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Laila Fettah – Associate Sales Engineer SPSS 27 January 2011. Informatie Analyse. Agenda. Government – Challenges Data mining CRISP-DM Example Application. Ongoing Budget Pressures. Lack of Decision-Quality Information. Ongoing Improvement, Less Resources. - PowerPoint PPT Presentation
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© 2011 IBM Corporation
Informatie Analyse
Laila Fettah – Associate Sales Engineer SPSS
27 January 2011
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Agenda
Government – Challenges Data mining CRISP-DM Example Application
2
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Government faces challenges everyday…
Demonstrate Effective Public
Policy
Ongoing Budget Pressures
Lack of Decision-Quality
Information
Transparency & Accountability
Ongoing Improvement,
Less Resources
3
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
How satisfied
do citizens feel?
Have job creation
programs helped curb
benefits applications?
Have new crime
fighting tactics been
effective?
What fraud patterns
are emerging?
How have collection strategies impacted budgets?
What is likely to
happen in the long-
term?
…and must answer critical questions everyday...
4
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Budgeting & Finance
Program Execution
Services Delivery
Workforce/ HR
Executive Leaders
Operations/ Readiness
Information Technology
Supply Chain
…and silos often persist that impact outcomes...
5
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Information Technology
Budgeting & Finance
Management
Operations/ Readiness Program
Execution
Services Delivery
Supply Chain
Public Safety Staff
Communities
…analytics can tear down silos
6
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
What is data mining?
7
Finding patterns in your data that you can use to do your business better
Business-oriented discovery of patterns producing insight and a predictive capabilitywhich can be deployed widely
Process of autonomously retrieving useful information or knowledge (“actionable assets”) from large data stores or set
“Predictive analysis helps connect data to effective action by drawing reliable conclusionsabout current conditions and future events.”
Gareth Herschel, Research Director, Gartner Group
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
What’s in a name?
Data Mining is not a great metaphor– Would mean people who dig for gold are “rock miners”!
Other early candidates:– Knowledge Discovery in Databases (KDD)– “Torturing the data until it confesses”
• “…and if you torture it long enough, it’ll confess to anything!”
8
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Traditional analyses
First by gender or offender?
By count of crime typeBy time of
offence
What do I do NOW???
What is the profile of the repeat offenders in my
district?
Give me the number of males and females
within the repeat offenders
Give me the times
that crimes where
committed
Give me a count of the types
of crimesReport 1
Report 2
Report 3
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Make individual profiles
A descriptive question
I know from my understanding of
crime that gender, time, place, type of crime, age can be
important
Youth gangs from cities A and B that are mostly active on
Thursday night in the center.Addicts that are mostly active around the central station as
pick pockets………..
There are several profiles for repeat offenders. The most
important are….
Data Mining
What is the profile of the repeat offenders in my district?
Let me think….
Data Mining Technology
Create profiles of repeat offendersbased on gender, time, location,type of crime…
Ok, so I need to talk with the railway and with local
authorities in city A and B….
10
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Descriptive (KPI) Predictive (KPP) Prescriptive (Scenario)
Statistics
Profiling
Clustering
Associations
Classification
Scoring
Prediction
Forecasting
Prediction
Scoring
Forecasting
What If
Underlying analyses
11
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
CRISP-DM
CRoss Industry Standard Process for Data Mining– Funding from European commission– Non-proprietary– Application/Industry neutral– Tool neutral– Focus on business issues as well as technical analysis– www.crisp-dm.org
Process framework for data mining projects– Process Standardization
12
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
CRISP-DM phases
13
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Example Application Areas:
Public Safety–Reduce crime–Improve border protection–Proactive disease surveillance–Intrusion and insider threat
detection Customs & Excise, Tax, Social
security–Predict & prevent fraud–Improve collections–Focus investigators &
inspectors
Defense–Increase battle readiness of
assets–Improve employee acquisition,
retention & growth Citizen satisfaction
–Implement continuous citizen feedback loop
–Improve operational processes ……
14
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Johnny is arrested for breaking into a carHe is 15 years old and confesses that he wanted to belong to a group of friends
Will he become a repeat offender?
If YES: advise DA and later parole officer?
15
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Johnny is arrested for breaking into a carHe is 15 years old and confesses that he wanted to belong to a group of friends
Will he become a repeat offender?
