The Bangalore approach: unstructured elegance of Data Analytics
The Bangalore approach: unstructured elegance of Data Analytics
Drawing parallels between city planning and the flow of analytics projects,
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I have been living in Gurgaon (or Gurugram) for more than a month now. Before that, I lived for almost 18 months in Bangalore. Both cities have their own unique characteristics, and my experiences in these cities have led me to draw parallels with the flow of a data analytics project.
Gurgaon, for example, is a planned city. Real estate giants DLF have built this city and changed the complete landscape of this place. The road connectivity is great, there is a metro that connects you to New Delhi and the rest of NCR. You’ll get an auto or a cab in 2 mins, which felt like a dream in Bangalore. You have office buildings all over the place and residential areas that are also well-planned and executed. However, it can get tiring here if you are not a “mall” person. Except for some big posh malls, there is hardly anything to do.
On the other hand, Bangalore is a classic Indian city. It felt lively and bustling with activity. Yes, you may indeed have to wait for 40 minutes to get a cab sometimes, and travelling 6kms would often take like 45 mins in the morning peak hour. But at the same time, you would feel like you’re surrounded by people and communities, unlike Gurgaon.
One thing about Bangalore is that there was a lot of exploration and then exploitation especially when it came to metro projects and bridges. You may encounter a random pillar that was meant for metro but it never saw the light of the day. This is unexpected in Gurgaon. You’ll never see that.
While having my morning coffee today, I had a realization. The flow of a data analytics project should ideally be like Bangalore and not Gurgaon. If you’re working on an analytics project with a JIRA agile project management tool and whatnot, you can end up finishing the project in time but you’ll limit the analytical capabilities if the work and timelines are too constrained.
A project in analytics should be like Bangalore. You have to dig a pothole, start building some pillars here and there (explore a lot of different angles and play around with the data) and then abandon some of them, and take a different direction (exploit when you have sufficient info).
Another thing about these projects is time boundaries. If I am supposed to work for x hours over y days, I will end up working x(±2-3) hours over that period of time but every day I won’t work for x/y hours. That is also what I have felt has been crucial in completing my projects. Data analytics projects require critical thinking, especially if you’re an individual contributor. And sometimes they need some time so that it comes to you. Some of my great ideas never came to me while I was sitting at my desk. But it came when I was taking a walk near Howrah bridge or went for a run on 80 feet road in Indiranagar.
In conclusion, while deadlines are important, there should be a free flow while you embark on the journey of reaching the deadline. The flow of an analytics project should be like Bangalore - unstructured but elegant.
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