Data Analytics Career Path: How to Start, Grow, and Succeed

By Trisha Manna Category Data Science Reading time 10.5 mins Published on Jun 07, 2023

We have become silent spectators of a technologically evolving world. From basic living needs to business world actions, automation takes a prominent position. The collaboration of business operations with technology leaps an analytics-driven culture. The foundation of competitiveness is evolving every time change takes place.

Advanced technology and analytics include complex datasets that demand effective ways of simplifying them to reach informed decisions. Under the scope of an analytics-driven culture, building a data analyst career path often becomes critical. It demands attentive learning of analytics tools with practical work experience.

Yet, many experts still feel the gap when switching their careers to the analytics field. It happens due to a lack of awareness of a wise step toward shaping a career in data analytics.

This blog provides proven facts that you must know to start, grow, and succeed in a data analyst career.

A step-by-step guide to data analyst career path

A way to career growth depends on the essential elements that help in foundation development. The data analyst career role is multifaceted yet has endless options for career shifts. Anyone who can diminish the complex boundaries can build a transforming career ahead.

How to become a data analyst?

Let us get through 5 relevant steps helpful for a data analyst career.

Step 1: Mastering the Essentials: Technical and Soft Skills

For success in data analytics careers, you must develop both technical knowledge and soft skills. Here is an effective roadmap to acquiring these essential data analytics skills:

  • Technical Skills:

Applied Math and Statistics: For complex datasets to be deciphered successfully, having an in-depth knowledge of probability theory, hypothesis testing, and statistical functions are indispensable tools for decoding complex datasets.

Programming Experience: Python is the premier data analyst language. Develop this skill along with Numpy and Pandas libraries for data manipulation and Matplotlib visualization tools to further your data analyst capabilities.

Understanding Machine Learning Fundamentals: Understanding machine learning concepts allows you to process complex data sets and make predictions more accurately.

Expertise in Data Analytics Tools: Knowing how to use tools such as SQL, Power BI, Big Data platforms, and time series analysis is integral for collecting, processing, and visualizing data effectively.

  • Soft Skills:

Communication and Presentation: Transform data into actionable insights with effective communication and presentation skills that effectively convey findings to non-technical stakeholders.

Problem Solving and Critical Thinking: Conquer complex, unstructured problems by developing problem-solving and critical thinking abilities.

Interpersonal Skills: Leverage the power of team collaboration for maximum data analytics success.

Success in data analytics requires mastery of both technical and soft analytics skills. Being adept at these essentials will allow you to thrive in today's data-driven world and contribute meaningfully towards the success of your organization.

Step 2: Verify the checklist of requirements if you want to qualify for the role

The first and foremost need for a data analyst career is to have a graduation degree in any domain. Holding good academics can streamline your success in a growing analyst field. Your substantial investment into 3-4 years of graduate education in any stream holds a good place in career shifts. Knowledge of fundamental data analyst skills and concepts leverages expertise, chasing the way toward a stronger job role.

Step 3: Practice in real-time

Pursuing a career in data analytics becomes difficult with basic knowledge, a bachelor’s degree, and skills learning. Having practical hands-on experience is essential for building a data analytics roadmap. Hence, joining an industry-proven course program gives you the scope to work on real-time projects in your chosen domain. Capstone projects upskill your learning and elevate the chances of career shifts. The best is to look for courses with simulated real-time projects. For self-practice, you can scroll through KDNuget, Kaggle, Github, and Buzzfeed.

Step 4: Upgrade the portfolio with competent skills

Employers need to go through the work portfolios of the candidates to hire them for the desired job positions. Essential technical & soft skills and real-time projects handled must be mentioned in the portfolio before applying for the job role. Your portfolio speaks to the real-time experience that you hold and your unique skills. The latest portfolio reflects the scope of career growth and hence must highlight industry-specific skills and expertise.

Step 5: With job-ready assistance, start applying for jobs

The last step to the data analysis roadmap is to direct you toward applying for industry-specific jobs. Professional grooming and mock interviews prepare the experts for actual job interviews. The data analyst career path reaches its destination when you have the right skills, experience, and confidence.

Mock interview sessions and preparation assist resume building that opens the door toward career success. Does a compelling resume help you get selected for MNC jobs? Yes, it does help. Having applied for the right job role at the right time can land you in the analytics industry.

Growth levels in the data analytics field

Leveling up your career with demanding job titles can land you in prominent job positions across the MNCs. A data analyst career path is becoming popular since businesses depend upon analytics for insightful decisions. Focusing on just getting a data analyst job can’t make your career secure. Instead, it needs close attention to have continuous career growth.

The tools and algorithms that come under data analytics certification help build a career in this field. The skills and expertise support data exploration and analysis, which makes the data analyst career lucrative. Here, entry-level jobs can be the first ladder in the growth journey. With minimum or no experience in the data analytics field, you may join as a junior analyst.

