Entry-Level Data Analyst Careers: What to Expect and How to Start

Data analysts examine data to find useful and valuable information that helps businesses make better decisions. Find out what to expect in an entry-level data analyst job and how you can begin your journey in this field today.  

Are you thinking of starting a career as an entry-level data analyst, but are confused about where to start? Then you are in the right place. In this post, we are going to discuss all about this - like entry-level data analyst salary for a fresher, how to become a data analyst with no experience, and how much demand will be there for this role in the future. 

Well, when we talk about the demand for this position, you don’t need to worry about it because the demand for talented data analysts is booming like crazy. In fact, the World Economic Forum declared that job opportunities for data analysts and data scientists are expected to grow at a rate of 40% by 2030. 

This makes it a great time to begin your journey in data analysis. So, without delay, let’s explore what an entry-level data analyst does, what key skills they require and what the salary expectations and lastly, how you can start.

What is an Entry-Level Data Analyst?

A person who is just starting their career in data is known as an entry-level data analyst. These experts work with raw data, clean it up, and organize it. With this practice, they find valuable insights from their work to help the company solve issues and make informed decisions. 

Responsibilities Include:

• Collecting and cleaning data
  
  
• Using tools like Excel, SQL, or Python to analyze datasets
  
  
• Creating reports and dashboards using tools like Tableau or Power BI
  
  
• Presenting findings in a clear and actionable way

At this beginning level, you are not expected to be an expert at everything, but you should be ready to learn things quickly and be comfortable working with numbers and logic. 

Entry-Level Data Analyst Jobs: What to Expect

Entry-level data analyst jobs are found in almost every industry—finance, healthcare, e-commerce, tech, and more. Common job titles include:

• Junior Data Analyst
  
  
• Business Data Analyst
  
  
• Reporting Analyst
  
  
• Data Associate
  

What employers expect:

• A basic understanding of analytics tools and data concepts
  
  
• Problem-solving ability
  
  
• Good communication skills
  
  
• Curiosity and willingness to learn

Sometimes, this could happen that you may be assigned roles that are part of a larger data intelligence team. Which means you will get lots of work to enhance your capabilities and opportunities to grow further. 

Entry-Level Data Analyst Salary

Here's a table summarizing the Entry-Level Data Analyst Salary section:

Salary Variations Based On:

• Location
  
  
• Industry
  
  
• Skills (e.g., Python, SQL)
  
  
• Certifications/Degrees

Note: As you gain more experience and develop specialized skills (like becoming a Data Scientist or BI Analyst), salaries can rise significantly.

How to Become a Data Analyst with No Experience

Get a Degree, Certification, or Credential

To start your career in the data analyst field, you have to start by earning a degree or a certification. According to the Bureau of Labor Statistics (BLS), the majority of entry-level data analyst positions require at least a bachelor’s degree.  Aspiring candidates especially pursue the following fields of study:

• Computer Science
  
  
• Business
  
  
• Mathematics
  
  
• Statistics

While a bachelor’s degree is considered enough to get started but in today’s time, employers give more priority to skills rather than a degree. 

So, you don’t need to worry if you don’t have a college degree! There are other ways to get into the field and be successful in it: 

• Data Analyst Boot Camps: These are the programs that teach you the practical skills to get an entry-level job as a data analyst in just a few months.
  
• Career Transitions: Even if you are changing your career, you can still apply for the role of data analyst by using the skills that you have used in your previous role.
• Professional Certifications: A great substitute for a degree is a certification. Meta Data Analyst Professional Certification is one of them. This is a self-paced program and generally gets completed within five months. But never underestimate this program due to its duration, because it equips you with the hands-on practical skills. 

Eventually, skills matter. So, no matter where you are gaining the knowledge, whether from a traditional degree or through a certification. Options are many, but the choice is yours; choose whichever suits you best. 

Hone Your Skills and Master Essential Tools

As an entry-level data analyst, both your technical abilities and soft skills will form the foundation of your success. It's important to stay well-trained in key areas such as programming, data visualization, database management, as well as communication, collaboration, and critical thinking. These skills will allow you to not only analyze data but also effectively convey insights to your team.

To ensure your success as an entry-level data analyst, you must be excellent in both technical and soft skills. It’s important to maintain your proficiency in critical thinking, teamwork, communication, programming, data visualization, and database administration. These abilities will help you build effective communication with your team, and hence, you will be able to drive valuable insights for a better strategy. 

In addition to these core skills, you’ll need to get comfortable with a few essential tools. While you don't need to master everything right away, it’s crucial to familiarize yourself with:

• Excel – For handling spreadsheets and conducting basic analysis.
  
  
• SQL – To query and manage data in databases.
  
  
• Python or R – For more advanced data analysis and statistical computing.
  
  
• Tableau or Power BI – For creating impactful visualizations that tell a story with your data.

Create an Impressive Portfolio

Many of us often overlook portfolios and rely only on CVs. However, they play a key role in securing a job quickly as they not only showcase our experience, unlike our CVs, but also represent our work more clearly and effectively. A strong portfolio showcases real skills through small projects (e.g., Kaggle datasets), turning insights into dashboards or presentations. An impressive portfolio also shows your ability to gather, organize, analyze, and present data. Upload projects to GitHub for easy employer access. 

How to Build a Strong Portfolio:

• Create small projects (e.g., Kaggle datasets)
  
  
• Analyze data, turning insights into visual dashboards or presentations
  
  
• Showcase all stages: data collection, cleaning, analysis, and presentation
  
  
• Upload projects to GitHub for easy employer access

Apply for a Job

To apply for a data analyst position, make sure you have compiled all your application materials—including your resume, cover letter, and portfolio—and use resume keywords to help recruiters read your application. 

You can find data analyst entry-level jobs online by searching for them on popular job posting sites like LinkedIn, Indeed, and ZipRecruiter.

How to Get a Data Analyst Job as a Fresher

Getting your first job might make you feel a bit awkward and daunted, but in reality, it's absolutely achievable. Yes, you may face rejections in the starting phase, but with patience and the right strategy, you can do it!

Here’s a strategy that works:

• Modify your resume

Mention your academic projects, internship work, or related work on which you have spent time. Also include work that you did for yourself, like personal projects. 

• Build an online presence

Make a GitHub profile, publish your blog posts about your projects, and demonstrate your dashboards on Tableau Public. 

• Use fresher-friendly platforms

Search for entry-level positions as a data analyst on platforms such as LinkedIn, Naukri, Indeed, or specialized job boards. 

• Prepare for interviews

Practice case-study-style problems, SQL queries, and basic Python logic. For an interview, confidence is also necessary to explain your thoughts clearly to the interviewer. 

• Network wisely

Networking with people is very important, so make connections with data experts wisely on LinkedIn. For faster network building, take part in virtual meetings, webinars, and gain knowledge and recognition. 

Discover How to Become a Data Analyst with DizitaAdda

At DizitalAdda, you can learn essential skills at both the foundation and expert levels. They provide a Data Analyst course for both extreme beginners and an advanced course who have some prior knowledge and experience in it. Their Data Analyst Professional Certificate is ideal for freshers, which will help you build a strong foundation in a few months by covering important tools such as Excel, SQL, and Python. The Advanced Data Science Certificate offers a deep insight into data modeling, machine learning, and predictive analytics.