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Data Analyst

Lenskart Academy Tijara, Rajasthan, India

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Job Description

"Unlock your potential as a Data Analyst at Lenskart Academy and drive business growth through data-driven insights."

As a Data Analyst at Lenskart Academy, you will be responsible for extracting valuable insights from large datasets, creating actionable reports, and driving business decisions.

Whether you're new to the field or looking to take your skills to the next level, this role offers a unique opportunity to work with a leading eyewear brand and contribute to its growth and success.

Why you should learn this:

The demand for Data Analysts is on the rise, with a projected growth of 16% in the next 5 years, according to industry reports.

Expected Salary: The average salary for a Data Analyst in India is ₹8-12 lakhs per annum, with top performers earning up to ₹20 lakhs.

How it works:

  • Step 1: Data Collection - Collect and organize large datasets from various sources, including operational reports, customer feedback, and market research.
  • Step 2: Data Analysis - Use SQL and Power BI to analyze the data, identify trends, and create actionable insights.

Core Concepts to Master

1

SQL Fundamentals

Learn the basics of SQL, including data types, functions, and query writing, to effectively manage and analyze large datasets.

2

Power BI

Master the use of Power BI to create interactive dashboards, reports, and visualizations that drive business decisions.

3

Data Visualization

Learn to create effective data visualizations that communicate complex insights to stakeholders, including charts, graphs, and tables.

Interview Questions (Beginner)

  • What is SQL and how is it used in data analysis?
  • Can you explain the difference between a pivot table and a chart?
  • How do you ensure data accuracy and quality in your analysis?

Job Overview

CompanyLenskart Academy
Employment TypeFull-time
LocationTijara, Rajasthan, India
Experience LevelFresher
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Advance Questions

  • • Design a data warehouse for a large e-commerce company.
  • • Create a predictive model to forecast sales using historical data.
  • • Develop a dashboard to track key performance indicators (KPIs) for a marketing campaign.