Data-Driven Decisions: Explained Over a Drink

A few weeks back, over drinks with friends in Sydney, I was sitting back, holding a cold beer in my hand.

Ravan leaned over, grabbed another chilled bottle from the bucket, and offered it across the table. “Shivam, Have a beer with us.”

Shivam waved his hand dismissively, swirling the ice in his glass. “No way, yaar. Why would I switch to a light beer when I’m already drinking whiskey? Whiskey, vodka, brandy—that’s the real stuff. Beer won’t even hit the spot.”

Everyone around the table nodded in agreement. And on paper, they weren’t wrong. Beer typically sits around 4% to 5% alcohol, while whiskey sits way up at 40% to 42.8%.

Case closed, right?

I looked down at the bottle in my hand, turned to Shivam, and said, “Wait a minute. Let’s not close the case yet.”

The Question Nobody Was Asking

Everyone was comparing the percentage. Nobody was comparing the quantity.

Think about it. When you drink whiskey, how much do you actually pour? A peg is usually 30ml, sometimes 60ml if you’re generous. But when you drink beer, you are not sipping 30ml from a shot glass. You are opening a full bottle — 330ml, 500ml, sometimes 650ml.

So the real question is not “which drink has more alcohol in it.” The real question is “which drink puts more alcohol in you.”

And that, my friends, is where the data tells a completely different story.

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The Pressure Cooker Whistle: Explaining My New Job

I am writing this from thousands of feet above, on my way to Seattle for Confluent’s Global Kick Off 2026.

It’s been three months since I joined. Looking back, leaving my previous role wasn’t easy. I was comfortable. I knew Azure like the back of my hand. Moving here meant leaving that safety net for a completely new technology stack. I have always loved technology, and I learned everything put in front of me. But the biggest change isn’t just the tech—it’s how I explain my job.

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