This is a reference example from a real NTT DATA opening in October 2025 — likely no longer accepting applications. It’s kept here because the role comparison, day-to-day breakdown, and interview prep below are still accurate for this type of role at NTT DATA and similar companies. Check NTT DATA’s official careers page for current openings.
NTT DATA previously hired for Business Analyst and Data Analyst roles out of its Bangalore office, in the 5–10 LPA range, open to both freshers and experienced candidates. Here’s what this kind of role genuinely involves, what actually gets you shortlisted, and how to prepare — without the recruitment-brochure language most listings bury this in.
Business Analyst vs. Data Analyst — What’s Actually Different
The two titles get used almost interchangeably in job postings, but the day-to-day work does differ, even at the same company. A Business Analyst is essentially a translator — they sit with stakeholders, figure out what the actual business problem is, and turn that into requirements a technical team can build against. A Data Analyst is more of an investigator — they go into the data itself, clean it, query it, and come back with evidence that answers a specific question.
| Business Analyst | Data Analyst |
|---|---|
| Gathers requirements from stakeholders | Extracts and cleans data from databases |
| Defines the “what” and “why” of a solution | Answers specific data-backed questions |
| Writes user stories and process documentation | Builds dashboards and statistical summaries |
| Core tool: JIRA/Confluence | Core tool: SQL + Power BI/Tableau |
At a company the size of NTT DATA, you’ll likely specialize in one, though the boundary blurs often — a BA who can write a decent SQL query is far more useful than one who can’t, and a DA who understands business context produces far more relevant analysis than one who only knows the data.
What a Realistic Day Looks Like
Mornings usually start with an Agile team stand-up, followed by writing or refining user stories in JIRA. Mid-morning tends to involve actual SQL work — pulling something specific like customer churn or sales data from a warehouse. Afternoons often mix a stakeholder meeting to align on a sprint’s goals with heads-down time building a dashboard in Power BI or Tableau, sometimes followed by presenting findings to a small panel of stakeholders. It’s a genuine mix of technical focus time and real conversation, not one or the other.
Skills That Actually Matter in the Interview
SQL is non-negotiable. You need to comfortably write queries involving joins, aggregations, and filtering — this gets tested directly in technical rounds, often as a live exercise rather than a multiple-choice question.
Data visualization matters almost as much — hands-on experience with Power BI or Tableau, specifically being able to build a dashboard that tells a clear story rather than just displaying numbers, is what separates candidates who can talk about tools from candidates who can actually use them.
Excel is still relevant, even at a company this size — pivot tables, XLOOKUP, and basic data modeling come up more often than people expect, especially for quick ad-hoc requests that don’t justify spinning up a full SQL query.
Basic statistics — mean, median, standard deviation, correlation vs. causation — matter more for the Data Analyst track specifically, since it’s what separates genuinely useful analysis from a chart that looks convincing but says nothing reliable.
On the soft-skills side, stakeholder management and clear communication carry real weight — you’ll regularly explain a technical finding to someone non-technical, and how well you do that is often judged as closely as your technical answers.
Building a Portfolio Without Corporate Experience
If you’re a fresher, the single most convincing thing you can bring to an interview is a capstone project: pick a public dataset (Kaggle and most government open-data portals are good sources), define a real business question, clean and analyze the data in SQL or Python, and build a dashboard in Tableau or Power BI presenting your findings. Document the whole process in a GitHub repo or a short write-up — a hiring manager learns more from seeing your actual work than from any list of tools on your resume.
If you’re coming in with prior experience, pick your two or three strongest projects and prepare to walk through them using the STAR method (Situation, Task, Action, Result) — with a clear emphasis on the actual business impact your analysis had, not just the technical steps you took.
What the Interview Process Tends to Look Like
Expect three stages: a short HR screening call covering background and compensation expectations, a technical round that includes live SQL work and a business case study (something like “why did user logins drop last quarter?” walked through out loud), and a final managerial/culture-fit conversation with behavioral questions about handling disagreements with stakeholders or past project challenges.
The case-study round is where most candidates either stand out or blend in — interviewers are watching how you structure your thinking out loud, not whether you land on a “correct” answer immediately.
Before you apply to similar roles
- Check NTT DATA’s own careers page directly for current openings — this specific listing is from October 2025 and is likely closed.
- Match your resume’s language to the actual job description — mention SQL, stakeholder management, and the specific visualization tool you know.
- Have one real project (even a self-built one) you can explain confidently for five minutes, including what you’d do differently now.
Written by Babu Addakula, Job Visit.
