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Data Analytics for Business Professionals

Video Introducing this tutorial


Introduction
Welcome
What you should know

1. Data Analytics in the Business World
Business leaders and data analytics
Introduction to Wear One
Types of data
Case study 1: Performance at Miami locations
Case study 1: Explanation
Challenge: Calculate descriptives
Solution: Calculate descriptives

2. Predictive and Prescriptive Analytics
Predictive analytics
Challenge: Make predictions
Solution: Make predictions
Prescriptive analytics

3. Asking the Right Question
Guidelines for formulating questions
Crafting better questions
Case study 2: What is the right question?
Role of business acumen

4. Unlocking the Data Within
Data collection issues
Case study 3: Unclean data
Case study 3: Explanation
Data fail: When data is just wrong

5. Understanding Averages
Nature of averages
Case study 4: Conversion rates and benchmark
Case study 4: Explanation
Context is everything

6. Sampling
Pros and cons
Case study 5: Social media survey
Case study 5: Explanation
Case study 5: Statistical deep dive

7. Cherry Picking
What is cherry picking?
Case study 6: Revenue
Case study 6: Explanation

8. Forecasting
Hurricane Matthew
Case study 7: Forecasting customer complaints
Case study 7: Explanation
Issues to consider

9. Correlation versus Causation
Cause and effect
Case study 8: Boston revenue
Case study 8: Explanation
Causal questions

Conclusion
Next steps

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