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

As data becomes increasingly important to daily operations and decision-making processes in business settings, so does data analysts' role in the professional world. The World Economic Forum’s The Future of Jobs Report 2023 ranked data analysts and scientists as the positions with the sixth most increased demand, indicating their value to employers across multiple industries [1]. 

The data is clear: it’s a good time to start as a data analyst. Discover 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 their responsibilities will be much less complex and weighted. 

You can typically expect the following from an entry-level data analyst position: 

Responsibilities

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 often collect data themselves. You can do this through surveys or by buying the appropriate data collection equipment.

• Data cleaning: Once you collect the data, you must clean it to ensure you find no errors or duplicates that might skew the results.

• Data modelling: 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 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 organisations achieve their goals.

• Data visualisation: Data analysts must be skilled at turning their insights into visualisations that make abstract findings tangible for stakeholders.

Skills 

Landing an entry-level data analyst job requires 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 visualisation tools like Tableau, Jupyter Notebook, and Excel.

• Knowledge of mathematics and statistics.

• Communication and storytelling skills to ensure you effectively convey insights to stakeholders.

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

Data analyst job outlook 

The job outlook for data analysts is extremely positive. As the World Economic Forum Future of Jobs Report shows, data analysts are in high demand, with data analysts and scientists being sixth in the increasing jobs list [1]. The demand for data analysts spans job sectors, with roles available in manufacturing, pharmaceuticals, finance, consulting, and government departments.

Data analyst salary 

The high demand for data analysts means they can command a higher-than-average salary. As of July 2024, Glassdoor estimated that the median salary for data analysts was £32,618. The starting salary at the entry-level is £24,00, rising to £45,000 with experience [2]. The median salary for a senior data analyst is considerably higher at  £50,430 [3]. 

How to land an entry-level data analyst job

The following steps are a common pathway that can lead to a successful career in data analytics.

1. Get a credential. 

If you can demonstrate relevant skills for the job, you may be able to secure a job as an entry-level data analyst with any degree subject. However, a degree in a related field, such as mathematics, computer science, information management, statistics, or business, will typically be helpful. Postgraduate degrees in data science are an option but not required. 

If you have a degree in a field unrelated to data analysis, consider obtaining a Professional Certificate, such as IBM’s Data Analyst Professional Certificate, to demonstrate your job preparedness to potential employers.  

2. Hone your skills.

Your combined technical and personal skills will be the cornerstone of your data analytics job. Keep up to date and train in the skills you will use in your entry-level position, such as programming, data visualisation, or database management. 

3. Build a portfolio.

A portfolio allows you 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, analyse, and present data with insightful visuals. 

Consider uploading your projects to Github or a similar software development platform so potential employers can easily view them. 

4. Gain experience.

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

5. Apply.

You can find entry-level data analyst positions to apply to online by searching for them on popular job posting sites like LinkedIn, Indeed, and Glassdoor. Ensure you have compiled all your application materials, including your CV, cover letter, and portfolio. Consider using CV keywords in your application to help get it to the recruiter’s eyes. 

Prepare for an entry-level data analyst career with Coursera

Data analyst positions are in demand with promising salary prospects. Starting as an entry-level data analyst and building your skills and experience is a good way to begin this career.

Whether you’re 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 learners with in-demand skills such as data cleaning, analysis, and visualisation that will have them job-ready in less than six months.