predictiveanalytics
TRANSCRIPT
Predictive Analytics
Defined:Brief Examples:Goal driven analysis of
“large” data sets…
To identify an approach for allocating organizational resourcesThat enhances performance on the organization’s self-defined performance metricsTo better achieve the organization’s business objectivesUsing a repeatable consistent strategy
Business
Objectives
DataQuantitative
Analysis
Spread
Sheets
BusinessIntelligence
Data Mining
Predictive
Analytics
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Predictive Analytics:
Opportunity Identification
1. Define Business Objective
2. Define Performance Metrics
3. Identify Behaviors that Impact
Performance
4. Identify Scarce Resources to be
Allocated
5. Confirm Availability of Historical Data
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Pro
cess
Ste
ps
Participants Barriers
Business Expert(s) Data Expert(s) Math Expert(s)
Determine Business Question(s) & Performance Metric(s)
Knowledge of Available Data: Within Internal and External Sources
Access to – or Quick Creation of – Usable Data; Minimizing Replication & Security Issues
Connection to Front-Line Business Issues
Time to Devote to Project; Collaboration with Fellow Data Scientists
Integration with Many Modeling Software Tools
Volume of Data to Validate Models
Data Expert Support to Embed Working Model into System; Business Expert Support to
Implement Business Process Changes
Identify Relevant Data
Pull Relevant Data
Data Preparation
Model Data
Evaluate Models
Deploy Validated Model(s)
Reporting Structure & Access to Expertise
Predictive Analytics Process
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Statistics Focuses on Central Tendency
Statistically Significant Difference, p < 0.05 ?
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Statistics vs. Predictive Analytics
Predictive Analytics Focuses on the “Tails”
Identification of the ExtremesHold-Out Sample Validation
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Statistics vs. Predictive Analytics
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Classification Forecasting
…Determined Largely by Phrasing of “Business Question”
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Predictive Analytics Success
Phase 1: Positive Behavior
Phase 2: Negative Behavior
Phase 3: Conflict Resolution
Phase 4: Ranking Across Continuum
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Predictive Analytics: Phased Execution