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LinkedIn Learning

Data Analytics for Business Professionals

via LinkedIn Learning

Overview

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

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

Taught by

John Johnson

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