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REQUIREMENT_ID_79 β€’ 3-DAY_ACTIVE_POLICY

Data Analyst – Fresher

Company
Company Vyaparapp
Type
Opportunity Type Internship
Salary
Stipend / Salary 6 LPA
Location
Location Bengaluru
Posted Date
Posted Date Yesterday
SQL Python Data Cleaning Data Transformation Power BI Tableau Excel Data Visualization Analytical Thinking Communication
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Aptitude Practice Questions Open Resource β†—
Helps you sharpen quantitative and logical reasoning skills essential for the online test at Vyapar.
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Company Interview Preparation Guide Open Resource β†—
Provides insights into common interview patterns and questions asked by Indian tech companies, useful for Vyapar's technical round.
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Comprehensive Interview Prep Resources Open Resource β†—
Covers a wide range of topics from data fundamentals to soft‑skill questions, aiding overall interview readiness.
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Algorithm & Data Structure Problem Set Open Resource β†—
Practicing these problems improves coding proficiency in Python, which is valuable for the technical assessment.

Graduates (B.Tech/B.E., B.Sc, B.Com, BBA) from any stream with a minimum of 60% aggregate. Final year students can also apply. No active backlogs at the time of joining. Batch years 2024‑2026 are preferred. Candidates should have a strong analytical mindset and basic knowledge of SQL or Python.

1
Round 1: Online Aptitude Test
2
Round 2: Technical Interview (SQL, Python, Data Visualization)
3
Round 3: HR Interview
Vyapar Apps Pvt. Ltd. is a fast‑growing Indian SaaS startup that empowers small and medium businesses with cloud‑based accounting, inventory, and invoicing solutions. Founded in 2015, the company has expanded its product suite to include point‑of‑sale, e‑commerce integrations, and analytics modules, serving over 1 million merchants across India. With a culture that encourages rapid learning, cross‑functional collaboration, and a strong focus on customer impact, Vyapar has consistently been recognized for its innovative product roadmap and employee‑first policies. The Data Analyst – Fresher role is designed for recent graduates who are passionate about turning raw data into actionable business insights. As a member of the analytics team, you will work closely with product, marketing, and sales stakeholders to ensure data quality, build visual dashboards, and support data‑driven decision making. This position offers a hands‑on environment where you will be mentored by senior analysts and get exposure to real‑world business problems from day one. Key responsibilities include: 1) Collecting and cleaning raw data from multiple sources such as databases, CSV files, and APIs. 2) Transforming data into structured formats suitable for analysis. 3) Performing exploratory data analysis on large datasets to uncover patterns and trends. 4) Designing and maintaining interactive dashboards using Power BI or Tableau. 5) Creating clear visualizations and reports that communicate insights to non‑technical audiences. 6) Supporting product, marketing, and sales teams with ad‑hoc analytical queries. 7) Preparing periodic analytical reports for senior leadership. 8) Presenting findings and recommendations to internal stakeholders. 9) Collaborating with the technology team to ensure data pipelines are reliable. 10) Upholding data integrity and quality standards throughout the lifecycle. The tech stack primarily involves SQL for data extraction, Python (pandas, numpy) for data manipulation, and visualization tools like Power BI/Tableau. As you grow, you can progress to senior analyst, analytics lead, or product analytics manager roles, with opportunities to specialize in machine learning or business intelligence strategy. Joining Vyapar means being part of a vibrant, inclusive team that values continuous learning, offers flexible work‑from‑office arrangements, and provides a clear career trajectory for ambitious freshers.

Vyaparapp β€” Data Analytics & SQL Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC πŸ“–
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

Open Resource β†—
COMPANY GUIDE 🎯
Vyaparapp Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Vyaparapp and off-campus tech roles.

Open Resource β†—
MOCK TESTS & PAPERS πŸ“
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource β†—
CODING PRACTICE πŸ’»
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource β†—
Round 1: Online Assessment (OA)
Aptitude, Quantitative Logic & 2 Coding Problems
Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1
Core Tech Stack (SQL, Python, Data Cleaning, Data Transformation, Power BI, Tableau, Excel, Data Visualization, Analytical Thinking, Communication) & Live Code Tracing
Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving
Database Schemas, APIs & Architecture Basics
Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion
Vyaparapp Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
What is the difference between WHERE and HAVING clauses in SQL? Answer β–Ό
Model Answer: WHERE filters rows before any groupings are applied, while HAVING filters aggregated groups after GROUP BY has executed.
Explain SQL Window functions: ROW_NUMBER(), RANK(), and DENSE_RANK(). Answer β–Ό
Model Answer: ROW_NUMBER() assigns unique sequential integers. RANK() assigns identical ranks to ties and skips ranks. DENSE_RANK() assigns identical ranks to ties without skipping rank numbers.
How do you handle NULL and missing values during data cleaning in Python/Pandas? Answer β–Ό
Model Answer: Use .isna().sum() to identify missing values. Impute with mean/median using .fillna() or remove with .dropna(subset=[...]) depending on variance impact.
What is the difference between Star Schema and Snowflake Schema in Data Warehousing? Answer β–Ό
Model Answer: Star Schema has denormalized dimension tables directly connected to the central Fact table. Snowflake Schema normalizes dimension tables into sub-dimensions to minimize redundancy.
How do you calculate MoM (Month-over-Month) growth in SQL? Answer β–Ό
Model Answer: Use LAG(revenue, 1) OVER (ORDER BY month) to fetch the previous month's revenue and compute (revenue - prev_revenue) / prev_revenue * 100.
Why do you want to join Vyaparapp as a Data Analyst – Fresher?
Preparation Tip: Highlight Vyaparapp's market reputation, recent tech innovations, and how your skills in SQL directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Preparation Tip: Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

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