Typical qualifications for Data Analyst jobs include a Bachelor's Degree in science, mathematics, or related fields and a postgraduate degree in data analytics or a related field. It is also important to have the knowledge of programming languages such as Python and R.Does data analyst require coding? ›
Do Data Analysts Code? Some Data Analysts do have to code as part of their day-to-day work, but coding skills are not typically required for jobs in data analysis.
Is data analyst hard? ›
Data analysis is neither a “hard” nor “soft” skill but is instead a process that involves a combination of both. Some of the technical skills that a data analyst must know include programming languages like Python, database tools like Excel, and data visualization tools like Tableau.What do data analysts do all day? ›
A data analyst reviews data to identify key insights into a business's customers and ways the data can be used to solve problems. They also communicate this information to company leadership and other stakeholders.How do I prepare for a data analyst interview? ›
Be prepared to discuss technical skills, analytics and visualization, as well as business acumen and soft skills. Study and practice interview questions: Make use of programs such as Datacamp to practice technical skills, or build up your project experience, as well as business and analytics case studies.Which is best tool for data analysis? ›
Microsoft Excel is the most common tool used for manipulating spreadsheets and building analyses. With decades of development behind it, Excel can support almost any standard analytics workflow and is extendable through its native programming language, Visual Basic.DO data analyst work from home? ›
As the data market grows and remote work continues to rise, data analysts will increasingly find opportunities for flexible, location-independent work. While it may prove more difficult for entry-level analysts to find a remote position, it's certainly possible.Do data analysts need a degree? ›
Yes, a bachelor's degree is the minimum requirement for nearly all data analyst positions.Do data analysts use math? ›
As with any scientific career, data analysts require a strong grounding in mathematics to succeed. It may be necessary to review and, if necessary, improve your math skills before learning how to become a data analyst.Can I become data analyst in 3 months? ›
Can I become data analyst in 3 months? Ans: Make the most of your three months and learn everything you can. Because time is limited, the emphasis should be on learning Excel, SQL, R/ Python, Tableau/ PowerBI, and ML if time allows. Investing your time in projects will also give you an advantage when applying for jobs.Is it stressful being a data analyst? ›
Several data professionals have defined data analytics as a stressful career. So, if you are someone planning on taking up data analytics and science as a career, it is high time that you rethink and make an informed decision.Can I be a data analyst if I am not good at math? ›
While data analysts need to be good with numbers, and a foundational knowledge of Math and Statistics can be helpful, much of data analysis is just following a set of logical steps. As such, people can succeed in this domain without much mathematical knowledge.