When you’re applying for your first job in tech, it can be intimidating and even discouraging to read the years of required work experience that are listed in job descriptions. After all, the only way to get work experience is by, well, working. Fortunately there are lots of entry-level tech jobs you can get with no experience, even within in-demand fields like data analytics.
Data Analysts are one of the most in-demand positions in tech; in fact, the Bureau of Labor Statistics forecasts that Data Scientist and Statistician will be some of the fastest-growing occupations over the next decade. As companies embrace digital technologies, they create more and more data that can be used to leverage business decisions. Organizations need Data Analysts who understand how to put data to work.
Wondering where you should start? With Codecademy’s beginner-friendly Data Science career paths, you can focus on learning the skills you need to get a job. The newest career path, Business Intelligence Data Analyst, is designed for absolute beginners and is the quickest, lowest-code way to get a job in tech. By the end of the path, you’ll be proficient in all of the technical tools that a BI Data Analyst uses, and be ready to apply for an entry-level position.
Read on to learn more about the roles that will help you break into data science, plus the technical skills you need to get hired and start gaining valuable work experience.
1. Business Intelligence Data Analyst
One of the quickest ways to launch a career in data is by becoming a Business Intelligence (BI) Data Analyst, which is a data professional who turns data into insights for an organization. A BI Data Analyst needs to know some programming with Python and SQL, plus be proficient in tools like Microsoft Excel and Tableau. They use these technologies to analyze data, write reports, and build dashboards that communicate their findings.
If you think this is the career for you, consider starting the BI Data Analyst Career Path today. We’ll walk you through everything you need to know — from basic statistics to SQL — to master data analysis. You’ll get hands-on practice cleaning, manipulating, and visualizing data with Python Pandas and MatPlotLib, and we’ll help you create a BI Data Analyst portfolio that you can use in job interviews. This path is beginner-friendly and you don’t have to be good at math or a “numbers person” to understand these skills.
2. Quality Assurance Data Analyst
You might’ve heard the saying, “garbage in, garbage out” before in data science. Basically, it means that data analysis is only as good as the data being used, and even the most advanced data algorithms are useless without quality data. A Quality Assurance (QA) Data Analyst is responsible for monitoring the quality of data that an organization uses. For example, they would be cleaning up messy data so it’s accurate and complete and validating data, which means checking that data actually measures what we think it is measuring.
You’ll learn all about how to clean and validate data and why it’s so important in the BI Data Analyst Career Path. If you want to take a closer look at the data-cleaning methods that Data Analysts use, you could also check out our courses How To Clean Data With Python and Handling Missing Data.
3. Data Steward
A Data Steward (sometimes called a Data Custodian) is another role that’s concerned with data quality and data governance, which Google Cloud defines as all of the steps that an organization takes to “ensure data is secure, private, accurate, available, and usable.”
Data Stewards ensure that members of an organization follow internal standards and processes for data collection, management, and analysis. In the new BI Data Analyst Career Path, you’ll learn all about the ethical considerations of data collection and how to apply the principles to your work.
4. Consumer Insights Analyst
Lots of companies turn to data analysis to better understand their consumers and clients. A Consumer Insights Analyst gathers data about consumer behaviors through a variety of research methods, and analyzes it to find potential shortcomings or opportunities for businesses to improve their relationship with consumers.
Consumer Insights Analysts typically use programming languages like SQL to query and join data, and may use BI tools like Tableau to create reports and dashboards. (BTW, we have a free course Learn Tableau for Data Visualization that will teach you the basics of data setup in Tableau.) Being able to tell a clear story with complicated data is key, because a Consumer Insights Analyst works closely with non-technical teams (like marketing) to develop strategies based on trends in data.
5. Junior Data Analyst
Taking an entry-level junior position is one way to gain on-the-job experience that you’ll need in order to get in the door. For example, a Junior Data Analyst typically works closely assisting Data Analysts and gets an inside look into how data influences business decisions. To learn more about how to make the leap from an apprentice, intern, or other junior position to a full-time employee, check out this blog post of tips from people who’ve done it.
These are just some of the exciting jobs you can get when you’re starting out as a data professional. Be sure to check out the rest of Codecademy’s career paths and courses in data science — they’re all self-guided, so you can stop and start whenever you need and work at the pace that’s right for you. And when it comes time to start submitting job applications, we have tons of resources, portfolio projects, and interview tips that will help you feel confident landing that position.