The Ultimate Guide to Becoming a Data Analyst 

Kyrie Mattos

 March 23, 2023

Ready for a career change? Maybe you don’t like your current job and heard about the growing need for data analysts. If so, you’ve come to the right place.

Data analysts are in high demand. According to data from the U.S. Bureau of Labor Statistics (BLS), data analyst jobs will grow by 20% from 2018 to 2028, which is much faster than the average job growth of 5%. Data analysts are needed across many industries, including finance, healthcare, education, government, business, and more.

What’s more, data analysts in the U.S. make an average of $70,033 per year.

So if you want to become a data analyst, here’s what you need to do:

1. Learn the basics of data analytics

The first step to becoming a data analyst is getting a broad overview of the field. What is data analytics, and what do data analysts do? In short, they collect, clean, organize, analyze, and interpret data to help companies make better business decisions.

As a data analyst, you’ll need to have a solid foundation in math and statistics. For example, you’ll want to review basic statistical principles, such as measures of center and spread, probability distributions, and hypothesis testing.

Data analysts also need to be naturally curious and good problem solvers. Much of the job involves working with raw data and detecting patterns from which you can draw insights. On top of having an exploratory mindset, you should also be a good communicator so that you can share your findings in a clear and clean way.

Lastly, the field of data analytics is always evolving with new tools and techniques. As a result, data analysts are always learning. So develop a learning mindset, too.

2. Build your technical skills

Next, you need to start working on your technical skills. Different data analyst jobs may require slightly different skill sets, but you’ll always need to know how to:

  • Use SQL (Structure Query Language) so you can query and manipulate databases.
  • Program in R or Python programming languages
  • Use data visualization software (e.g., Tableau or Jupyter Notebook)
  • Clean and prepare data with Microsoft Excel or Google Sheets

Some data analyst jobs may also require you to learn industry-specific software. For example, construction or utility companies may require you to understand and use Enterprise Asset Management (EAM) software.

To get a better sense of what other technical skills employers are looking for, browse through entry-level data analyst job listings of companies you would like to work for.

3. Get certified in data analysis

In the past, having a college degree in data science or a related field like math, statistics, or economics was a prerequisite to many data analyst jobs. However, this is increasingly no longer the case.

In the modern job market, many employers will also accept professional certifications or no qualifications at all if you can prove your skills.

For example, these days, there are many data analytics certification programs that you can complete online for a fraction of the cost of a college degree. Some popular ones include Google’s Data Analytics Certificate and IBM Data Analyst Professional Certificate.

That said, some certifications are more recognized than others, and none guarantee you a job. The biggest value of data analytics certification programs is the skills you’ll learn in them (those listed in the previous step).

If you prefer to learn on your own, you can do that too. There are plenty of free learning resources available online. It just means that you’ll need to work extra hard to prove your talent to employers.

4. Practice your data analyst skills

Once you’ve learned the essential data analyst skills, it’s time to practice them. This means working on a project with real data. It could be a capstone project as part of a course or a personal project on an issue that interests you. The point is to work on a real-life problem.

Use a real dataset. You can find many datasets for free on sites like Kaggle, FiveThirtyEight, and Google Dataset Search.

Once your project is complete, practice presenting your findings. You can present to a friend or family member and ask for feedback or record yourself and rewatch the video to find areas where you can improve.

Honing your communication skills is important because, as a data analyst, you’ll be expected to present your findings and insights to key decision-makers and other stakeholders in the company.

5. Develop a portfolio of your work

At this point, you’re ready to create a work portfolio. This is where you publish some of the projects you’ve completed. It’s an opportunity to show off your best work and demonstrate your data analytics skills to hiring managers.

To stand out, include projects that are unique and align with your personal interests. Also, try to include a group project in your portfolio to show you know how to work with a team. You can use a platform like GitHub or Kaggle to host your data analyst portfolio.

6. Apply for entry-level data analyst jobs

The last step is to apply for entry-level data analyst jobs. You may need to update your CV or resume first. Try to tailor it to the specific jobs you’re applying for.

When applying for jobs, don’t worry too much if you aren’t 100% qualified. Few candidates are. Just put your best foot forward and try to show why you would make a good fit for the position.

Practice doing job interviews with a friend or family member. If you don’t get the first few jobs you apply for, don’t give up. Rejection is normal. Stay persistent, and eventually, you can land a job that’s right for you.

Final advice

At the end of the day, becoming a data analyst can be challenging. But by following the roadmap outlined above, you’re much more likely to be successful. Stick to the plan, and you could be a data analyst within months!

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