How to Get Into Data Analytics If You Don’t Have the Right Degree

Are you passionate about data analytics but discouraged by the idea that you need a specific degree to pursue a career in this field? Think again! Contrary to common belief, there are alternative pathways that can lead you to a successful career in data analytics, even if you don’t have the ‘right’ degree.

In today’s digital age, data analytics plays a crucial role in solving complex business problems and driving strategic decision-making. As organizations increasingly rely on data to gain insights, the demand for skilled data analysts is skyrocketing. So, how can you join this exciting field without the typical qualifications? Let’s find out.

Table of Contents

Key Takeaways:

  • Discover alternative pathways to enter the field of data analytics.
  • Build a strong foundation in statistics to excel in data analysis.
  • Acquire programming skills in languages like Python or R.
  • Gain practical experience through internships, projects, and bootcamps.
  • Showcase your skills through side projects and certifications.

Understanding the Field of Data Analytics

Data analytics is a rapidly growing field that plays a crucial role in businesses and industries across the globe. It involves the analysis, interpretation, and extraction of valuable insights from large sets of data. A career in data analytics can be highly rewarding, both professionally and financially, given the increasing demand for skilled professionals in this domain.

As a data analyst, you will be responsible for collecting and organizing data, identifying patterns and trends, and translating complex data into actionable recommendations. You will play a key role in helping organizations make informed decisions, optimize processes, and improve overall performance.

Building a successful career in data analytics requires a combination of technical skills, analytical thinking, and problem-solving abilities. Let’s take a closer look at the key skills and knowledge needed to thrive in this field:

  1. Quantitative and statistical analysis: Data analysts must have a strong foundation in statistics and possess the ability to apply statistical techniques to derive meaningful insights from data sets.
  2. Data manipulation and visualization: Proficiency in tools like SQL, Python, or R is essential to extract, clean, and transform data. Additionally, data visualization skills using tools like Tableau or PowerBI are crucial for effectively communicating findings.
  3. Machine learning and predictive modeling: Knowledge of machine learning algorithms and predictive modeling techniques is becoming increasingly important in the field of data analytics.
  4. Business acumen: Data analysts need to understand the business context in which they operate and be able to translate data insights into actionable recommendations that drive business growth.

Table: Key Skills for Data Analytics Career

Skill Description
Quantitative and statistical analysis Ability to apply statistical techniques to analyze data
Data manipulation and visualization Proficiency in tools like SQL, Python, or R for data processing and visualization
Machine learning and predictive modeling Knowledge of algorithms and techniques for predicting outcomes
Business acumen Understanding of the business context and ability to provide actionable insights

Data analytics is a dynamic field that constantly evolves with new technologies and methodologies. Keeping up with the latest trends and advancements is crucial to stay competitive in the job market.

“Data is the new oil, and analytics is the combustion engine that powers modern organizations.” – Peter Sondergaard

H3: The Value of Data Analysts in Organizations

Data analysts are integral to organizations of all sizes. Their expertise and insights drive data-informed decision-making and optimize business processes. By providing valuable insights, data analysts help identify growth opportunities, mitigate risks, and improve overall operational efficiency.

The ability to transform raw data into actionable insights is invaluable in today’s data-driven world. Hiring skilled data analysts allows organizations to unlock the full potential of their data and gain a competitive edge in the market.

Furthermore, data analytics has a significant impact on various industries, including finance, healthcare, marketing, e-commerce, and more. It enables organizations to better understand customer behavior, optimize marketing strategies, improve product offerings, and enhance customer satisfaction.

As the volume of data continues to grow exponentially, the demand for data analysts will continue to rise. This presents excellent career opportunities for individuals passionate about working with data and making a meaningful impact on businesses.

The Importance of a Degree in Data Analytics

While pursuing a degree in data analytics can provide individuals with a solid educational foundation and in-depth knowledge of the field, it is important to remember that having a degree is not the only path to a successful career in data analytics. The value of a degree lies in the comprehensive understanding and specialized skills it can offer, but alternative pathways can also lead to rewarding opportunities in this fast-growing industry.

Obtaining a degree in data analytics can equip individuals with essential technical knowledge, analytical skills, and a deep understanding of statistics. It can also demonstrate a commitment to learning and a dedication to the field, which can be valued by employers. Additionally, a degree can provide access to valuable resources such as industry connections, internships, and research opportunities, which can further enhance job prospects.

