Data Science for Business Decision Making

Chapters

1Foundations of Data Science in Business

2Business Problem Framing and Decision Science

3Data Strategy, Governance, and Ethics

4Data Acquisition and Quality Management

5Exploratory Data Analysis and Business Understanding

6Descriptive Analytics and BI for Operators

7Statistical Thinking for Decision Making

8Experimentation and Causal Inference

9Predictive Modeling for Business Outcomes

10Time Series and Forecasting

11Customer and Marketing Analytics

12Operations, Pricing, and Optimization

Optimization problem types Linear and integer programming Heuristics and metaheuristics Inventory models and policies Supply chain analytics Workforce planning Pricing strategies and rules Revenue management levers Capacity planning Routing and logistics Queueing theory basics Simulation modeling Trade-off and sensitivity analysis Constraint management Decision support systems

13Data Storytelling, Visualization, and Influence

14Productizing Analytics: MLOps and Deployment

15Measuring Impact, ROI, and Change Management

Courses/Data Science for Business Decision Making/Operations, Pricing, and Optimization

Operations, Pricing, and Optimization

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Apply optimization and simulation to improve operations, pricing, and logistics.

Content

13 of 15

Trade-off and sensitivity analysis

Original version

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