My Journey from a “don’t-know-what-to-be” Student to Becoming a Data Analyst at Blibli.com
Hi!
My name is Vincent. I recently graduated from one of the top universities in Indonesia, majoring in Computer Science. I write this post to share my personal experience of how I become a data analyst at one of Indonesia’s e-commerce companies, Blibli.com. Since this is just a personal experience and I believe everyone has their own story, I hope you can be motivated and inspired, as well as take the positive insights from my story.
My background
Before attending my university, I wasn’t exposed to coding or IT stuffs. Well, I used to join programming extracurriculars in my junior high school. I recalled that I wasn’t able to understand what “integer” was at that time HAHAHA. When I was in the last year of my senior high school, I knew that I would be choosing one of the universities in Indonesia, so I had been preparing for the Joint Entrance Selection of State Universities (or Indonesian students called it SBMPTN) exam although I hadn’t decided which major I would take. As a fun fact, I originally wanted to major in Architecture, but I decided to put Computer Science as the priority. Long short story, I took the exam and was accepted as a Computer Science student. Oh yes, my sweet and sour memory: I didn’t even dare to take a short nap because I was afraid of failing the exam, so I kept on studying until 11 PM every day, including weekends. Thanks a lot, it paid off.
My first & second year
All my courses were held under the Faculty of Mathematics and Natural Sciences. As someone who wasn’t exposed to programming at that time, I spent my time studying calculus. I love Calculus a lot. I used to spend an extra 1–2 hours a day reviewing the materials. One semester passed by, and I started to change my mind to focus more on coding. I noticed my friends were coding insanely and had showcased their projects to me. Uhm, I realized that investing my time to create project portfolios could help me receive an internship easier. I tried web designing (Frontend and UI/UX), web development, and competitive programming, but I wasn’t captivated. Then, I embarked on another journey which was learning data science. It took a while to get a grip on how data science workflow was supposed to be and what essential skills were needed in this field of study. At that time, my learning resources were Youtube videos and Google articles.
One day, I received a notification about an exclusive machine learning program, called Bangk!t Academy — a soft-skill and hard-skill (focusing on machine learning, especially deep learning) led by Google, Gojek & Tokopedia (GoTo), and Traveloka. It was the very first batch of the program. I remembered that one of my major’s colleagues also joined and we were considered to be the youngest students (in terms of the educational year, not by age) to receive the opportunity. We were in the same class as our seniors from various faculties and even master program students. It was an honor to be a part of the first batch and able to learn about deep learning from the amazing instructors. Today, Bangk!t Academy is part of Indonesia’s Kampus Merdeka program and has three learning paths — machine learning, mobile development, and cloud computing.
By the end of a semester, we usually had a short holiday. While other universities had almost two to three months of holiday, mine was about one to two months. It was pretty stressful to find a one-to-two-month internship because you would probably take the first month of your internship to get used to the systems, data, workflows, and environment. I also believed that I wasn’t skilled enough that my applications were rejected by several companies. So guess what? I didn’t land any internship until my third year, which was the fifth semester out of eight semesters in total. Something worse even happened, the pandemic forced my university to shift from offline learning to online learning.
Third & Fourth year — My Journey in Blibli’s FUTURE Program
There was a moment when I began to question myself, “Am I sure to continue my journey in Data Science? Should I try another different role?”. One of my random colleagues shared a poster about Blibli.com’s FUTURE Program. It is a program that offers extensive learning by joining boot camps and tackling real-life projects. I thought it was a convincing program to boost my career, so I chose the Data Track (the program offers various tracks such as Mobile Development, Software Engineering, Software Engineering in Test, Infrastructure, Data, and Quality Assurance).
Data Track covers the field of data engineering, data analysis, and data science. I was exposed to data science more than data analysis. Even data engineering was the field of study that I wanted to avoid the most. Well, I gave it a try and submitted my application. I would not lie about how serious Blibli’s were, scanning the applications and sending the assessment tests. If I was not mistaken, the assessment tests consisted of Aptitude Test, Psychological Test, HR Interview, Technical Interview, and Forum Group Discussion. It was like applying for a scholarship application, but seriously I enjoyed and got to know my capabilities from those assessments.
Tada! I passed the assessments and officially joined the program by the end of December 2020. I attended the soft-skill and hard-skill boot camps. When the boot camps ended, here we go… project. You can imagine the project as a combination of data engineering, data analysis, and data science. I will explain it in more detail below. Each of the members in my track was given a chance to request a mentoring session from a Data Engineer, Data Analyst, and Data Scientist (of course from Blibli’s). It was a nightmare because I had the mindset of “avoiding” data engineering the most, so it was pretty challenging for me to catch up at that moment.