“A degree in data analytics can provide individuals with a strong foundation and important technical skills that are highly sought after in the industry.” – John Adams, Data Analytics Professor

However, it is essential to highlight that degrees are not the sole determinant of success in data analytics. Many professionals in this field have built successful careers through alternative paths that emphasize practical experience, continuous skill-building, and a strong portfolio. Real-world experience and practical application of data analytics skills can often be just as valuable as formal education.

Employers in the data analytics industry increasingly recognize the importance of hands-on experience, strong problem-solving abilities, and a solid understanding of data analysis techniques. They value individuals who can demonstrate their skills through concrete examples, such as projects, certifications, or freelance work. This emphasis on practical ability opens the door to aspiring data analysts who may not have conventional degrees but possess strong skills.

Ultimately, the choice of pursuing a degree in data analytics or taking an alternative path depends on an individual’s circumstances, goals, and learning style. It is important to consider personal preferences and opportunities for skill development when deciding which route to take. Regardless of the chosen path, continuous learning, staying updated with industry trends, and actively seeking opportunities to apply data analytics skills are essential for long-term success in this dynamic field.

Alternative Paths to Enter Data Analytics

While a relevant degree can certainly open doors in the field of data analytics, it’s important to note that there are alternative paths to embark on this exciting career journey. These paths take into account practical experience, a strong skill set, and the ability to showcase relevant projects. By leveraging these alternative routes, individuals without a direct degree can still find success in the world of data analytics.

One such alternative path is gaining practical experience in data analytics. Companies often value hands-on experience and the ability to apply theoretical knowledge to real-world situations. By actively seeking internships, freelance projects, or personal projects, aspiring data analysts can acquire the necessary skills and demonstrate their expertise to potential employers.

Building a strong skill set is also crucial for entering the field of data analytics without a relevant degree. While formal education provides a structured framework, individuals can develop their skills through self-study, online courses, and coding bootcamps. By focusing on key areas such as statistics, programming languages like Python or R, and data visualization, aspiring data analysts can acquire the essential abilities needed to excel in the field.

Alternative routes offer opportunities for individuals without a relevant degree to break into the field of data analytics. By gaining practical experience and developing a strong skill set, they can showcase their abilities and compete in this increasingly competitive market.

To further highlight the value of these alternative paths, here is a table comparing traditional education with alternative approaches:

Traditional Education Alternative Approaches
Requires a specific degree No degree requirement
Takes several years to obtain a degree Opportunity to start gaining experience immediately
Focused on general data analytics curriculum Ability to specialize in specific areas or technologies
Structured learning environment Flexibility to customize learning approach

As the table demonstrates, alternative approaches provide unique advantages for individuals looking to enter the field of data analytics. The ability to gain experience, specialize in specific areas or technologies, and have flexibility in the learning journey can empower aspiring data analysts and set them apart from their peers.

Ultimately, while a relevant degree in data analytics can certainly provide a strong foundation, it is by no means the only path to success in this field. By embracing alternative routes, individuals without a degree can acquire the necessary skills, gain practical experience, and become valued contributors in the world of data analytics.

Develop a Strong Foundation in Statistics

Statistics forms the backbone of data analytics, providing the necessary tools and techniques for data analysis and interpretation. To excel in the field of data analytics, it is crucial to develop a strong foundation in statistics. With a solid understanding of statistical concepts, individuals can effectively analyze data, identify patterns, and make informed decisions.

“Statistics is the grammar of data science.”

The Importance of Statistics in Data Analysis

In data analytics, statistics plays a vital role in extracting meaningful insights from datasets. Statistical methods enable data analysts to accurately analyze trends, identify correlations, and evaluate the reliability of results. By applying statistical concepts such as probability, hypothesis testing, and regression analysis, analysts can draw meaningful conclusions and make data-driven decisions.

