Entry-Level Data Analyst: What They Do + How to Get Started

Written by Coursera • Updated on

Data analysts glean insights from data to help businesses make better decisions. Learn what you can expect from an entry-level data analyst position and how to get started today.

[Featured Image]: A woman wearing an orange dress, is sitting in front of two computer screens as works as an entry-level data analyst.

As data becomes increasingly important to the daily operations and decision-making processes in business settings, so too has the role that data analysts play in the professional world. In fact, the World Economic Forum’s The Future of Jobs Report 2020 ranked data analysts and scientists as the positions with the most increased demand, indicating their value to employers across multiple industries [1]. 

The data is clear: it’s a good time to start out as a data analyst. Below, you will learn more about what you can expect from an entry-level data analyst position and how to get started. 

Entry-level data analyst: responsibilities and skills

Entry-level data analysts perform many of the same tasks as those with prior experience, whom they support through their work. An entry-level data analyst might do many of the same tasks as a senior-level analyst but the complexity and weight of their responsibilities will be much less. 

Here’s what you can expect from an entry-level data analyst position: 


As an entry-level data analyst, you can expect to perform many of the same tasks as more experienced analysts, except with lowered responsibility. These tasks include: 

  • Data collection: Data analysts must often collect data themselves. This can be, done through surveys or by buying the appropriate data collection.

  • Data cleaning: Once data is collected, it must be cleaned to ensure there are no errors or duplicates that might skew the results.

  • Data modeling: Data analysts must structure their data sets after they have collected and cleaned them.

  • Data analysis: The central function of a data analyst’s position – whether just starting out or an experienced professional – is to interpret data to find trends or patterns. Through this interpretation process, data analysts can produce actionable insights to help organizations achieve their goals.

  • Data visualization: Data analysts must be skilled at turning their insights into visualizations that make abstract findings real for stakeholders.


If you’re interested in landing a job as an entry-level data analyst, you’ll need to demonstrate mastery over several important technical and interpersonal skills. Some of the most common skills include: 

  • Programming languages, such as Python or R 

  • Database tools, including Microsoft Excel and SQL

  • Data visualization tools like Tableau, Jupyter Notebook, and Excel

  • Knowledge of mathematics and statistics

  • Communication and storytelling skills to ensure that insights are effectively conveyed to stakeholders

  • Strong collaboration and teamwork abilities are particularly important because entry-level data analysts often must support more senior members 

Read more: What Does a Data Analyst Do? Career Guide

Data Analytics in Everyday Life

Data analyst job outlook 

The job outlook for data analysts is extremely positive. 

According to the US Bureau of Labor Statistics (BLS), the number of employment opportunities for operations research analysts (the job category under which data analyst falls) is projected to grow by 23 percent between 2021 and 2031. As a result, the BLS projects that 10,300 new job openings are expected to open every year on average during that period [2].  

Data analyst salary 

The high demand for data analysts means they can also command a higher-than-average salary. 

According to Glassdoor, entry-level data analysts earned a median salary of $55,089 as of May 2022 [3]. As data analysts gain more experience, however, they can expect to earn even more. As of May 2022, Glassdoor estimated that the median salary for data analysts was $71,622 [4], while the median salary for Senior Data Analysts was $102,825 [5]. 

How to land an entry-level data analyst job

There’s no one way to start a career. However, the steps below are a common pathway that can lead to a successful career in data analytics.

1. Get a credential. 

According to the BLS, the typical entry-level degree for data analysts is a bachelor’s degree, but some employers might prefer candidates with a master’s degree. These degrees should be in a related field, such as mathematics, computer science, engineering, or business [6]. 

It is possible to get an entry-level data analyst position without a college degree. Individuals lacking the resources to pursue a bachelor’s degree or those with a bachelor’s degree in a field unrelated to data analysis might consider obtaining a professional certificate, such as IBM’s Data Analyst Professional certificate, to demonstrate their job preparedness to potential employers.  


professional certificate

IBM Data Analyst

Unlock your potential in data analytics. Build job-ready skills for an in-demand career as a data analyst. No degree or prior experience required.


(12,301 ratings)

116,319 already enrolled


Average time: 4 month(s)

Learn at your own pace

Skills you'll build:

Microsoft Excel, Python Programming, Data Analysis, Data Visualization (DataViz), SQL, Data Science, Spreadsheet, Pivot Table, IBM Cognos Analytics, Dashboard, Pandas, Numpy, Jupyter notebooks, Cloud Databases, Relational Database Management System (RDBMS), Predictive Modelling, Model Selection, Dashboards and Charts, dash, Matplotlib, SQL and RDBMS

2. Hone your skills.

Your combined technical and personal skills will be the cornerstone of your data analytics job. You should keep up to date and well trained in the skills you will use in your entry-level position, such as programming, data visualization, or database management. 

3. Build a portfolio.

A portfolio gives you the opportunity to showcase your skill set and accomplishments to employers, particularly when you lack prior work experience. Your projects should demonstrate your ability to gather, clean, model, analyze, and present data with insightful visuals. 

To make your projects easily viewable by potential employers, consider uploading them to Github or a similar software development platform. 

Read more: How to Build a Data Analyst Portfolio: Tips for Success

4. Gain experience.

Perhaps the best way to demonstrate your preparedness for an entry-level position is to gain prior experience through either an internship or volunteer opportunity. Such opportunities give you the chance to gain relevant work and industry experience in a fixed amount of time. They also help you network with practicing professionals who can provide key career tips, insights, and opportunities. 

5. Apply.

To land any job, you need to apply for it first. Before applying, though, make sure you have compiled all your application materials, including your resume, cover letter, and portfolio. Consider using resume keywords in your application to help get it to the recruiter’s eyes. 

You can find entry-level data analyst positions online by searching for them on popular job posting sites, such as LinkedIn, Indeed, and Zip Recruiter. 

Read more:15 Data Analyst Interview Questions and Answers

Start your career with Coursera

Whether you’re brand new to the field or already have some training, you might consider taking an online course to prepare you for your first data analyst role. Google’s Data Analytics Professional Certificate equips course takers with in-demand skills such as data cleaning, analysis, and visualization that will have them job-ready in less than six months. 


professional certificate

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.


(105,503 ratings)

1,491,582 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

Article sources


World Economic Forum. “The Future of Jobs Report 2020, https://www3.weforum.org/docs/WEF_Future_of_Jobs_2020.pdf.” Accessed November 10, 2022.

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.

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