With the rapid growth of data in the digital age, the field of data analytics has exploded in popularity. Data analyst roles are predicted to be some of the fastest growing over the next decade. This has led many people to pursue data analytics certificates to gain the skills needed for these lucrative roles.
But is getting a data analytics certificate really worth the time, effort and money required? Here we’ll examine the pros and cons of obtaining a data analytics certificate.
The growing demand for data analysts
There is an enormous demand for data analysts today. As companies and organizations collect more and more data, they need skilled professionals who can analyze it and derive meaningful insights. According to IBM, the amount of global data is doubling every two years. At the same time, the role of data analyst is expected to grow by 27.9% from 2019 to 2029, much faster than average job growth.
This presents a huge opportunity for those with data analytics skills. Becoming a certified data analyst signals to employers that you have the required skills and knowledge to fill these in-demand roles. Certifications can make your resume stand out and potentially lead to job offers and higher starting salaries.
Gain valuable data analytics skills
A data analytics certification helps you develop and master essential data skills like Python, R, SQL, data visualization, machine learning, and more. The curriculum is designed by industry leaders and aligns with the day-to-day work of data analysts. This means you gain applicable skills to tackle real-world data challenges.
For example, you’ll learn how to:
- Collect, clean and organize data from diverse sources
- Analyze and interpret complex datasets
- Identify patterns and trends through statistical analysis and data mining
- Visualize and effectively communicate data insights
- Implement machine learning algorithms for predictive analytics
These in-demand capabilities are hard to acquire through self-study alone. A structured certification program provides comprehensive training on the precise skills employers are looking for in data analysts.
Understand how to apply data analytics
Beyond technical know-how, a certificate program teaches you how to think critically about applying data analytics to drive business solutions. Coursework and projects focus on using data skills to impact real business outcomes, equipping you with knowledge of the full data analysis process.
Through case studies and hands-on scenarios, you learn best practices for:
- Asking the right analytical questions
- Designing analytics strategies tailored to business needs
- Producing analytics that provide meaningful, actionable insights
- Using analytics to optimize business operations and strategy
This higher-level understanding of the business context and value of data analytics makes certified analysts more capable and valuable in the workplace.
Credentials to boost your career
Earning an industry-recognized certification provides you with credentials that appeal to employers. 69% of employers said data analytics certifications make a job candidate more attractive. Certifications demonstrate that you have dedicated time to honing your skills and have practical abilities to tackle data challenges.
Some of the most valued IT certifications include:
- Google Data Analytics Certificate
- IBM Data Analyst Professional Certificate
- Microsoft Certified: Azure Data Analyst Associate
- SAS Certified Data Analyst
- Oracle Analytics Cloud Data Analyst Associate
- Tableau Desktop Certified Associate
These credentials signal to employers that you have mastery of data analytics tools and techniques that align with their business needs. Certified professionals are more likely to land job interviews and access better career opportunities.
Career advancement
Beyond getting your foot in the door, data analytics certifications also boost your long-term career growth. They demonstrate your commitment to continually expanding your skillset. With an advanced certification like SAS Certified Data Scientist or Microsoft Certified: Azure AI Engineer Associate, you can propel your career to higher positions and salary levels.
Your investment in certifications pays dividends through:
- Access to more advanced job roles
- Higher salary potential
- Leadership opportunities
- Expanded career options
Certifications produce an average of +11.7% boost in salaries. They open the door to management, senior analysis and architecture roles only accessible to those with higher level credentials.
Versatility to work across industries
A data analytics certification provides versatile skills applicable across many industries. Candidates with cross-industry analytical abilities are highly employable. Certifications train you in broadly useful capabilities like Python, advanced Excel, query languages, visualization tools, and more.
With a credential like the Google Data Analytics Certificate or IBM Data Analyst Professional Certificate, you have in-demand skills suitable for roles in:
- IT and technology
- Retail
- Finance and banking
- Healthcare
- Media and marketing
- Government and public sector
This versatility expands your career possibilities to diverse industries. You can pivot your career or specialize in an industry that interests you.
Learn at your own pace
Earning a certification is appealing because you can complete courses at your own pace. Programs allow you flexibility to learn alongside your current work and life commitments.
With online platforms like Coursera, Udacity, Udemy and others, you have options like:
- Self-paced online courses you take when convenient
- Part-time programs with flexible schedules
- On-demand video instruction you access anytime
- Rolling enrollment instead of fixed cohort start dates
- Learning on mobile so you can study anytime, anywhere
This flexibility empowers you to acquire new data skills without putting your career on hold. You can upskill on your own timeline.
Costs of data analytics certifications
While certifications offer many advantages, they also come with required investments of time and money. Carefully consider the costs before committing.
Time investment
Be prepared to devote focused time and effort to certification training. Quality programs entail rigor and depth – not just a quick crash course. It takes most learners around 6-9 months of consistent study to complete a respected data analytics program, whether part-time or full-time.
During this period, you’ll need to carve out 10-20 hours per week for coursework, lectures, projects and studying. You may also need to scale back other commitments. Budget the time required before embarking on a program.