Resources to Enhance Statistical Knowledge

To develop a strong foundation in statistics, individuals can utilize various resources such as online courses, tutorials, and books. These resources provide comprehensive explanations of statistical concepts and practical examples to reinforce learning. Here are some recommended resources:

  1. Online Courses:
    • Introduction to Statistics by Coursera
    • Statistics for Data Science by edX
    • Applied Data Science with Python Specialization by Coursera
  2. Tutorials:
    • Khan Academy’s Statistics and Probability Tutorials
    • Statistics How To
    • DataCamp’s Statistics Courses
  3. Books:
    • “The Elements of Statistical Learning” by Trevor Hastie, Robert Tibshirani, and Jerome Friedman
    • “Statistics for Business and Economics” by Paul Newbold, William L. Carlson, and Betty Thorne
    • “Practical Statistics for Data Scientists” by Peter Bruce and Andrew Bruce

Investing time in learning and mastering statistics will provide a strong foundation for data analytics, enabling individuals to perform accurate data analysis and contribute effectively to the field.

Acquire Programming Skills

Programming skills are essential for data analysts, enabling them to effectively manipulate and analyze data. Particularly in languages such as Python or R, coding proficiency is highly valued in the field of data analytics. Fortunately, there are numerous online resources and programming courses available to help individuals acquire these essential skills.

Recommended Programming Courses for Data Analysts

  1. Python for Data Analysis: This course offers a comprehensive introduction to Python programming specifically tailored for data analysis. It covers data manipulation, data visualization, and statistical analysis using Python’s powerful data science libraries such as pandas, NumPy, and matplotlib.
  2. R Programming for Data Science: This course focuses on teaching the fundamentals of R programming, a popular language among data analysts and statisticians. Participants will learn how to import, manage, clean, and visualize data using R, as well as how to perform advanced statistical analysis.
  3. Data Science and Machine Learning Bootcamp with Python: Designed for individuals with basic programming knowledge, this bootcamp covers a wide range of topics including data cleaning, feature engineering, machine learning algorithms, and model evaluation. Participants will gain hands-on experience in applying Python to solve real-world data analysis problems.

By enrolling in these programming courses, aspiring data analysts can develop the necessary coding skills to thrive in the field of data analytics. These courses provide a solid foundation in programming languages commonly used for data analysis, empowering individuals to effectively manipulate and analyze data to derive meaningful insights.

Gain Experience Through Internships and Projects

Obtaining practical experience in data analytics is crucial for individuals looking to establish a successful career in the field. Internships, freelance projects, and personal projects offer valuable opportunities to apply theoretical knowledge to real-world scenarios and build a strong portfolio.

Internships are an excellent way to gain hands-on experience while working alongside industry professionals. They provide a chance to apply data analytics skills in a professional setting and learn from seasoned practitioners. Many companies offer internships specifically targeted towards data analytics, providing interns with the necessary guidance and mentorship.

Freelance projects offer flexibility and the opportunity to work on a variety of projects across different industries. Platforms such as Upwork and Freelancer connect data analytics professionals with clients seeking their expertise. By taking on freelance projects, individuals can enhance their skills while building a diverse portfolio.

Personal projects are an excellent way to showcase individual capabilities and creativity. By working on personal data analytics projects, individuals can demonstrate their problem-solving abilities, analytical skills, and innovative thinking. These projects can be shared on professional platforms like GitHub to gain visibility and recognition within the data analytics community.

Internships and projects provide invaluable experience that cannot be gained solely through academic education. They contribute to the development of practical skills, such as data collection and cleaning, statistical analysis, and data visualization. Moreover, they offer an opportunity to work on real-world datasets and encounter challenges that can deepen knowledge and expertise.

– John Smith, Senior Data Analyst

When looking for internships or projects, it is essential to research and target organizations that align with your specific interests and goals. Networking with professionals in the industry, attending job fairs, and leveraging online platforms like LinkedIn can help individuals discover relevant opportunities.

Building a comprehensive and diverse portfolio is crucial for showcasing skills and capabilities to potential employers. Including a variety of projects that demonstrate proficiency in different areas of data analytics, such as data cleaning, statistical modeling, and data visualization, can make a portfolio stand out.

Leverage Data Analytics Bootcamps and Online Courses

For individuals looking to enhance their data analytics skills and build a strong foundation in the field, data analytics bootcamps and online courses can be invaluable resources. These learning platforms offer specialized training programs designed to provide hands-on experience and practical knowledge. Whether you prefer in-person instruction or the flexibility of online learning, there are various options available to cater to your learning preferences and schedule.

Attending a data analytics bootcamp can offer intensive and immersive training in a short period. These programs are typically led by industry experts who guide participants through a structured curriculum and provide real-world projects to apply their newfound skills. Bootcamps often cover essential topics such as data analysis, data visualization, programming, and statistical modeling.

