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Human Obsession with Prediction - Coggle Diagram
Human Obsession with Prediction
HISTORY (2000 year)
8BC: Ancient Greeks heared predictions at the Oracle of Delphi
Since then, there exist common sense, nonsense and wishful thinking.
Prediction
turned scientific to statistics in England (around 1700AD)
Hyper-progress around World War II
In business analytics, they used data to predict outcomes of their firm
PREDICTIVE MODELS
GOOD PREDICTIONS
Requirements
Sound Reasoning
Business apps transforms
data to information and knowledge
Non IT-managers
are the only sources of things competitively worth predicting and models in their functions domain
Apps are "
models
" translated into software codes
Sound Data
Data
: Raw facts
IT's unit job
: Collecting and managing data (but not all data is worth managing)
Insight
: Actionable information
Competitively valuable
Information
: Sorted, condensed,and contextualized data
Assumption: Past behavior can predict future
The bread-and-butter of analytics
Firms got better at collecting data
Example
Data warehouses
Data centers
Spreadsheets
Led to flurry of innovative practices in all functional area
Tier customers on lifetime value
Segment markets
Forecast demand for a product any hour