Business to Bytes: Chantanee Manonom’s Data Analyst Journey in Tech

Business to bytes Chantanee Manonom's data analyst journey in tech

Stay Informed With Our Weekly Newsletter

Receive crucial updates on the ever-evolving landscape of technology and innovation.

By clicking 'Sign Up', I acknowledge that my information will be used in accordance with the Institute of Data's Privacy Policy.

Chantanee Manonom is a determined individual who continuously seeks to improve her skills and achieve her career goals.

She started her academic journey at Chulalongkorn University, where she obtained a Bachelor of Science in Biology.

However, she soon shifted her focus to business. She earned a certification as a Master of Applied Commerce (Business Analysis & Systems) from the University of Melbourne and a Master of Business (Enterprise Resource Planning Systems) from Victoria University.

After working in the business industry for 11 years, she decided to pursue a career in Data Science & AI and successfully completed the Institute of Data course.

We recently spoke with Chantanee to congratulate her on her new role as a data analyst and learn more about her journey from making the decision to enter the tech industry to landing her first role after completing the course.

1. Why did you choose to pursue a career in tech?

Prior to my interest in data science, I worked as a consultant and business analyst in the human resources information system (HRIS) field. 

I specialised in supporting multinational corporations (MNCs) with system applications and products (SAP), human resources (HR), and SuccessFactors systems. 

I spent over 11 years in these roles before I decided to pursue a career change into data science. 

Many of the professional activities in my previous role were similar to what I could expect in data science, which made it easier for me to adapt my mindset and cultivate an interest. 

These activities included troubleshooting, system configurations, system implementations, business requirement gathering, and as-is vs to-be analysis.

2. How did the career consultation with the course advisor help you in your professional goals?

My session with course advisor Dynah was beneficial and reassuring. She provided me with valuable insights about the course, such as the success stories of other candidates and possible obstacles I may encounter. 

I had a clearer understanding of the course and industry outlook, and I felt ready to embark on my new career and enrolled in the boot camp.

3. What were the course’s most engaging and challenging aspects?

The best parts of the course were the class presentations and the discussions all the students would have amongst themselves and with the trainers. It helped with sharing ideas and different outlooks for approaching the same problem.

During the discussions, I was able to improve my soft skills by exchanging ideas and receiving constructive criticism from my peers who shared similar interests. 

The most challenging aspect of my new role was the transition to creating new programs from scratch, which was unlike my previous experiences, which focused more on troubleshooting. 

I had to adapt to this change and brush up on my mathematical concepts while also learning Python.

4. How did your trainer assist you in the upskilling journey?

I was fortunate to have a wonderful trainer named Mahesh, who has been incredibly helpful throughout my course and continues to offer me valuable professional advice.

During our academic interactions, he shared his personal journey with me and took the time to understand my background and industry insights, providing me with useful career guidance. 

Mahesh also taught me the importance of staying curious in my profession and taking calculated risks.

5. What was your process for finding the focus for your final capstone project?

It was quite a journey to find the focus for my capstone project. Initially, I had the idea to work on “anything,” but that felt overwhelming, and I struggled to decide on a specific topic to approach.

However, Mahesh taught our class an interesting approach, where we started by picking three initial topics: easy, realistic, and extreme. This helped us narrow down from initial ideas to the concepts we would finally use. 

Drawing from my experience in human resources projects, I was able to choose a topic that resonated with me professionally. 

This aided me in developing a concept that I could relate to and work on effectively. 

I was able to frame the problem correctly and narrow it down to identify the best approach. 

6. How did you approach the capstone project?

Working on the ‘capstone project’ was both challenging and fun. It served as a ride down memory lane for me since I had worked on a similar project during my graduate school years.

In light of the memories and lessons I had with my earlier attempt, I took the following steps:

  1. Join the capstone presentation of other cohorts.
  2. Start the preparation early so that there will be time for revisions.
  3. Practice a lot since practice makes perfect.
  4. Rest the day before the presentation.

7. How did the Institute of Data’s job outcome program help you with job hunting?

I felt that the job outcome program contributed as much towards getting me to my professional goals as the classes did. 

I was fortunate to work with an amazing team who patiently helped me build confidence in my career change. 

They provided me with personality profiling, career guidance, morale support, mock interviews, and assistance with salary negotiation. 

I landed my current role as a data analyst. Coincidentally, my current manager had also taken the same program, so the classes essentially served as my 6-month long interview!

8. What are the job responsibilities in your current profession, and what does a general day-to-day look like for you?

I am a data analyst at an information and communication technology (ICT) solutions and service provider called AsiaPac Technology. My main tool for work is Python. My job duties include analysing operational data to gain insights, improve operational efficiency, forecast demand, and perform natural language processing (NLP) analysis.

Other than that, I am involved in the tender preparation process for the data analysis aspect.

I occasionally evaluate new data-science-related tools, and for some assignments, I get to draw from my past experiences in business analysis and the human resources space.

9. What is your advice for someone with a non-IT background looking to upskill in data science?

Since the world and all its industries are rapidly changing, upskilling is inevitable. Of course, there is a certain learning curve students with non-IT backgrounds will experience during the career change.

Still, the end goal is reasonably achievable if they are committed, determined and thorough.

Business-process knowledge is infinitely more important than technical skills.

It is also essential to always stay curious, open-minded, and willing to learn.

If you are looking to pick up skills for the start of your journey, product demo sessions and literature reviews are excellent starting points.

On the other hand, meetups and conventions are perfect if you wish to get connected, inspired and exposed to new trends.


If you are considering a career transition into data science and pursuing your dream job, consider booking a free career consultation with one of our course advisors to build a roadmap that will get you on the path towards your goals. 

You can connect with Chantanee Manonom and follow her professional journey on LinkedIn.

Share This

Copy Link to Clipboard