Online courses, on the other hand, provide the flexibility to learn at your own pace and from the comfort of your own home. There are numerous reputable online platforms that offer data analytics courses, ranging from beginner to advanced levels. These courses provide comprehensive content, interactive exercises, and practical assignments to help you build the necessary skills for a career in data analytics.

When choosing a data analytics bootcamp or online course, it is essential to consider factors such as the curriculum, instructor credentials, real-world projects, and alumni success stories. Here are some highly regarded bootcamps and online platforms to get you started:

Bootcamp or Online Platform Description
DataCamp DataCamp offers a vast catalog of interactive online courses covering various aspects of data analytics. Their courses are designed to help individuals acquire practical skills in programming, statistics, machine learning, and data manipulation.
General Assembly General Assembly offers immersive data analytics bootcamps both online and at physical campuses worldwide. Their programs provide a comprehensive curriculum covering data analysis, data visualization, and SQL, among other essential topics.
Udacity Udacity offers a range of data analytics nanodegree programs that provide hands-on experience with real-world projects. These programs cover various aspects of data analytics, including programming, data wrangling, and data visualization.

By leveraging the resources available through data analytics bootcamps and online courses, individuals can gain the skills and knowledge needed to thrive in the field of data analytics. These educational opportunities provide a structured learning environment, access to expert instructors, and the chance to work on real-world projects. Whether you prefer an immersive bootcamp experience or the flexibility of online courses, there are options available to suit your individual learning style and career goals.

Networking and Building Industry Connections

Networking plays a vital role in establishing a successful career in the data analytics industry. Building industry connections can open doors to new opportunities, valuable insights, and collaborative partnerships. Here are some strategies for networking and connecting with the data analytics community:

Attend Industry Events

Industry events such as conferences, seminars, and networking gatherings provide a great platform to meet professionals in the data analytics field. Attend relevant events where you can engage with experts, exchange ideas, and expand your network.

Join Professional Organizations

Joining professional organizations, such as the Data Analytics Association or the International Institute of Business Analysis, can provide access to a community of like-minded professionals. These organizations often host events, webinars, and forums where you can connect with industry leaders and peers.

Engage on Social Media Platforms

Participate in online communities and discussion groups on platforms like LinkedIn, Twitter, and Reddit. Follow industry influencers, join data analytics-related groups, and actively contribute to conversations. This can help you stay up-to-date with industry trends and connect with professionals from diverse backgrounds.

Collaborate on Open Source Projects

Participating in open source projects related to data analytics can provide opportunities to collaborate with other professionals and contribute to the community. Platforms like GitHub offer a space for data analysts to showcase their skills, collaborate on projects, and build connections with industry experts.

By actively networking and building industry connections, you can enhance your visibility within the data analytics community and uncover new career prospects. Networking can also lead to mentorship opportunities, collaborations on projects, and valuable insights from seasoned professionals.

Showcasing Your Skills Through Side Projects and Certifications

One of the most effective ways to demonstrate your abilities and stand out in the competitive field of data analytics is by showcasing your skills through side projects and certifications. These valuable additions to your professional profile can provide concrete evidence of your expertise and dedication. Here are some tips to help you effectively leverage side projects and certifications:

1. Selecting Relevant Projects

When choosing side projects, it’s essential to focus on topics and datasets that align with the skills you want to highlight. Select projects that showcase your proficiency in data analysis, visualization, and problem-solving. By tackling real-world challenges and producing actionable insights, you can demonstrate your ability to apply data analytics techniques to drive business success.

2. Creating an Impressive Portfolio

As you complete side projects, compile them into a well-organized portfolio that showcases your range of skills and accomplishments. Provide clear explanations of each project’s objectives, methodologies used, and the outcomes achieved. Including visualizations, graphs, and data-driven narratives will help make your portfolio visually engaging and easy to comprehend.

3. Pursuing Reputable Certifications

Obtaining certifications from trusted organizations can boost your credibility and enhance your marketability in the data analytics field. Look for certifications that are recognized by industry professionals and employers. Some popular certifications in data analytics include:

Certification Issuing Organization
Microsoft Certified: Azure Data Scientist Associate Microsoft
Google Data Analytics Professional Certificate Google
IBM Data Science Professional Certificate IBM

These certifications demonstrate your proficiency in specific data analytics skills and provide evidence of your dedication to professional growth. They can help you stand out in the job market and increase your chances of landing desirable data analytics positions.

