This document presents a Venn diagram that outlines the key skills and areas of knowledge required for good and great data science. For good data science, areas include data and IT management, programming languages, mathematical models, linear algebra and calculus, probability distribution and statistical inference, and domain expertise. For great data science, additional people skills are needed like empathy, presentation skills, communication skills, leadership skills, and understanding of human behavior and body language. The document was created by Koo Ping Shung and provides his contact information.

1. Data Science Venn Diagram
Koo Ping Shung
pskoo@smu.edu.sg/koolanalytics@gmail.com

2. Venn Diagram – Good Data Science

3. Data & IT Management
How data collection channel works.
ETL process
How to ensure high quality data.
What are the risk involved in each stage.
Cost & Benefit Analysis
How infrastructure should be structured and
integrated.
What are the limitations of the infrastructure,
especially on data quality.
How to treat missing data?
How to handle data errors?
Programming Languages

4. Mathematical Models
Data Requirements of each models.
Assumptions of each models.
Formulas involved to calculate the coefficients
behind each models.
If data is not enough what to do?
How to do ‘proper’ sampling?
How to evaluate effectiveness of models?
Linear Algebra & Calculus
Probability Distribution & Statistical Inference

5. Domain Expertise
Business Rules, Policies & Process
Regulations
Strategy Planning and Execution
Marketing – Online & Offline
Accounting
HR Management
Supply Chain & Logistics
Consumer Psychology

6. Venn Diagram – Great Data Science!

7. People Skills
Empathy.
Presentation Skills.
Communication Skills.
Leadership Skills.
Be a good follower.
Motivational Skills
Human Behavior & Body Language

8. Koo Ping Shung
pskoo@smu.edu.sg/koolanalytics@gmail.com