Tuition costs
Data analytics bootcamps and certification programs range from free options to $20,000 for elite credentials. Here are typical price points:
Program | Typical cost |
---|---|
Coursera online courses | $29 – $99 per month |
edX courses | Free or $99 – $300 per course |
Udacity nanodegree | $400 – $2,400 total |
Udemy courses | $10 – $200 per course |
General Assembly bootcamp | $3,950 – $15,950 |
University certificate programs | $3,000 – $10,000 |
Savings are possible through discounts, scholarships and flexible payment options. Still, expect to invest at least $1,000 for quality training.
Lost income while studying
If pursuing full-time certification training, you’ll need to account for lost income from leaving your job or reducing hours. Depending on your current salary and expenses, this may represent a significant financial hit. Even with part-time study, you may need to dial back working hours.
Some bootcamps and online programs allow you to continue working, making lost income less of an issue. But assess the impact on your finances before committing.
Costs of exam prep and testing
Finally, many programs have required costs for preparing, registering, and taking certification exams. These range from $100 – $400 per exam. You’ll need to pass exams to earn official credentials. Factor these costs into your total investment.
Time for a career change
An intense certification program requires energy and diligence. If you’re burnt out or unfulfilled in your job, this can be challenging. Before signing up, thoughtfully assess where you are in your career.
Changing careers into analytics may be easier when you:
- Desire a career pivot from an unrewarding job
- Feel stuck with no growth opportunities
- Have a reasonable cushion of savings
- Receive support from family to change paths
- Crave new challenges and skills
If your current work is uninspiring, upskilling into analytics can reinvigorate your career. Use that energy to fuel certification success.
What you give up
Committing to certification also entails sacrifices. You may need to give up:
- Nights, weekends and free time
- Income from a job or freelancing
- Time with family, friends and hobbies
- Vacations and travel
- Time invested in your current career
These sacrifices can strain finances, relationships and mental health. Be honest about what you’re willing to temporarily give up to make certifying a success.
Support structure
A strong personal and professional support structure helps withstand certification demands. Look at your current situation.
Pursuing analytics training works best when you have:
- A partner, family and friends who encourage the pivot
- Savings to pay bills during training
- Flexible job that allows study time
- Mentors who can advise your transition
- Strong time management and self-discipline
A support network enables you to commit fully to certification and manage the stress. Seek out these resources before embarking on intensive training.
Your learning abilities
To benefit from a data analytics program, you need certain core abilities:
- Mathematical and analytical aptitude
- Curiosity and critical thinking skills
- Ability to learn complex technical tools
- Data modeling and statistical capabilities
- Coding expertise in Python, SQL, R and more
- Focus for self-paced learning
Certification programs accelerate skills, but don’t replace foundational abilities. Assess your learning skills to pick the right data training path.
Your career ambitions
Before investing in certification, be clear on your career goals. Analytics roles span many levels and specialties like:
- Business analysts
- Data analysts
- Marketing analysts
- Financial analysts
- Operations analysts
- Data engineers
- Data architects
- Data scientists
- Machine learning engineers
Certifications open more doors when targeted to your specific ambitions. Focus on training tailored for the role and industry you want.
Consider certificate alternatives
Certifications aren’t the only route to analytics careers. Other options include:
- Self-study through online courses and resources
- On-the-job training at your current company
- Internships focused on gaining data skills
- Degree programs in data science or analytics
- Transitioning your experience from roles like business analyst
Certifications have advantages but aren’t universally required. Weigh if alternatives like these fit your background and goals.
The best jobs want experience
While certifications can help land that first analytics role, many top positions ultimately require experience. Employers hiring for senior analysts, architects and scientists still look for solid track records.
Certification shows you have potential, but established candidates have proven abilities like:
- Years executing successful analytics initiatives
- Management and leadership accomplishments
- Major contributions and impact made through data insights
- Large-scale project successes and failures to learn from
- Diverse analytics challenges faced
Post-certification, focus on excelling in your first data role to open more senior doors. Experience gets the best offers.
Weighing the pros and cons of data analytics certification
Here are key considerations when deciding if certification is worthwhile for you:
Pros | Cons |
---|---|
Develop in-demand data skills | Significant time commitment |
Gain credentials that impress employers | Major costs for tuition and lost income |
Learn real-world analytics applications | Sacrifices career progress in your current field |
Position yourself for lucrative data roles | Limitations if you lack core analytical abilities |
Change careers or enhance your current path | Still need experience for senior-level roles |
Certification makes the most sense when you:
- Want to pivot into a data career from a different background
- Can commit focused time and accept costs
- Have innate analytical abilities to develop
- Desire roles like business analyst and data analyst
With the right circumstances, data analytics credentialing can be a worthwhile investment in new skills and opportunities.
The final word on data analytics certification
While not universally necessary, data analytics certifications offer proven value in the right situations. They equip you with specialized abilities to extract insights from data in demand across industries. Certifications open doors to rewarding careers while signaling your capabilities to employers.
Before pursuing a program, reflect on your career ambitions, skills, and circumstances to determine if certifying makes sense. Committing requires sacrifices but pays dividends for motivated learners. Combine certification with real-world experience to maximize career advancement.
In our data-driven world, analytics skills deliver immense value. For those dedicated to unlocking that value, certification can be a strategic first step towards an exciting new data career.