By investing time and effort into side projects and pursuing reputable certifications, you can effectively showcase your skills and capabilities in data analytics. These tangible demonstrations of your abilities will set you apart from the competition and open doors to exciting career opportunities in this rapidly growing field.

Leveraging Transferable Skills

While a degree in data analytics can provide a solid foundation for a career in the field, individuals with different educational backgrounds can still enter the world of data analytics by leveraging their transferable skills and relevant experiences. By identifying and highlighting the skills that are applicable to data analytics, these individuals can showcase their capabilities to potential employers and make a successful transition into this in-demand field.

Transferable skills are abilities that can be applied across various industries and roles. These skills can be highly valuable in data analytics, as they demonstrate adaptability, problem-solving capabilities, and a strong work ethic. Here are some examples of transferable skills that can be leveraged in the field of data analytics:

  1. Analytical Thinking: The ability to analyze complex problems, identify patterns, and derive insights from data is crucial in data analytics. Individuals who possess analytical thinking skills can effectively apply their logical reasoning and critical analysis capabilities to solve real-world data challenges.
  2. Communication: Effective communication is essential in data analytics, as professionals often need to convey complex technical concepts to non-technical stakeholders. Individuals with strong communication skills can present their findings in a clear and understandable manner, bridging the gap between data analysis and business decision-making.
  3. Problem-Solving: Data analytics involves identifying and resolving data-related issues and optimizing processes. Individuals with strong problem-solving skills can effectively approach data challenges, develop innovative solutions, and drive continuous improvement within an organization.
  4. Project Management: Data analytics projects often involve managing timelines, resources, and stakeholders. Individuals who have experience or expertise in project management can effectively plan, execute, and deliver data analytics initiatives, ensuring their successful implementation and the achievement of project goals.
  5. Domain Knowledge: While a background in data analytics is beneficial, domain knowledge in specific industries can be a significant asset. Individuals who have expertise or experience in areas such as marketing, finance, healthcare, or retail can leverage their domain knowledge to provide valuable insights and drive data-informed decision-making.

By effectively showcasing these transferable skills, individuals can position themselves as valuable assets in the field of data analytics. Whether through highlighting relevant experiences, sharing success stories, or participating in data analytics-related projects, individuals can demonstrate their ability to apply their skills in this rapidly growing field.

Having a different educational background should not deter individuals from pursuing a career in data analytics. With the right mindset, a willingness to learn, and a strategic approach to leveraging transferable skills, anyone can unlock opportunities in this exciting field.

The Growing Demand for Data Analysts

In today’s ever-evolving job market, the demand for data analysts is skyrocketing across various industries. As businesses recognize the value of data-driven decision-making, the need for skilled professionals who can derive meaningful insights from complex datasets has never been higher.

Data analysts play a critical role in helping organizations understand trends, identify patterns, and make informed decisions that drive success. Their expertise in data analysis, statistical modeling, and data visualization allows them to extract actionable intelligence from raw data, providing companies with a competitive edge.

The job market for data analysts is thriving, with companies of all sizes and across industries actively seeking data-driven professionals to fill their ranks. From technology giants to healthcare providers to financial institutions, the demand for skilled data analysts continues to grow steadily.

According to the Bureau of Labor Statistics, the employment of data analysts is projected to grow 21% from 2020 to 2030, much faster than the average for all occupations. This significant growth is attributed to the increasing reliance on data-driven decision-making and the expanding availability of big data.

Industry Projected Growth
Tech +
Finance +
Healthcare +
Retail +

As shown in the table above, the projected growth in demand for data analysts varies across industries. The technology sector, in particular, is expected to experience a surge in demand, driven by advancements in artificial intelligence, machine learning, and data-driven technologies.

With such a promising job market, aspiring data analysts have a wealth of opportunities to explore. Whether it’s working in the tech industry, finance, healthcare, or any other sector, the demand for skilled data analysts will continue to rise.

If you’re considering a career in data analytics, now is the perfect time to embark on this exciting and rewarding journey. By acquiring the right skills, staying up-to-date with emerging trends, and showcasing your expertise, you can position yourself for success in the ever-growing field of data analytics.


