Working on a new project as a Data Science Trainee, going over the project I realized that there were many similar aspects shared between Rocketry and Data Science. This singular thought made me reminisce about my college days. My mind drifted from the project and I was back to my sophomore year in college. A Mechanical Engineering student who was passionate about rocketry and robotics.
Through my years in college, I participated in a number of intercollegiate activities involving Robowars, Model rocket launching, and Building Arduino RC cars. My experiences in these various events, without my knowledge, were now helping me as a Data Scientist. There were a few points that really stood out to me which I am stating below:
Always think about the larger picture:
My team and I had decided to take part in one of the intercollegiate rocketry tournament held at New Mexico, USA. While building our rocket we decided to divide the work by creating 5 sub-assemblies for the project. This helped us ease the workload on everyone. Although each of the individual components was made perfectly, upon assembling all the parts together we noticed some assemblies were slightly misaligned in the rocket. This made us change a majority of the structural part of the assembly in order to obtain the perfect fit. A small oversight led to a major blunder costing us valuable resources and time. In hindsight, the one major flaw in our plan was we all focused on our own individual work. We did not look at the bigger picture. This one mistake taught my team and I a very important lesson. – Always take a step back and look at the bigger picture
Attention to Detail:
In the Robowars VJTI Mumbai competition, our bot had been performing really well in the previous matches and we had had the confidence to win the whole competition. Pumped with the excitement of winning the preceding matches we entered the semi-finals match. The match was going according to our expectations until we got a short hit from the opponent’s bot and our bot got stuck on a protrusion from the wall. This rendered our bot immobile even though all our assemblies were working just fine. The main aim of the competition is to make the opponents’ bot immobile and our opponents achieved this. On our post-match analysis, we realized why our bot got stuck on the wall. It was due to outer body bolts we had used. We then changed all the outer body bolts to countersunk bolts. This not only taught us about focusing on the details of the design but also understanding the various outcomes possible because of just one oversight.
Assigning work through expertise:
Understanding the team’s abilities (Individually and together) will help you define all the sub-parts of your project. Getting to know the abilities of your colleagues will be easier at the time of redistributing your work. Data science students or coders would relate to this immediately, as it’s often very hard to understand the code or work done by your co-worker. There were similar problems that I faced back in my days of engineering. There were always a few people in our team who couldn’t come at the site of the competition. Understanding their work in order to solve the related issue was one of the most challenging things we needed to face on the competition site.
A clear cut process flow for project management:
Rocketry like Data Science has a very complex workflow. While participating in the Intercollegiate Rocket Engineering Competition (IREC). It was the flagship event held at Spaceport America, organized by ESRA (Experimental Sounding Rocket Association). My team and I worked on the design of the project but missed assigning the workflow from the project which led to 2 teams creating the exo-structure and the recovery mechanism of the rocket while no one worked on integrating the GPS model into the recovery mechanism of the rocket. Clearly defining the workflow is an integral part of any project which was made abundantly clear to us.
Time management is crucial for all projects. This point may seem obvious to most, but trust me, its importance cannot be overstated. While participating in our Indian intercollegiate Robowar competitions, we faced a huge predicament. Our bot through the series of matches had accumulated a lot of damage. The majority of the free time we had between the matches were spent on repairing our bot. This was very unprecedented because we had not planned for this. This left us little time to properly strategize for our upcoming matches and to analyze our opponent’s bot beforehand. Correctly allocating time for each process was very essential which we could not do. We learned from this mistake and rectified this when we represented India in the FMB (Robowars) world cup held in Jiaxing.
Always have a plan B:
A very simple suggestion but it makes a world of difference in every project. While competing in FMB (Robot Wars) semi-finals we ran into a major setback. In the previous matches, our bot had taken some heavy damage and needed urgent repair for the upcoming match in the finals. Due to various circumstances, we were not able to bring spare parts for our bot to the tournament. We had decided to purchase the spare parts at the local shops but on visiting the shops we realized that the parts needed were not available. Adding this to the language barrier we were in a dire situation. To our surprise, we were helped by one of the sponsorers of the team we had just defeated. He helped us procure the parts we needed and also helped us with all the repair work. This helped us win the FMB tournament making us the first Indian team to win the FMB World cup in 60 kg category. This incident always reminds me of the importance of a plan B.
After graduation, I was looking at the most upcoming fields in the world and what struck me as the most interesting was data science. Data Science encapsulated a variety of fields including manufacturing for IoT, Healthcare, Financial Services and many more. I was fascinated and enthralled by it. While searching for companies specializing in data science, I chanced upon Ellicium Solutions, a Big Data, Analytics, and Artificial Intelligence. Ellicium is one of the most upcoming companies in the field of Data Science.
I got an opportunity to join Ellicium solutions and now as a Data Science trainee at Ellicium, I am learning so much. Often I realize while working that I use a lot of my learnings as a rocketry competitor in my everyday life as a data science trainee.