In today’s data-driven world, there is an increasing demand for professionals who can make sense of the vast amounts of information generated by businesses and organizations. Data analytics is an exciting and rewarding field that offers numerous opportunities for career growth and advancement, even for those without a background in information technology.

Data analytics involves analyzing and interpreting data to identify patterns, trends, and insights that can be used to inform business decisions. This field encompasses a wide range of skills and techniques, including data visualization, statistical analysis, machine learning, and data mining. While data analytics has traditionally been associated with IT and computer science, there is an increasing recognition of the importance of data analytics in other fields, such as finance, healthcare, marketing, and logistics.

So, why is data analytics a better career option for a non-IT person? Here are some key advantages to consider:

• Diverse career opportunities

One of the biggest advantages of pursuing a career in data analytics is the diverse range of job opportunities available. Data analytics roles are found across a wide range of industries and sectors, from finance and healthcare to marketing and logistics. This means that there are many different types of jobs available, each with its own set of challenges and opportunities for growth and advancement.

• High demand for data analytics professionals

Another advantage of pursuing a career in data analytics is the high demand for professionals with these skills. According to the U.S. Bureau of Labor Statistics, employment in the field of data analytics is projected to grow by 11% between 2020 and 2030, much faster than the average for all occupations. This means that there are plenty of job opportunities available for those with the right skills and qualifications.

• Transferable skills

Data analytics requires a range of skills, including critical thinking, problem-solving, and attention to detail. These are skills that are transferable across many different industries and job roles. Even if you decide to move away from data analytics in the future, the skills you develop in this field will be valuable in many other roles.

• Competitive salaries

Data analytics is a high-paying field, with competitive salaries offered for entry-level positions and senior roles alike. According to Glassdoor, the average salary for a data analyst in the United States is around $76,000 per year, with more experienced professionals earning upwards of $100,000 or more.

• Opportunities for growth and advancement

Finally, data analytics offers many opportunities for growth and advancement. As you develop your skills and gain experience, you can take on more senior roles and responsibilities, or specialize in a particular area of data analytics, such as data visualization, machine learning, or data mining. You may also have the opportunity to move into leadership roles or start your own data analytics consultancy.

So, what are the key skills and qualifications you need to pursue a career in data analytics? While a background in IT or computer science can be helpful, it is not essential. Here are some of the key skills and qualifications that are important in this field:

• Strong analytical and problem-solving skills

Data analytics requires a strong analytical mindset and the ability to think critically and creatively about data. You should be comfortable working with numbers and data, and be able to identify patterns, trends, and insights that can inform business decisions.

• Knowledge of statistics and data analysis techniques

A good understanding of statistics and data analysis techniques is essential for data analytics. You should be familiar with statistical concepts such as regression analysis, hypothesis testing, and confidence intervals, as well as data visualization tools such as Tableau, Power BI, or Excel.

• Knowledge of programming languages and software tools

While a background in programming is not essential, it can be

helpful to have some knowledge of programming languages and software tools commonly used in data analytics. Some of the most commonly used programming languages in data analytics include Python, R, SQL, and Java. Additionally, software tools such as Hadoop, Spark, and SAS are widely used in the industry.

• Communication skills

Effective communication skills are crucial in data analytics, as you will need to explain complex data analysis concepts to non-technical stakeholders. You should be able to present data and insights in a clear and concise manner, and be able to tailor your communication style to your audience.

• Certifications and training programs

There are many certifications and training programs available in data analytics that can help you develop the skills and knowledge needed to succeed in this field. Some of the most widely recognized certifications include the Certified Analytics Professional (CAP), the Microsoft Certified: Azure Data Scientist Associate, and the SAS Certified Data Scientist.