Here’s why you should learn data analytics
Worldwide, big data market revenues for software and services are projected to increase from $42 billion in 2018 to $103 billion in 2027, gaining a CAGR of 10.48 percent, according to Wikibon. Additionally, an estimated 2.7 million job postings for data analytics and data science are projected in the United States by 2020.
With more and more companies understanding the importance of Big Data as a useful source for gaining insights and making informed decisions, the demand for data analytics specialists who can define Big Data, uncover hidden patterns, spot opportunities and create insights for the improvement of business are surely benefiting from trending job opportunities in data analytics.
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With big data seeing massive adoption, you’ll now find analytics being used from aviation route planning to predictive maintenance analysis in manufacturing plants. Even industries like retail use analytics to improve customer loyalty and tailor unique offerings.
Why Do You Need a Data Analytics Certification?
Increases Your Chances to Land Highly Coveted Roles
Simply put, a certification can increase your likelihood to get hired. In a study from Microsoft, 91 percent of hiring managers claimed that certification played a major role in the candidate selection process. It’s not easy to earn a respected data analytics certification and there are many lucrative opportunities for those who are certified in the field. Your resume will surely stand out from the rest when you have the relevant certification. Therefore, this gives employers another reason to invest in you.
Just to name a few, here are a few different job titles you may be qualified for once you have a professional certification in data analytics:
Data Analyst: Data analysts are expected to draw insight from the data that directly impacts business decisions. Data analysts are directly involved in day-to-day business activities and there are a lot of ad hoc analyses that a data analyst is expected to do.
Business Intelligence Analyst: BI analyst uses data to help figure out market and business trends by analyzing data to develop a clearer picture of where the company stands. The major difference between a data analyst’s role and a BI analyst’s role is that a data analyst focuses on algorithms to determine relationship between data offering insights. A business analyst, on the other hand, analyzes data and assesses requirements from a business perspective related to an organization’s overall system.
Data Visualiser: A data visualiser is responsible for creating weekly dashboards to inform the management about weekly sales of different products, orders, user flow, user behavior, and so on.
Data and Analytics Manager: In this role, the manager leads the team and s/he gives direction to the data science team and makes sure the right priorities are set. The person combines strong technical skills in a diverse set of technologies, such as SAS, R, SQL, Excel, Python, among others,along with the social and leadership skills required to manage a team.
If you are starting a career in data analytics, holding a data analytics certificate will provide you with a lot of great options. A data analyst can advance his/her career to Business Analyst, Operations Manager or Senior Business Analyst. From these positions, one may be promoted to Sr. Operations Manager, Lead Business Analyst or Analytics Manager.
It Makes You Eligible Across Multiple Domains
E-commerce, marketplaces, finance, healthcare, entertainment, and retail are just some of the industries all leveraging the power of data analytics today. There are a million avenues for certified data analysts. Specifically, countries like the United States, United Kingdom, Germany, Italy, France, and India have been employing data scientists and data analysts at a steady pace. A data analytics certification can make you eligible for a variety of relevant job roles, such as solution architect, data scientist, project manager, business intelligence professional and statistician.
The skill sets developed in one industry or country are usually easily transferable to another industry or country. Hence, one is not tied to a particular industry and can explore opportunities in another industry in the future.
Less Investment Needed Than a College Degree or Learning on the Job
Comparatively, college degrees cost more and take longer. Additionally, students spend a lot of time and money learning a lot of general academics. With a professional certification, they receive practical training that better prepares them for the industry they’re interested in working in.
Learning on the job takes a long time and it is also highly unstructured. You could end up making avoidable mistakes, which may have significant costs to your career.
There aren’t any prerequisites, such as a college degree or diploma to get certified as a data analyst. But there are some strong skills that are required to excel in this field, such as analytical skills, numeracy skills, technical and computer skills, attention to details, business skills, and so on. These skills can make for a great data analyst, and can usually be acquired through a focused online education program.
It Shows Your Degree of Passion & Self-Motivation
A certification on your resume will show potential employers and professional peers that you are an individual who takes your career seriously. Most hiring managers are looking for candidates who are driven and sincere about their job aspirations. Any self-motivated individual who is keen on a data analytics career would have at least one certification of international recognition in his/her repertoire. Another undeniable benefit of enrolling in an online certification program is the opportunity to work hands-on with actual projects, which is one feature that Simplilearn offers through their Data Analytics Certification Course.
It Defines Your Credibility
A certification is a validation of your skills. When organizations are looking to hire a data analyst, the first preference is often for those candidates who have professional training from an accredited institute. Earning a professional certification in data analytics is evidence of high standards of education.
Potential Salary Increase
There are several factors that people consider when making their career choices, but let’s face it, one of those factors is often money. Social Security reports that the average American income is $50,321.89 annually. But a few quick searches on some of the most popular job listing websites show that careers in the data analytics field often provide a lucrative salary that far surpasses the nation’s average. According to PayScale.com, the national average salary for data analysts is $58,522. But as professionals gain more experience and grow in the data analytics field, their salary tends to reflect those changes. Someone with a more advanced position in the industry, such as a data scientist, tends to make an average of $139,840 annually. There aren’t a lot of other jobs out there that make it possible to make this kind of money without a college degree; usually, professionals in this salary bracket have professional degrees beyond a four-year college degree.
Keeps You Updated with the Latest Industry Trends
Earning a data analytics certification will help you stay updated on the latest trends in the industry. Learning something new every day is the key to expand your knowledge base. If you are a working professional, you wouldn’t have time to learn these things from multiple sources. As such, it’s best to enroll in an education program that provides you with professional certification. This will even make you an asset to your employer in the future.
If you are only learning on the job, then you are learning only a portion about the vast field of data analytics: just in your industry, specific to the tools/business needs of your company. A certification course from Simplilearn offers hands-on projects, assignments and interaction with experts and peers across industries, which will keep you updated with practical knowledge about different fields within data analytics.