Overview
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Learn how to use data analytics to make better business decisions and gain competitive advantage. This fast-paced introduction is ideal for managers and executives.
Syllabus
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Introduction
- Welcome
- What you should know
- 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
- Predictive analytics
- Challenge: Make predictions
- Solution: Make predictions
- Prescriptive analytics
- Guidelines for formulating questions
- Crafting better questions
- Case study 2: What is the right question?
- Role of business acumen
- Data collection issues
- Case study 3: Unclean data
- Case study 3: Explanation
- Data fail: When data is just wrong
- Nature of averages
- Case study 4: Conversion rates and benchmark
- Case study 4: Explanation
- Context is everything
- Pros and cons
- Case study 5: Social media survey
- Case study 5: Explanation
- Case study 5: Statistical deep dive
- What is cherry picking?
- Case study 6: Revenue
- Case study 6: Explanation
- Hurricane Matthew
- Case study 7: Forecasting customer complaints
- Case study 7: Explanation
- Issues to consider
- Cause and effect
- Case study 8: Boston revenue
- Case study 8: Explanation
- Causal questions
- Next steps
