The Myth, and What’s Actually True

Here’s the number that should end the debate: roughly 60 percent of active data analysts in India today come from non-IT backgrounds. Job postings for analyst roles overwhelmingly say “any graduate” rather than demanding a specific degree. No posting asks for a 90th percentile in mathematics. What they ask for is a set of tools, and those tools are taught from scratch to everyone, engineers included.

That last point matters more than it sounds. A B.Tech graduate doesn’t walk into an analyst role already knowing SQL or Power BI. Everyone starts at zero on the technical layer. What actually separates candidates is who builds a real portfolio of dashboards and projects, not which degree sits on their transcript.

Why Non-Engineering Graduates Sometimes Have the Advantage

This is the part most career guides skip entirely, and it’s the most important one. Commerce graduates already understand revenue, margins, cost structures, and profit and loss statements, the exact business context that turns a chart into an actual decision. An engineer can build a technically flawless dashboard that nobody in finance trusts, because they don’t understand what the numbers actually mean to the business. A commerce graduate builds a dashboard a finance director immediately acts on, because they already speak that language.

Arts and humanities graduates bring something equally valuable and often underestimated: structured reasoning and communication skill. A meaningful chunk of a data analyst’s actual job isn’t building the analysis, it’s explaining findings clearly to people who aren’t technical, and that skill doesn’t show up in a statistics textbook.

This isn’t a consolation prize for people who “couldn’t do engineering.” Recruiters in BFSI, consulting, and finance analytics increasingly prefer commerce-plus-analytics candidates over pure engineering graduates for exactly this reason, because domain understanding is harder to teach than SQL is.

What You Actually Need to Learn

The technical layer for entry-level analytics work is smaller than most people assume, and none of it requires a computer science degree to pick up.

Advanced Excel comes first, pivot tables, XLOOKUP, conditional formatting, and data cleaning, since a large share of real business analysis still runs through spreadsheets. SQL comes next, the language used to pull and organize data from databases, genuinely learnable in a matter of weeks with consistent practice. A visualization tool like Power BI or Tableau turns raw numbers into the dashboards that non-technical stakeholders actually look at. Basic Python is optional at the entry level but becomes valuable within a year or two, mainly for automating repetitive analysis rather than for anything resembling software engineering.

That’s the complete technical foundation for most entry-level analyst roles. Coding, in the traditional engineering sense, simply isn’t required to start.

What the Job Actually Looks Like

Roles vary by how business-facing versus technical they lean. A Business Analyst or Financial Analyst role suits commerce and finance graduates especially well, translating data into recommendations tied directly to revenue, cost, or operational decisions. A Marketing Analyst role fits naturally for graduates who understand consumer behaviour and campaign performance. Operations Analytics roles reward people who understand supply chains, logistics, or process efficiency, regardless of their original degree. As experience builds, many non-engineering analysts move toward specialized domain analytics, healthcare, HR, or a specific industry vertical, where their business background becomes a genuine competitive edge over generalist technical candidates.

The Numbers Worth Knowing

India’s analytics market is projected to grow from roughly $3.5 billion in 2024 to more than $21 billion by 2030, and data roles rank among the fastest-growing job categories globally according to the World Economic Forum. Entry-level analyst salaries in India typically start between ₹3.5 and 6 LPA, with professionals who add SQL or Python to a no-code foundation after a year or two often seeing 30-50 percent salary jumps. Major employers span e-commerce platforms like Flipkart and Meesho, fintech companies like Razorpay and Paytm, and established banks with dedicated analytics teams, alongside global MNCs and consulting firms building out data functions across nearly every industry.

Should You Get a Master’s Degree First

Generally, no, at least not purely to break into an entry-level analyst role. Employers weight a real project portfolio and demonstrated tool proficiency far above an additional degree at the entry level. A structured analytics programme combined with genuine project work, five or six real dashboards built on actual business questions, typically opens more doors faster than two additional years in a classroom. A postgraduate qualification like an MBA becomes more relevant later, for leadership or highly specialized analytics roles, but it isn’t the gate you need to pass through to get started.

Getting Started

If you’re a commerce, arts, or business graduate wondering whether this field is actually open to you, the honest answer is yes, and the data backs that up more strongly than most people expect. The real work is building the technical layer, Excel, SQL, and a visualization tool, on top of the business understanding you’ve already spent years developing. That combination, not an engineering degree, is what most Indian employers are actually hiring for in 2026.

KVELL’s M.Sc. in Data Analytics for Business Economics is built specifically for graduates from non-engineering backgrounds, including Commerce, Economics, and related disciplines, combining data science fundamentals with the business context that makes an analyst’s work genuinely useful to the organizations hiring them.