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SmartData Collective > Big Data > Data Science > Top 5 Reasons You Should Become a Data Analyst
Data Science

Top 5 Reasons You Should Become a Data Analyst

Big data technology is driving some major changes, which creates new opportunities for data scientists.

Andrey Koptelov
Last updated: 2022/11/15 at 12:14 AM
Andrey Koptelov
6 Min Read
reasons to become a data analyst
Shutterstock Photo License - Andrey_Popov
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Data has unquestionably had a huge impact on our lives. It is becoming more prolific as well, as 2.5 quintillion bytes of data are generated every day.

Contents
1.     In Demand Profession2.     Advance as a Leader3.     Work in a Variety of Industries4.     Boost Problem-Solving Skills5.     Good SalaryConclusion

Data is everything in today’s tech-driven world. Every company collects data, analyzes it, and makes its marketing and sales strategies based on the data’s results to attract more customers and increase sales and profits.

Here comes the role of the data analyst. They are highly-skilled individuals that gather and analyze the data to cater to various problems and provide solutions faced by different organizations or even individuals.

Data analysts work in many industries and can support companies with focuses ranging from retail to healthcare to IT companies etc.

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If you are considering a data analyst career, here are some reasons that may help solidify your decision. So, without further delay, let us get straight to the topic.

1.     In Demand Profession

Unsurprisingly, those pursuing careers in data analysis are highly sought after. Companies need professionals with the skills and knowledge to analyze data effectively, helping them make strategies to increase leads, sales, revenue, and overall profits.

You can land a job just after completing your degree or even if you are in your final years; this also shows this career’s demand. Not only is this career in demand, but growing.

As a data analyst, you will learn several technical skills that data analysts need to be successful, including:

  • Programming skills
  • Machine learning knowledge
  • Data visualization capability
  • Data Mining skills
  • Data wrangling ability

Many professionals pursue careers in data analysis by obtaining data science online masters or on-site, depending upon their preference.

You can also choose the mode of education as per need; if you are working in the industry and want the degree to climb the professional, then opt for online mode, or if you are just continuing your studies after your bachelor’s and love learning on-site, you can choose the on-campus option. 

2.     Advance as a Leader

In addition to having the technical skills needed to succeed as a data analyst, those in this profession also need strong people and leadership skills.

As a data analyst, you will directly manage your organization’s data, its data managing team, if you are a team lead, and data strategy. It means that you need to be able to collaborate effectively with others, as well as communicate data insights and findings.

Data analysts usually have comprehensive and always-changing skill sets. As a result, they become more confident by juggling multiple tasks and priorities while improving crucial collaboration and presentation abilities. These qualities can help them progress to becoming managers and leaders in their organizations.

3.     Work in a Variety of Industries

Data analysts are in high demand across many industries, from healthcare to finance to education to tech, etc.

With data analytics skills, you can pursue data analyst jobs in various fields and industries, including government, retail, education, and more. It means that data analysts can work on a wide range of projects and data sets, giving you greater variety in your career.

Additionally, data analysts can often take advantage of opportunities for career advancement and leadership roles, which are also plentiful in various industries.

Data analyst positions are projected to grow speedily in the coming years, making data analytics a great career choice.

With the nature of the data constantly growing and changing, data analysts have the opportunity to stay on top of new trends and technologies, making data analytics an exciting and rewarding field.

4.     Boost Problem-Solving Skills

As data analysts work with data daily, they need to be able to think critically and approach complex data problems. It requires sharp analytical and problem-solving skills, which data analysts must constantly develop and refine to succeed. 

Whether you are working on data analysis projects or managing data operations, data analysts must constantly be able to identify and solve data-related problems.

With data analytics skills, you can tap into your ability to think critically and solve complex data problems. 

Staying ahead of data trends is essential to success in any field, and data analysts are uniquely poised to do just that.

After doing a degree in data analysis, you can easily hone the problem-solving skills that can help you in your professional and personal life.

5.     Good Salary

Lastly, the other main reason to become a data analyst is that they get a good and lucrative salary as they are high in demand. Note that the annual national average salary of a data analyst is around $66,283.

So, if you need a good-paying job, you should opt for a data analyst job.

Conclusion

Data analysts are in high demand, and their career prospects are promising. If you’re good with data and enjoy working with it, becoming a data analyst is a great choice.

There are many reasons to become a data analyst, but the above top five stand out the most. If you’re on the fence about whether or not to pursue this career, jump off and go for it. You won’t regret your decision.

TAGGED: big data, data analytics
Andrey Koptelov November 12, 2022
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By Andrey Koptelov
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Andrey Koptelov is an Innovation Analyst at Itransition, a custom software development company headquartered in Denver. With a profound experience in IT, he writes about new disruptive technologies and innovations in artificial intelligence and machine learning.

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