Shivangi’s Inspiring Journey as a Data Analyst

In a rapidly evolving job market, transitioning into data analytics can be challenging, but not impossible. Shivangi’s journey from a student at DataMites to securing not one, but receiving two job offers as a Data Analyst one from Bandy and Moot and another from Dilytics, is a testament to the power of structured learning, persistent practice, and guided mentorship through DataMites Institute. In this article, we explore her story in a question-answer format to help aspiring data analysts understand what it takes to break into the field successfully.

Shivangi’s career path for data analyst

From a determined learner to a successful data analyst career, Shivangi’s career path showcases how the right training into Top IT Courses and dedication can lead to impactful transformation in the data industry.

Q1: Can you tell us where you’ve been placed and how your journey started?

I recently got placed as a Data Analyst at Dilytics, and the journey began when I enrolled in the DataMites Certified Data Scientist (CDS) course in October 2023.

Q2: What was your experience like while learning at DataMites?

It was excellent! The structure was very systematic, starting with Python, then Statistics, followed by Machine Learning, SQL, and Power BI. Each module came with mini-projects which helped to apply theoretical concepts in a practical way. The instructors were knowledgeable and very helpful.

Q3: You mentioned you’re from a coding background. Did that help?

Yes, it helped, but Python was new to me. The DataMites teaching approach made learning Python and other technical topics like statistics and ML easier, especially with their hands-on style.

Q4: What motivated you to pursue a career in data analytics?

Initially, I wasn’t sure about which field to enter, but after research, I realized data science and analytics are booming. I loved the idea of transforming raw data into actionable insights.

Q5: How did you structure your study time during the course?

I studied around 2 hours every evening after class. I revised notes and practiced daily. After completing the course, I started working on external projects via YouTube, Kaggle, and additional mini-projects beyond the ones provided in class.

Q6: What online resources did you use apart from the course material?

• Python: CodeWithHarry
• SQL: TechTFQ YouTube channel
• ML: Krish Naik's videos
• Projects: Kaggle, Analytics Vidhya
• Practice Platforms: LeetCode, HackerRank
• Theory: Analytics Vidhya blogs

Q7: Tell us about your internship experience at Rubixe. Did it help in your placement?

Absolutely. I worked on five real-time projects including a Flight Fare Prediction model. The experience helped me confidently answer project-based questions in interviews.

Q8: How many mock interviews did you take, and how did they help?

I had three mock interviews. Each mock highlighted areas for improvement. Questions from these interviews actually appeared in my real interviews, which made a big difference in my confidence and performance.

Q9: What types of questions were asked during your real interviews?

Primarily project-based questions, logical scenarios, and concept applications in SQL and Python. In Power BI rounds, I was asked how to derive insights from visuals like pie charts. Some interviews also included in-depth questions on decorators and library functions in Python.

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Q10: How did you prepare specifically for interviews?

I used ChatGPT to generate topic-specific questions and practiced answers. Focused preparation on SQL, Python, and projects helped me stand out.

Q11: What skills do you believe are most crucial for a Data Analyst today?

• SQL: A must-have skill, often heavily tested.
• Power BI: For visualization and business insights.
• Excel: Foundation for BI tools.
• Project knowledge: Deep understanding of your portfolio projects.

For data science roles, Computer Vision and ML algorithms are also valuable.

Q12: Did your academic degree influence the hiring process?

No, not at all. Employers focused on my skills and project experience, not my degree. Even bachelor's degree holders with strong skills can get high-paying roles.

Q13: How was your resume prepared?

Initially, I created it myself. Post-mock interviews, the PAT team at DataMites reviewed and refined it, helping me highlight the right skills and projects effectively.

Q14: How many interviews did you attend before accepting this offer?

I cleared two interviews. I didn’t accept the first offer but joined the second one at Dalytics in Hyderabad.

Q15: How long did it take from course completion to placement?

I completed my internship by January 2024, and got placed by June 2024. So, roughly five months after finishing the internship.

Q16: Any advice for future aspirants?

• Master the basics: SQL, Python, and Excel.
• Build solid projects and understand them deeply.
• Practice mock interviews.
• Use online resources and platforms like Kaggle.
• Be consistent and stay motivated!

Key highlights from Shivangi’s journey

Shivangi’s journey from beginner to data analyst is a remarkable DataMites success story, offering valuable insights for anyone aspiring to build a thriving career in data analytics. Here are the top lessons from her experience:

1. Structured Learning Matters: DataMites’ step-by-step curriculum helped Shivangi grasp complex technical topics with clarity.
2. Real-World Internship Projects: Hands-on projects during her internship directly aligned with real interview scenarios.
3. Mock Interviews Build Confidence: Regular mock interviews helped identify improvement areas and boosted her confidence.
4. Supplement with Self-Study: Resources like YouTube, ChatGPT, LeetCode, and Kaggle played a key role in deepening her understanding.
5. Resume Assistance Was a Game-Changer: The PAT team helped her craft a resume that highlighted her strengths and stood out to recruiters.
6. Focus on Soft Skills: Communication and interview preparedness were just as critical as technical knowledge.
7. SQL and Power BI Dominate Interviews: These two tools were most frequently assessed in her technical rounds.
8. Skills Trump Degrees: In today’s job market, practical skills and project exposure hold more weight than academic backgrounds.

This transformative path is driven by inspiring DataMites success stories, where individuals from varied educational and professional backgrounds have transitioned into thriving careers in data-driven roles. Their achievements stem from a structured learning approach, practical project experience, and expert mentorship provided by the institute.

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Shivangi’s transformation through DataMites showcases how structured learning and hands-on training can turn beginners into skilled data analysts. Her journey underscores that with the right guidance and dedication, success in data analytics is achievable. With the global data analytics market projected to grow from USD 82.33 billion in 2025 to USD 345.30 billion by 2030 (Mordor Intelligence), the opportunities are immense.

Enrolling in an offline Data Analyst course in Mumbai, or in other emerging tech cities like Bangalore, Chennai, Coimbatore, Hyderabad, Ahmedabad, Delhi, Chandigarh, Jaipur, Kochi, and Pune, opens doors to real-time industry exposure, valuable networking, and rapid career advancement in data analytics and software development. 

DataMites Institute offers expert-led training in Data Science, AI, Machine Learning, Python, Data Analyst course with internships, Data Engineering, and IoT. With hands-on projects, internships, and placement support, learners gain real-world skills. The Certifications from IABAC and NASSCOM FutureSkills boost credibility and job readiness in the tech industry.

For aspiring data professionals, DataMites delivers specialized Data Analyst training in Hyderabad, along with centers in Bangalore, Kochi, Chennai, Pune, Coimbatore, Ahmedabad, Delhi, Chandigarh, Jaipur, and Mumbai, ensuring access to high-quality, industry-aligned education across India.