The first project was analyzing e-commerce data.
- Data Engineering: Perform Extract-Transform-Load (ETL) to a database.
- Data Analysis: Create five business questions and answer those questions with data visualizations.
- Data Science: Train a supervised and an unsupervised learning model.
This e-commerce data was not real data, however, it was mapped so that it looked like real data. If you are interested in the project, you can check it out here — FUTURE first project.
After passing the first phase, the next was the second phase or the final phase. The boot camp’s materials especially the hard-skill courses were a bit complex but I managed to catch up after a couple of reviews. The second project was leveled up. This time, I was paired with one of my team members, and we dealt with real-life data.
The second project was analyzing text reviews on e-commerce apps.
- Data Engineering: Extract reviews from Google Play Store and Apple Store and Perform Extract-Transform-Load (ETL).
- Data Analysis: Create an interactive dashboard to present the findings.
- Data Science: Perform topic modeling to identify what topics are heavily mentioned in the text reviews.
If you are interested in the project, you can check it out here — FUTURE second project.
During the completion of these projects, I struggled a lot. There were moments I wanted to give up, but I kept holding on. I was confused about what steps I should take on next, tons of hidden-to-my-eyes errors, tight deadlines, and much more. I was ashamed of asking too much to my mentors because I didn’t want to look “bad” in front of them. But hey, they were here to help so I gathered up the courage and asked for recommendations from them. What I appreciated the most was that they, as the mentors, were willing to prioritize the best practices and shared that before suggesting a workaround to solve my issues. I believed I remembered the best practices shared more than the issues that ruined my sleep.
As I was not only exposed to data science during the program, I began to fall in love with data analysis. I was amazed by how powerful data could be used to draw insights and answer questions to drive data-driven decision-making. Since the program had ended, I kept on enhancing my skills in SQL and visualizations.
Back to academic life, the day I finished my undergraduate thesis had come — it was deep learning research HAHA. I would say that even though my interest has shifted from data science to data analysis, I will never forget data science. I have even been attracted to deep dive regarding data engineering especially in extracting data from certain sources, transforming it into a suit-your-need format, and loading it into a database for further use. Thanks, Airflow, I love you. However, I managed to become a Data Analyst as my first professional working role at Blibli.com!
Closing Statement
Fieeww! That summed up my journey from a “don’t-know-what-to-be” student to becoming a Data Analyst. I would like to thank you for reading up to this point. Before I end this story, here are the key takeaways:
- Don’t be afraid to try. Sometimes we have been worrying too much about something that probably will not happen. You will always learn something new from the decisions you’ve made.
- Environment matters. With whom you spend your journey together have an impact on your life. If you have supportive friends who share the same goals, create a group chat and keep in touch. Exchange useful information and help each other out.
- Never give up until the end. To be honest, I can’t even imagine where I am now if I gave up on my ongoing project. Sometimes, we are just too tired to receive anything more which made us exhausted mentally and emotionally. Take a break, for example sleeping, playing pokemon games (I LOVE POKEMON), listening to BTS or Blackpink’s songs, swimming, reading, etc. Once you are feeling better, put your head up and go back on track. What if you are not feeling any better even after a break? I’ll seek help from someone :).
- Seek help from someone. Some people prefer to keep everything themselves. I am not that kind of person. I have been reaching out to several people I believe are willing to listen to my story and provide meaningful feedback to me. If you don’t have someone in mind, you can find one on LinkedIn. Try to connect with that person and ask him/her if he/she is willing to free some time to listen to your concerns. I can also be your loyal listener so feel free to reach out on LinkedIn :))))). Anyways, there are tons of online mentoring programs nowadays. You can find one here too.
- Try something new a.k.a keep learning. The reason why I wanted to avoid data engineering at that time because I was never intended to become a data engineer. I gradually shifted (not completely) from a fixed mindset to a growth mindset. Having a growth mindset made me value all my efforts, even the smallest ones.
- Always appreciate yourself. Don’t be too harsh on yourself. Enjoy what makes you happy and always do your best.
That’s all I can share. I hope there is something positive you can implement in your daily life. I would like to apologize if you find anything disturbing or the use of unpleasing words. Also, don’t forget to check out Blibli.com’s Career Page if you are interested in joining Blibli! Thank you and see you on the next posts :D.
