Module 1 Flashcards
Common mistakes in the absence of data analytics:
-“fooled by randomness”
-drawing broad conclusions from small samples
-basing decisions on anecdote
-confirmation bias
collecting evidence that supports the existing conclusion
discounting evidence that does not support the existing conclusion
The need for data analytics:
-Bias: instincts can be misleading (cultural/racial bias)
-complexity: with greater complexity comes greater risk
-data analytics can lead to…….. (outcomes that would have been missed
Examples of business analytics in marketing
- recommendation systems
-Netflix, google, spotify
-measures what you liked before and what other similar to you have liked
Examples of analytics in management
-predicting warehouse volumes by location for upcoming delivery requests
-amazon and Walmart shipping centers
-the race to same day delivery
Four different methods of business analytics
- Descriptive: interpreting historical data to identify trends and patterns. mostly done by visualization (answers “what happened?”)
- Diagnostic: interpretation of historical data to determine why something has happened (“Why did this happen?”)
- Predictive: the use of statistics to forecast future outcomes (what might happen in the future?”)
- prescriptive: application of testing and other techniques to determine which scenario gives the best result (What should we do next?”)
Tools for data analytics
-communication skills
-synthesis
-statistics (evidence based decision making)
-software tools (excel aka workhorse)
three types of questions for data analytics
- predicting an outcome
- evaluating information
- identifying a casual relationship
Data analytics is transforming all of the business disciplines like….
- marketing
-finance
-management
-accounting
-economics
Data is the raw material of knowledge. It is the foundation of:
-facts
-evidence
-truth