Summary of "Data Analysis Kya Hota Hai? Different Types of Tools Data Analysts Use"

Main Ideas & Concepts Conveyed

A data analyst is given a business problem (e.g., create different internet plans).
They collect usage data from all users (example given: 500 million users).
They identify patterns/categories of usage, such as:
- A group with very low usage (mostly browsing), about 2–3 GB/day
- Another group with high usage, consuming more than 3 GB/day and streaming major events (e.g., cricket/football)
Based on these categories, they design multiple plans tailored to different customer behavior.

Lesson: Data analytics is about finding patterns in data to support decision-making and strategy.

The speaker worked for 2.5 years in a data analytics team at a bank.
Responsibilities included analyzing loan growth month-over-month and year-over-year.
Work scale: a global bank with 90,000+ employees and hundreds of analysts.
Output: reports to senior leadership to support critical decisions.

Lesson: Data analysts turn data into insights that leadership can act on.

Descriptive Analytics
- Answers: What happened?
- Example questions:
  - How is revenue performance in the last three months?
  - Did sales grow from January → February → March?
Diagnostic Analytics
- Answers: Why did it happen?
- Example questions:
  - Revenue was fine in February, but why did it drop in March?
Predictive Analytics
- Answers: What is likely to happen next?
- Example scenario:
  - Using 5 years of historical data to forecast the next 3 months (whether sales will rise and by how much).
Prescriptive Analytics
- Answers: What should we do to get the best outcome?
- Example concept:
  - If offering discounts or increasing marketing spend correlates with higher revenue, then:
    - Use that relationship during key seasonal periods (e.g., December gifting, summer mango sales) to increase sales.

A common misconception addressed: data analytics is not only for computer science or statistics backgrounds.
Speaker example: B.Com graduate who got a data analytics job after college.
Recommendation: pursue online courses to learn the skills.

“Skill Arbitrage’s detailed course on data analytics” (link referenced as being in the description).

SQL (Structured Query Language)
- Purpose: learn database management
- Benefit: opens the door to data analytics work
Tableau
- Purpose: data visualization and analysis presentation (dashboard-style)
Power BI
- Clarified as: Power Business Intelligence
- Purpose: visualization and presenting analytics
Python (for advanced learning)
- Suggested after learning the tools above for more advanced capabilities