Journey transition from android developer to data analyst

My passion for coding begin in 2nd year of my B.Tech.
I spent my entire college time doing Android development and knew no other languages other than Java and Kotlin.
I was very attached to creating apps and used to participate in all kinds of events, hackathons, and tech fests, and a few internships.

But when campus placements came into the picture, there were very few companies who were coming for app developer roles, and I was scared I won’t get any job. I faced a dilemma –the fear kicked in to as I took an education loan, I wanted to have at least one offer letter as backup.

I took a leap of faith, landing a data analyst role despite no formal training. This article charts that journey — the self-taught tactics used, steep learning and lessons learned transforming into an analytics expert.

The campus placement season is both dream and dread. Securing a job was my priority. I had to expand my horizons, but had little exposure beyond mobile analyst positions. Data analytics was one the field which was booming which makes it intriguing yet intimidating.

I did doubted myself can I stretch beyond hard-coded software to extracting soft insights?

The trick I used then was whenever I used to sit in interviews for any kind of role, I used to turn my projects around that role.
So :
-> If the position was for a data analyst, I would present all of my observations from my apps as insights and improvements as decisions.

I explained how I:

• Collected user data to understand app usage
• Organized data to store properly in apps
• Analyzed data to improve app features
• Created data dashboards to track user engagement

-> if it was around software development: I used to explain my app architecture, how I built UI, frontend, backend ,UI/UX ,feedback , github and commencing new versions

I realized most recruiters had limited technical acumen to evaluate my hands-on skills. The advantage I had was that all my apps were published to the play store, I can walk them through different apps, complex data layers, features, cloud demonstrating I know what i do. This way they could try them out in front of their eyes and see the work beyond the interview discussion. Having a public profile or portfolio website is way to win recruiter’s heart.

Luckily, I got hired!
But the real challenge came after that: To learn the relevant skillset of the data domain. I felt clumsy as a beginner. But I tried my best to pick up new data skills through online courses. I asked senior analysts lots of questions. Within a few months, concepts like regression analysis and data visualization started making sense
-> Learning new skills takes courage and time, and from the start, it’s okay to have the awkwardness of not knowing how things work.
-> We function to seek comfort and avoid failure, I could have gone back to creating apps because that was comfortable for me but I realized career my lies with Data.
-> It may seem weird, but the earlier you fail, adjust, and try again, the faster you succeed. For that, self-awareness is important!

Always try to step outside of your comfort zone, work through your fears and keep going as you acquire each new skill, apply what you learn, and eventually, you’ll become a pro!