How to Become a Data Analyst in 2023

Data Analyst

Data analytics is a fast-paced industry where data analysts are extremely in demand. Yet, entering a new field can be intimidating, especially in tough times like these. Fortunately, the big data market is still considered as significant as ever. As a matter of fact, it is projected that its market will be worth $229.4 billion by 2025. Simply put, the data market is rapidly increasing, and so is the demand for new data analysts. 

To make yourself stand out and discover great opportunities, you will need some strategies. This article will elaborate on the steps on how to become a data analyst.

What a Data Analyst Does?

A data analyst gathers, processes, and conducts statistical analyses on a big dataset. He or she finds out how data can be used to solve problems and answer questions. Data analysis has progressed with the advancement of computers and an ever-growing shift to technological innovations. The evolution of the relational database also gave data analysis a new dimension as it now allows analysts to use SQL to collect data from databases.

A Step-by-Step Guide to Becoming a Data Analyst

Familiarize yourself with the basics.

Immerse yourself in the data analytics world and familiarize yourself with some of the top tools and contexts. The first component of this step is to take up the theory behind data analytics. Grasp as much theory as you can about it. Learn how it is being applied in real-life situations, and be familiar with the types of analyses that an analyst may conduct.

However, remember that the goal is not to learn about everything just by yourself.  Once you have acquired personal insights about data analysis, you are prepared to move on to the next steps.

It is time to get serious.

If you want to take data analysis as a career, the most effective and rewarding way is to enroll in a bachelor’s degree or specialized program. Now, your next question may be “How long does it take to become a data analyst?” A college degree usually takes around three to four years.

You will not run out courses and bootcamps to choose from. But not all data analytics are made the same. Invest in one that offers mentorship, a practical curriculum, career training, and a job guarantee.

Keep up with new and leading data analytics tools.

Know the latest tools related to data analysis, which include:

  • Spreadsheets and querying languages relied on by data analysts, like SQL and XML
  • Programming frameworks and languages, such as Python, Hadoop, and R 
  • Visualization tools, such as Power BI, Tableau; Bokeh, Plotly, and Matplotlib

You should also have experience in one or more top data analysis solutions, such as Adobe Analytics and Google Adwords & Analytics.

In addition, you may want to put together practice works that deal with the various stages of data analysis: researching businesses and opportunities, setting the standards of the data you must gather, collecting and cleaning such data, then shaping and studying it using tailor-built algorithms. Lastly, transform these insights into stunning visualizations.

Try touching on a number of practice projects to master and show your skills in working with several data types, mining structured data, texts, images, audio, or video to conduct statistical analysis, identity causality, and perform predictions.

Improve your soft skills.

Some soft skills required to become a data analyst are:

  • Good at research
  • Good at numbers
  • An analytical mindset
  • Excellent communication, collaboration, and presentation skills
  • A problem-solver
  • Attention to details
  • Excellent organization skills and can meet deadlines
  • Business acumen
  • Knowledge of logical and methodical approaches 

If you are already good with some of these skills, identify what skills may still need some work from you. If your current workplace offers a kind of development in these areas, grab it. You can also look for opportunities elsewhere. For instance, carry out informal meetups. 

During job applications, list as many essential skills on your CV as possible. Eventually, the right skills will land you your dream job.

Make visualizations and practice demonstrating them.

Practice making your own visualizations and look for the perfect way to allow the data to speak for itself. Microsoft Excel comes into the picture even at this early stage, and it remains to be useful after more than three decades and is inevitable in the data science field.

Data analysts should also be able to use visualizations to explain outcomes. If such communication skills do not come innately to you, start practicing now. If needed, start small by presenting to a friend, then colleagues, and so on.

Build a network.

Build a network.

Build a network, both online and in-person, and make connections. Networking does not have to be as awkward as it may seem. A friendly LinkedIn message may readily do it for you.

Connect with like-minded individuals ahead of time. A good network paves the way for potential opportunities and career prospects. It is also a wonderful source of support and mentorship. Furthermore, surrounding yourself with individuals you can share experiences with and learn from is important. A good connection may even lead you to a job opportunity.

Start with your student community. You can also try where tech and data meetups across the world take place. Join data analytics groups or connect with analysts on LinkedIn, too.

Prepare your portfolio and yourself for the job market.

Arguably, your portfolio is the most vital asset that you have with regard to job applications as it exhibits your expertise and skills to employers. It can also show that you really know how to apply them in real life. 

The creation of a polished portfolio is rooted in taking the right data analytics program. Another factor is being coached by a competent mentor.

Establish your online presence.

Ensure that you have an optimized online presence. Update your LinkedIn account to display all your skills and tools that you are adept with. Also, include a summary of the type of role you are searching for. 

Apply to data analyst jobs.

There is a vast selection of data analyst jobs you can apply for. Some of these include researcher, database administrator, data and analytics manager, digital marketing manager, statistician, transportation logistics, business analyst, systems analyst, and health care analyst, among others. McKinsey & Co. says that demand for these roles may outpace the estimated data professionals supply by 50% or 60%, meaning that it will be harder to fill these jobs. Nevertheless, the data analyst salary starts at $65,236, according to Indeed.

Once you begin applying for jobs, get ready to be interviewed. Every company has its own interviewing methodologies, but you should know how to answer some commonly asked questions. 

Is data analysis the right career path for you?

All businesses depend on data to come up with informed decisions. A restaurant might review sales from various timelines of the year to determine operation hours during the holidays. A software provider might probe labor expenses and compare them with revenues to settle on staffing for the next year.

No matter the type of industry, data analysis is a critical factor of strategic planning. If you are into data, information, clues, or evidence, when solving problems and making decisions and predictions, data analysis may be the right career for you. Have this list of best data analytics software for 2022 handy should you decide to take this path.

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