On paper it looks like a strange line: a BBA in Marketing Management, a PGDM in Marketing & Finance, internships running ad campaigns — and then, somehow, Power BI, SQL and Python. People ask how a marketer ended up in the data. The honest answer is that I never really left marketing. I just got obsessed with the part most people skip.
It started at the dinner table
I come from a business family. Growing up, “how’s the shop doing?” wasn’t small talk — it was the actual conversation. I got curious early, but not about advertising. I was curious about why some businesses grow and others don’t, and how the good decisions actually get made.
Marketing gave me the questions
My degrees and internships pointed me at marketing, and I loved the craft of it — SEO, paid ads, content, the whole game. But every campaign I ran left me with the same itch: okay, but how do we know? I’d present results and quietly wish I could stand behind the numbers with more than a screenshot.
Data gave me the answers
So I went looking. SQL first, to actually query the data instead of exporting it. Then Python, to clean and shape it. Then Power BI, to turn it into something a client could see and act on in ten seconds.
That combination — a marketer who’s just as comfortable in a Power BI model as in a content calendar — is the whole point. It’s not two careers. It’s one loop: research the data, build the strategy, run it, then measure and adjust.
Marketers who can read their own numbers are rare. Analysts who understand what the business actually needs are rare. Sitting in the overlap on purpose is the most useful thing I’ve done.
What’s next
More real projects, deeper models, and dashboards that don’t just look good but change a decision. If you want the technical origin stories, they’re here: how I learned SQL and how I learned Python.