Khushi's Jobaaj Learnings Review: From Project Coordinator to Data Analyst at Zeta Global

"My top priority was to get a job as a Data Analyst. So, I focused on the most relevant modules: Excel, SQL, and Tableau. I found that these three tools were enough for me to crack the job interviews." — Khushi

Khushi completed a Bachelor of Commerce and began her career as a Project Coordinator — running project management, database management, billing reconciliation, client escalations and SLA compliance. She took Jobaaj Learnings' Data and Business Analytics Program, deliberately narrowed her focus to three tools, and has joined Zeta Global as a Data Analyst.

If you are searching “is Jobaaj Learnings genuine”, “is Jobaaj real or fake” or “can a B.Com graduate become a data analyst”, note two things about this account. Khushi describes applying through Naukri, LinkedIn and company career portals herself — her advice is a job-search playbook, not a placement story. And she confirms that degree bias is real in some companies, while saying it is not universal. Read it alongside the other conversations in our Interview Series and the wider feedback on the reviews page.

Who Is Khushi? Project Coordination Before Analytics

Khushi completed a Bachelor of Commerce and started work as a Project Coordinator. Her responsibilities there are worth listing because they explain why the analytics move was a shorter step than it looks:

• Project management
• Database management
• Billing reconciliation
• Stakeholder and client management, including escalations on off-track projects
• SLA compliance

Database work and reconciliation are already data work — done in spreadsheets and under deadline pressure, without the job title. What she needed was the tooling and the vocabulary.

Her Strategy: Learn Three Tools, Not Everything

This is the most useful decision in Khushi's account, and it runs against how most people approach a broad syllabus:

"My top priority was to get a job as a Data Analyst. So, I focused on the most relevant modules: Excel, SQL, and Tableau. I found that these three tools were enough for me to crack the job interviews."

The evidence that it was the right call is in what she was actually asked. Her Zeta Global interview covered Excel, Advanced Excel, SQL and Tableau — precisely the three she prioritised. She did not need breadth; she needed depth in the tools the job listings named.

On Degree Bias: Her Honest Answer

Asked directly whether her B.Com background hurt her in interviews, Khushi did not give the reassuring answer:

"Maybe in a few companies in the beginning. Some might prefer B.Tech candidates. But not all companies do. Many value skills over degrees. You just have to find the right companies and keep applying."

That is a more useful answer than “degrees don't matter.” Some doors were closed to her. The strategy that worked was volume and targeting — finding the companies that hire on skill and continuing to apply.

Her broader view on what a degree gives you: “college helps us develop our communication and presentation skills. After that, it's about the direction we choose.”

How She Actually Got the Job

Khushi's job-search method is the most detailed in this series, and it is entirely self-directed:

• Naukri and LinkedIn for volume.
• Company career portals directly — her reasoning: “Applying through the company's own website often reduces competition.”
• Referrals on LinkedIn — but requested properly, which is the part most candidates get wrong.

How to Ask for a Referral, According to Khushi

"Don't just ask, 'Do you have openings?' Instead, share the job link and your resume with the person. Make it easy for them to help you."

The difference is workload. A vague enquiry asks a stranger to do research on your behalf. A specific one — here is the role, here is my CV — asks for thirty seconds.

Resume Optimisation: The Lever She Rates Highest

Asked what matters most in the application process — resume, job platform optimisation, or interview prep — Khushi picks one:

"Everything matters, but resume optimization is key. Your resume should be customized for each role. For example, if you're applying to a data role in investment banking, use relevant terminology. Also, make your resume ATS-friendly so recruiters can find you easily on job platforms."

Two distinct points there, both worth acting on:

• Customise per role, including domain vocabulary — a data role in finance and a data role in retail want different words.
• Be findable. An ATS-friendly resume is not just about passing a filter; it is about surfacing in recruiter searches on job platforms.

Why Projects Matter

Khushi's view on portfolio work is short and practical: “Projects are super important. They give you a near real-world experience and show how things work in companies. Most importantly, they help you market yourself better to recruiters.”

The framing to take from that is the last clause. Projects are not only learning — they are the evidence that the tools on your resume are real.