To succeed in the field of data analytics, a relevant degree is not the only path. This article has provided insights into alternative pathways that individuals without a relevant degree can take to enter the industry.

By developing a strong foundation in statistics, acquiring programming skills, gaining practical experience through internships and projects, attending data analytics bootcamps or online courses, networking, and leveraging transferable skills, it is possible to build a successful career in data analytics.

The growing demand for data analysts in various industries presents ample opportunities for individuals to showcase their skills and contribute to organizations’ success. With dedication, continuous learning, and a determined mindset, anyone can thrive in this dynamic field, regardless of their educational background. Embrace the possibilities and embark on a rewarding journey in data analytics today!


Can I pursue a career in data analytics if I don’t have a relevant degree?

Yes, you can! While having a degree in data analytics can be beneficial, it is not the only path to a successful career in the field. There are alternative pathways and strategies you can adopt to enter the field and gain the necessary skills and experience.

What does data analytics entail?

Data analytics involves analyzing large sets of data to uncover insights and make informed decisions. It requires skills in statistical analysis, data visualization, and programming, among others. Data analysts play a crucial role in helping organizations identify trends, solve problems, and optimize their operations.

Is a degree in data analytics necessary to succeed in the field?

While a degree in data analytics can provide a strong foundation and open up more opportunities, it is not a prerequisite for success in the field. Many successful data analysts have entered the profession through alternative paths, such as gaining practical experience, building a strong skill set, and showcasing relevant projects.

How can I enter the field of data analytics without a relevant degree?

There are several alternative paths you can take to enter the field of data analytics without a relevant degree. These include gaining practical experience through internships or personal projects, acquiring programming skills, attending data analytics bootcamps or online courses, networking within the industry, and leveraging transferable skills from other fields.

How can I develop a strong foundation in statistics for data analytics?

Developing a strong foundation in statistics is crucial for data analytics. You can enhance your statistical knowledge through online courses, tutorials, and books. Platforms like Coursera and Udemy offer a wide range of resources to help you improve your statistical skills.

What programming skills are important for data analytics?

Programming skills are essential for data analysts, particularly in languages such as Python or R. These languages are widely used in data analysis and provide powerful tools and libraries for working with data. Online programming courses and resources can help you acquire the necessary programming skills for data analytics.

How can I gain practical experience in data analytics?

Gaining practical experience is vital in data analytics. You can do this through internships, freelance projects, or personal projects. Look for opportunities to work with real datasets and solve practical problems to build your experience and showcase your skills to potential employers.

Are there any data analytics bootcamps or online courses available?

Yes, there are many data analytics bootcamps and online courses available that can help you develop the necessary skills for a career in data analytics. Some reputable bootcamps include General Assembly and DataCamp, while online platforms like Coursera and edX offer a wide range of data analytics courses.

How important is networking in the data analytics industry?

Networking is highly important in the data analytics industry. Building connections with professionals in the field can provide valuable insights, mentorship, job opportunities, and collaborations. Attend industry events, join professional organizations, and participate in online communities to expand your network.

How can I showcase my skills and capabilities in data analytics?

Showcasing your skills and capabilities is crucial in data analytics. You can do this through side projects and certifications. Select relevant projects that demonstrate your ability to analyze data and provide actionable insights. Additionally, reputable certifications like the Certified Analytics Professional (CAP) can enhance your credibility.

How can I leverage my transferable skills to enter the field of data analytics?

If you have a different educational background, you can leverage your transferable skills to enter the field of data analytics. Skills such as problem-solving, critical thinking, and communication are applicable to data analytics and can complement your technical skill set. Highlight these skills in your resume and during interviews.

Is there a high demand for data analysts in the job market?

Yes, there is a growing demand for data analysts across various industries. With the increasing volume of data being generated, organizations need professionals who can analyze and interpret this data to drive informed decision-making. The job market for data analysts is expected to expand in the coming years.

What is the conclusion of pursuing a career in data analytics without a relevant degree?

In conclusion, pursuing a career in data analytics without a relevant degree is possible. By adopting alternative paths, building a strong skill set, gaining practical experience, and showcasing your capabilities, you can succeed in the field. With dedication, continuous learning, and the right mindset, you can carve out a rewarding and fulfilling career in data analytics.

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Deepak Vishwakarma


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