Year 1 Internship Roadmap
Week 1
– Introduction to the Corporate World & Data Analytics
Objective:
Understand how companies work and where data analytics fits.
Topics
Company orientation
Different departments in an organization
What does a Data Analyst actually do?
Difference between:
Data Analyst
Business Analyst
Data Scientist
Data Engineer
ML Engineer
The data analytics lifecycle
Common tools used in industry
Week 2 – Business Fundamentals for Data Analysts
Objective: Learn the language of business.
Topics
How companies make money
Revenue vs Profit
Cost vs Investment
KPIs
Customer journey
Conversion funnel
Business models
Decision-making using data
Choose any company (Amazon, Flipkart, Swiggy, etc.) and explain how data analytics supports its business.
Week 3 – Thinking Like an Analyst
Objective: Develop analytical thinking.
Topics
Defining business problems
Asking the right questions
Root Cause Analysis (5 Whys)
Fishbone Diagram (Ishikawa)
Critical thinking
Structured problem solving
Analyze a business problem (e.g., declining website traffic) and list:
Questions to ask
Possible causes
Data required
Potential solutions
Week 4 – Data Quality & Data Ethics
Objective: Understand why clean and ethical data matters.
Topics
Data quality dimensions
Missing values
Duplicate records
Data validation
GDPR
PII
Data privacy
Responsible AI
Write a case study on a real-world data breach and discuss its business impact.
Week 5 – Understanding Business Metrics
Objective: Learn the metrics that companies monitor.
Topics
CAC
CLV
Churn Rate
ROI
Gross Margin
Net Profit
Conversion Rate
Bounce Rate
Retention Rate
Create a glossary explaining each metric with a practical example.
Week 6 – Data Storytelling & Communication
Objective: Learn to communicate insights effectively.
Topics
Storytelling with data
Choosing the right chart
Presenting to non-technical stakeholders
Executive summaries
Presentation skills
Week 7 – Corporate Skills
Objective: Build professional workplace habits.
Topics
Professional email writing
Meeting etiquette
Daily status reports
Weekly reports
Documentation
Time management
Team collaboration
Receiving and acting on feedback
Week 8 – Industry Research & Presentation
Objective: Connect theory with practice.
Topics
Case studies:
Netflix
Amazon
Uber
Spotify
Banking fraud detection
"How Data Analytics Solves Real Business Problems"
Year 2 Internship Roadmap
Week 1 – Working with Real-World Data
Topics
Difference between academic datasets and company datasets
Types of business data
Structured vs Unstructured Data
Sources of data
Data collection methods
Importance of data accuracy
Research different types of business data and explain where companies collect them from.
Week 2 – Excel for Business
Topics
Why companies still use Excel
Sorting and Filtering
Conditional Formatting
Basic formulas
Pivot Tables
Charts
Organizing data
Week 3 – Introduction to SQL in Business
Topics
What is SQL?
Why businesses use databases
Basic SQL queries
Filtering data
Sorting results
Aggregate functions
GROUP BY
Write SQL queries to answer simple business questions (e.g., highest sales, total orders, average revenue).
Week 4 – Understanding Business Metrics
Topics
Revenue
Profit
Sales
Customer
Conversion Rate
Website Traffic
Bounce Rate
Customer Satisfaction
Choose a company and identify five important metrics they should track
Week 5 – Data Visualization
Topics
Why graphs are important
Choosing the right chart
Common visualization mistakes
Storytelling with charts
Presenting insights clearly
Week 6 – AI Tools for Data Analysis
Topics
ChatGPT
Gemini
Claude
NotebookLM
Responsible use of AI
Writing effective prompts
Assignment
Compare three AI tools and explain how each can help a Data Analyst in daily work.
Week 7 – Corporate Skills
Topics
Professional emails
Team communication
Meeting etiquette
Daily work reports
Time management
Receiving feedback
Workplace professionalism
Week 8 – Final Business Case Study
Task
Choose one company (Amazon, Swiggy, Zomato, Flipkart, Netflix, etc.) and prepare a report covering:
What the company does
What data it collects
Why that data is valuable
Three business problems data can solve
Five KPIs the company should monitor
Recommendations based on your analysis
Chandramouli Singh
Web Developer
AeroSoft Corp
Asiatic International Corp
LinkedIn :
linkedin.com/in/chandramouli02
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