The Outcome: Data Analyst at Zeta Global

Pros and Cons, Based on Khushi's Account

What worked:

• Focused depth in Excel, SQL and Tableau, which matched exactly what she was interviewed on
• Live sessions with real-life case studies, and mentors who answered questions about switching from non-technical backgrounds
• Project work she could point recruiters to
• A move from project coordination into a named data analyst role

What her account shows honestly:

• She found and applied for the job herself, across three channels.
• Some companies preferred B.Tech candidates — the degree did close some doors.
• She was still in Zeta's own training phase when this was recorded, so the role is at an early stage.
• The transition was overwhelming at first — she describes technical terms and coding logic as difficult early on.
• No salary is disclosed and no rating was asked for.

Data Analyst Interview Questions and Model Answers

What are your strongest tools in data analytics?

Answer: Excel, SQL and Tableau. In Excel, pivot tables, VLOOKUP, INDEX-MATCH and data cleaning. In SQL, joins, aggregations, subqueries and window functions. Tableau for the visualisation layer — dashboards that communicate the finding rather than just displaying the data.

How would you clean messy data in Excel?

Answer: Scan first for the usual failures — blanks, duplicates, inconsistent formatting. Then TRIM and CLEAN to standardise text, IFERROR to stop broken formulas propagating, and TEXT to normalise formats. Data validation prevents the next round of mess, and a pivot table is the fastest way to spot outliers and gaps before you start analysing.

What kind of SQL queries have you written?

Answer: Joins across tables, filtering with WHERE and HAVING, aggregates like SUM and COUNT, subqueries, and window functions such as RANK and ROW_NUMBER. In practice these came together on problems like ranking products by sales within each region.

Describe a project from your training.

Answer: A retail dataset analysed across regions and time periods — SQL to extract metrics like top-selling products and monthly revenue, Excel for the initial cleaning and formatting, and Tableau for an interactive dashboard of sales performance and trends. It covered the full pipeline rather than one stage of it.

How do you meet deadlines and maintain quality?

Answer: That comes from project coordination rather than analytics — break large tasks into milestones, prioritise by deadline, and review at each step. On the data side specifically, validate results against business logic rather than trusting the query, and document each step so the work can be checked by someone else.

How would you explain a complex dataset to a non-technical stakeholder?

Answer: Lead with the insight and its business impact, supported by a visual. Not “I used SQL joins” but “I combined the sales and customer data to identify the high-value clients by region.” Same work, described in terms of what it lets them decide.

What was hard about switching from a non-technical background?

Answer: The technical vocabulary and coding logic were overwhelming at first. Structured learning, practical assignments and repetition fixed it gradually — and mentor support in live sessions helped most with the confidence rather than the content.

Khushi's Advice for Learners Starting Out

• Be consistent. Her core message: “Even during festivals or if you're unwell, try to spend at least 1–2 hours daily on your skills and job prep.”
• Specialise rather than covering everything. Three tools, learned properly, cleared her interviews.
• Customise your resume per role, and make it ATS-friendly so recruiters can find you.
• Apply through company career portals as well as job boards — less competition on the same role.
• Ask for referrals properly. Send the job link and your resume; do not ask people to go looking on your behalf.
• Keep applying past the rejections. Some companies prefer B.Tech candidates; the answer is finding the ones that do not.

Full Podcast Transcript

The complete conversation, unedited.

Frequently Asked Questions

Is Jobaaj Learnings genuine, or is it fake?

This page documents one recorded case: Khushi, a B.Com graduate and former project coordinator, who focused on Excel, SQL and Tableau and joined Zeta Global as a Data Analyst. She names her employer and the tools she was interviewed on. She also describes applying through job platforms and career portals herself. See the wider review set on the reviews page.

Which tools do you actually need for a data analyst job?

On Khushi's evidence, three: Excel (including advanced), SQL and Tableau. Those are what she focused on and what her Zeta Global interview covered.

Does a B.Com degree hold you back in data analytics?

Partly. Khushi says some companies preferred B.Tech candidates, especially early in her search — but many valued skills over the degree. Her answer was to target those companies and keep applying.

How should you ask for a referral on LinkedIn?

Her method: send the specific job link and your resume rather than asking whether someone has openings. Make the request take the other person thirty seconds, not thirty minutes.

What matters most in a job application?

Resume optimisation, in her view — customised for each role with the right domain vocabulary, and formatted to be ATS-friendly so recruiters can find you on job platforms.

How much time should you spend on job prep daily?

One to two hours, every day — including during festivals and when unwell. She names that consistency as what made the difference.