Your career in data analytics may go through several stages that bring job roles as:-

  • Analysts (with different levels of hierarchy)
  • Manager level (analyst manager and related roles)
  • Specialist level (analysts with specific domain choices or expertise)
  • Consultant (with years of experience and advisory skills developed)

A data analyst career can see growth since the volume of complex datasets is increasing. Many MNCs and MAANG partners are looking forward to data analyst career roles since they bring tremendous value to business improvements. Hence, it’s only you who can make a decision and take a wise step toward the role.

Check Out This Blog: The Future of Data Analytics Career

What does a successful career in data analytics look like?

A successful career in data analytics brings infinite prospects for growth. Rejections are part of the career change journey, but the one with updated skills and expertise can conquer success. Continuous refinements of the skills can justify success.

A successful data analyst cracks leading job vacancies and gets better hikes and promotions. We notice success in the form of job designation and salary package. The data analytics roadmap carries many job titles with attractive salary packages.

A salary range for data analysts ranges between ₹4.1 LPA to ₹12 LPA. Yet, a unique skill set and work experience further help in deciding the package.

Therefore, having strong preparation and a progressive learning methodology with a Data Analytics Course becomes crucial to a career perspective. An industry-paced course in the field can help you build an inspiring career in analytics.

To ease the understanding I have added a few aspirant personas below. These are created from real-life example analysis.

1. Pooja's Journey as a Data-Driven Marketer:

Pooja recognized the potential of data analytics within marketing. To take full advantage of it, she took an in-depth approach, emphasizing communication and problem-solving soft skills as well as enrolling in a data analytics course that taught her to utilize tools like Power BI for data-driven marketing strategies - leading her to create campaigns with increased ROI due to her data analytics expertise.

2. Divin's Journey From Analyst to Consultant:

Starting as a data analyst, Divin gradually developed his abilities over time, becoming proficient in machine learning and predictive analysis while working on various projects. Following this success, he eventually transitioned to becoming a data analytics consultant where he advises businesses on data-driven strategies and decisions - his journey epitomizing the opportunities afforded to data analytics specialists today.

These real-life examples demonstrate the diversity of data analyst careers. No matter your background, with dedication and the right skills you can forge an illustrious path in data analytics. By learning from past experiences you gain an appreciation of all its opportunities.

Mark your success with an industry-paced data analytics course program.

Data Analytics Program proves to be a yardstick of career growth for entry-level and mid-career experts. Having at least one year of experience, a career in the data analytics field is possible. Industry-proven course modules in data analytics support your dream career. Capstone projects with your preferred domain electives, this program opens the way toward never-ending success.

Build a lucrative career in data analytics

Data analyst career is flourishing around. Not every professional wishes to limit their career roles to manager positions or specific IT/non-IT designations. In the data-driven world, many new job titles and challenging yet interesting duties are emerging. Such industry shifts change the mindset of the people, which motivates them to crack challenging roles.

As mentioned above, Professional Courses like Data Analytics Programs can be your savior in the industry. The practical work experience during the course helps in gaining real-time knowledge. Plus, you also get a certificate from IBM after the completion of the course that supports career shifts.

Frequently Asked Questions

1. What is the amount of time needed to become a data analyst?

This depends on your learning process, the skills you have, and also data analysis roadmap you choose. Even if existing knowledge of fundamentals will help, gaining practical experience may take time. Yet, a minimum of 6 months is required to prepare yourself for a job in data analytics.

2. List down the essential skills that a data analyst must have.

Data analysts must try to develop both the soft and technical abilities demanded across the industry. Technical skills such as

  • Basic knowledge of applied statistics
  • Python Programming
  • ML fundamentals
  • Data analytics tools,
  • Advanced Excel

Plus, interpersonal abilities, critical thinking, and problem-solving skills are mandatorily required.

3. Can a non-programming professional become a data analyst?

Yes, anyone with basic knowledge of mathematics and statistics can kick-start his/her career in the data analytics field. Yet, to shape an industry-proven career in analytics, you must try to learn additional skills and programming languages. Plus, practical experience with industry projects is equally essential.

4. How to improve a data analyst career in the long run?

A data analyst career is a challenging field; hence, to strengthen your position in this field, you must stay updated with the latest trends and skills in demand. Plus, working on many industry projects will help you gain practical experience that will help you understand the real business world. This will help in long-term career growth.

5. What is the general career path to becoming a data analyst?

A data analyst goes through different positions that are set on a hierarchy. It starts with an entry-level analyst position, then leads to a senior analyst or manager, and ends with a CTO position. The future in the data analytics industry sees a rising trend. Yet, your skillset decides the speed of career growth in analytics.