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Data analysts gather, clean, and study data to help guide business decisions. If you enjoy working with data, solving problems, and identifying insights, this in-demand career might be right for you. At a glance, here's what you need to know about data analysts:

• Data workers are in demand. According to the US Bureau of Labor Statistics (BLS), the number of job openings for data professionals is projected to grow by 34 percent between 2024 and 2034 [].

• Data analysts possess skills in data analytics, statistics, programming, and data visualization, among other things.

• While most data analysts possess a bachelor's degree, some employers may be willing to hire entry-level data analysts without one, so long as they have relevant skills.

In this article, we'll go over the different ways you can become a data analyst鈥攚ith or without a degree. Afterward, if you want to get started building job-ready skills, consider enrolling in the IBM Data Analyst Professional Certificate. Over 11 courses, you'll develop a working knowledge of the Python language as well as how to visualize data and present your findings. All you need is basic computer literacy, high school math, and comfort with numbers.

How do I become a data analyst? A step-by-step guide

You can find data analytics jobs in all sorts of industries, and there鈥檚 more than one path toward securing your first job in this high-demand field. Whether you鈥檙e just getting started in the professional world or pivoting to a new career, here are some steps toward becoming a data analyst.

Learn more: What Does a Data Analyst Do? A Career Guide

1. Get a foundational education.

If you鈥檙e new to the world of data analysis, you鈥檒l want to start by developing some foundational knowledge in the field. Getting a broad overview of data analytics can help you decide whether this career is a good fit while equipping you with job-ready skills.

It used to be that most entry-level data analyst positions required a bachelor鈥檚 degree. While many positions still do require a degree, that鈥檚 beginning to change. You can develop foundational knowledge and enhance your resume with a degree in math, computer science, or another related field鈥�or you can also learn what you need through alternative programs, like professional certificates, bootcamps, or self-study courses.

Learn more: What Degree Do I Need to Become a Data Analyst?

2. Build your technical skills.

Getting a job in data analysis typically requires having a set of specific technical skills. Whether you鈥檙e learning through a degree program, professional certificate, or on your own, these are some essential skills you鈥檒l likely need to get hired.

• Statistics

• R or Python programming

• SQL (Structured Query Language)

• Data visualization

• Data cleaning and preparation

Take a look at some job listings for roles you鈥檇 like to apply for, and focus your learning on the specific programming languages or visualization tools listed as requirements.

In addition to these hard skills, hiring managers also look for workplace skills, like solid communication skills鈥攜ou may be asked to present your findings to those without as much technical knowledge鈥攑roblem-solving ability, and domain knowledge in the industry you鈥檇 like to work.

Learn how to perform data analysis, including data preparation, statistical analysis, and predictive modeling, using R, R Studio, and Jupyter with the IBM Data Analytics with Excel and R Professional Certificate.

3. Work on projects with real data.

The best way to learn how to find value in data is to work with it in real-world settings. Look for degree programs or courses that include hands-on projects using real data sets. You can also find a variety of free public data sets you can use to design your own projects.听

Dig into climate data from the , delve deeper into the news with data from , or come up with solutions to looming challenges on Earth and beyond with open data. These are just a few examples of the data out there. Pick a topic you鈥檙e interested in and find some data to practice on.

If you鈥檙e looking to build job-ready data analyst skills without committing to a degree, consider the Google Data Analytics Professional Certificate through 糖心vlog官网观看. You'll learn how to clean and organize data with SQL and R, visualize with Tableau, and complete a case study for your portfolio.

When you complete the program, you'll get access to hiring resources through Google鈥檚 Employer Consortium.

4. Develop a portfolio of your work.

As you play around with data sets on the internet or complete hands-on assignments in your classes, be sure to save your best work for your portfolio. A portfolio demonstrates your skills to hiring managers. A strong portfolio can go a long way toward getting the job.听聽

As you start to curate work for your portfolio, choose projects that demonstrate your ability to:

• Scrape data from different sources

• Clean and normalize raw data

• Visualize your findings through graphs, charts, maps, and other visualizations

• Draw actionable insights from data

If you鈥檝e worked on any group projects through the course of your learning, consider including one of those as well. This shows that you鈥檙e able to work as part of a team.

If you鈥檙e not sure what to include in your portfolio (or need some inspiration for project ideas), spend some time browsing through other people鈥檚 portfolios to see what they鈥檝e chosen to include.

Tip: Sign up for a account and start posting your projects and code to the site. It鈥檚 an excellent spot to network with a community of data analysts, show off your work, and possibly catch the eye of recruiters.

5. Practice presenting your findings.

It can be easy to focus only on the technical aspects of data analysis, but don鈥檛 neglect your communication skills. A significant element of working as a data analyst is presenting your findings to decision makers and other stakeholders in the company. When you鈥檙e able to tell a story with the data, you can help your organization make data-driven decisions.听

As you complete projects for your portfolio, practice presenting your findings. Think about what message you want to convey and what visuals you鈥檒l use to support your message. Practice speaking slowly and making eye contact. Practice in front of the mirror or your classmates. Try recording yourself as you present so you can watch it back and look for areas to improve.

6. Get an entry-level data analyst job.

After gaining some experience working with data and presenting your findings, it鈥檚 time to polish your resume and begin applying for entry-level data analyst jobs. Don鈥檛 be afraid to apply for positions that feel like a stretch. Your skills, portfolio, and enthusiasm for a role can often matter more than if you check every bullet item in the qualifications list.

If you鈥檙e still in school, ask your university鈥檚 career services office about any internship opportunities. With an internship, you can start gaining real-world experience for your resume and apply what you鈥檙e learning on the job.

7. Consider certification or an advanced degree.

As you move through your career as a data analyst, consider how you鈥檇 like to advance and what other qualifications can help you get there. Certifications, like the Certified Analytics Professional or Cloudera Certified Associate Data Analyst, may help qualify you for more advanced positions at higher pay grades.听聽

If you鈥檙e considering advancing into a role as a data scientist, you may need to earn a master鈥檚 degree in data science or a related field. Advanced degrees are not always required, but having one can open up more opportunities.

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