By Paul Chimodo
Data analysts gather, clean, and study data to help guide business decisions. If you’re considering a career in this in-demand field.
You can find data analytics jobs in all sorts of industries, and there’s more than one path toward securing your first job in this high-demand field. Whether you’re just getting started in the professional world or pivoting to a new career, here are some steps toward becoming a data analyst.
- Get a foundational education.
If you’re new to the world of data analysis, you’ll 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’s degree. While many positions still do require a degree, that’s beginning to change. While you can develop foundational knowledge and enhance your resume with a degree in math, computer science, or another related field, you can also learn what you need through alternative programs, like professional certificate programs, bootcamps, or self-study courses.
2. Build your technical skills.
Getting a job in data analysis typically requires having a set of specific technical skills. Whether you’re learning through a degree program, professional certificate, or on your own, these are some essential skills you’ll likely need to get hired.
To become a data analyst, you’re required to learn multiple technical skills: SQL, Excel, Python, and PowerBi. However, Mariam says you do not have to learn them all at once.
Starting with Excel especially if you don’t have any previous programming experience before moving on to SQL and Python.
In addition to these hard skills, hiring managers also look for workplace skills, like solid communication skills—you may be asked to present your findings to those without as much technical knowledge—problem solving ability, and domain knowledge in the industry you’d like to work.
Skills you’ll build: Data Analysis, Creating case studies, Data Visualization, Data Cleansing, Developing a portfolio, Data Collection, Spreadsheet, Metadata, SQL, Data Ethics, Data Aggregation, Data Calculations, R Markdown, R Programming, Rstudio, Tableau Software, Presentation, Data Integrity, Sample Size Determination, Decision-Making, Problem Solving, Questioning.
- 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.
Dig into climate data from the National Centers for Environmental Information, delve deeper into the news with data from BuzzFeed, or come up with solutions to looming challenges on Earth and beyond with NASA open data. These are just a few examples of the data out there. Pick a topic you’re interested in and find some data to practice on.
- Develop a portfolio of your work
This might sound obvious, but in practice, not all organizations are as data-driven as they could be. According to global management consulting firm McKinsey Global Institute, data-driven companies are better at acquiring new customers, maintaining customer loyalty, and achieving above-average profitability.
As you complete projects for your portfolio, practice presenting your findings. Think about what message you want to convey and what visuals you’ll 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.