If YES: advise DA and later parole officer?
A citizen reports a burglaryReports that her house was burglarized while she was talking to a representative from the city council
Does this crime resemble others? Is it serial?
Do we have a team working on similar crimes that we can assign it to?
16
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Johnny is arrested for breaking into a carHe is 15 years old and confesses that he wanted to belong to a group of friends
Will he become a repeat offender?
If YES: advise DA and later parole officer?
A citizen reports a burglaryReports that her house was burglarized while she was talking to a representative from the city council
Does this crime resemble others? Is it serial?
Do we have a team working on similar crimes that we can assign it to?
A Break-in into a shop is reportedThe perpetrators entered by breaking a window probably between 3am and 5am. Crime was discovered at 6 pm next day
Does it make sense to send out a CSI team?
Is it likely that they’ll find useful evidence?
17
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
An organized crime unit wants to bust a drugs ringThe detectives are interested in identifying the central players within a narcotics network
Johnny is arrested for breaking into a carHe is 15 years old and confesses that he wanted to belong to a group of friends
Will he become a repeat offender?
If YES: advise DA and later parole officer?
A citizen reports a burglaryReports that her house was burglarized while she was talking to a representative from the city council
Does this crime resemble others? Is it serial?
Do we have a team working on similar crimes that we can assign it to?
A Break-in into a shop is reportedThe perpetrators entered by breaking a window probably between 3am and 5am. Crime was discovered at 6 pm next day
Does it make sense to send out a CSI team?
Is it likely that they’ll find useful evidence?
Who are the key persons? Who are the leaders?18
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Johnny is arrested for breaking into a carHe is 15 years old and confesses that he wanted to belong to a group of friends
Will he become a repeat offender?
If YES: advise DA and later parole officer?
A citizen reports a burglaryReports that her house was burglarized while she was talking to a representative from the city council
Does this crime resemble others? Is it serial?
Do we have a team working on similar crimes that we can assign it to?
A Break-in into a shop is reportedThe perpetrators entered by breaking a window probably between 3am and 5am. Crime was discovered at 6 pm next day
PD uses predictive analytics to profile crimes & criminals to improve solved crime rates and optimize resource usage
Crime Data
Crime record notes and call logs
Surveillance Data
Communication Data
Financial Data
Predictive Modeling for Crime Pattern Detection
An organized crime unit wants to bust a drugs ringThe detectives are interested in identifying the central players within a narcotics network
Does it make sense to send out a CSI team?
Is it likely that they’ll find useful evidence?
Who are the key persons? Who are the leaders?19
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Johnny is arrested for breaking into a carHe is 15 years old and confesses that he wanted to belong to a group of friends
Will he become a repeat offender?
If YES: advise DA and later parole officer?
A citizen reports a burglaryReports that her house was burglarized while she was talking to a representative from the city council
Does this crime resemble others? Is it serial?
Do we have a team working on similar crimes that we can assign it to?
A Break-in into a shop is reportedThe perpetrators entered by breaking a window probably between 3am and 5am. Crime was discovered at 6 pm next day
PD uses predictive analytics to profile crimes & criminals to improve solved crime rates and optimize resource usage
Crime Data
Crime record notes and call logs
Surveillance Data
Communication Data
Financial Data
Aspiring Repeat Offender profile…If maleAnd age 14-16And crime =‘car break in’And motive =‘peer pressure’Then repeat risk is HIGH ALERT DA…
Predictive Modeling for Crime Pattern Detection
An organized crime unit wants to bust a drugs ringThe detectives are interested in identifying the central players within a narcotics network
Does it make sense to send out a CSI team?
Is it likely that they’ll find useful evidence?
Who are the key persons? Who are the leaders?20
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Johnny is arrested for breaking into a carHe is 15 years old and confesses that he wanted to belong to a group of friends
Will he become a repeat offender?
If YES: advise DA and later parole officer?
A citizen reports a burglaryReports that her house was burglarized while she was talking to a representative from the city council
Does this crime resemble others? Is it serial?
Do we have a team working on similar crimes that we can assign it to?
A Break-in into a shop is reportedThe perpetrators entered by breaking a window probably between 3am and 5am. Crime was discovered at 6 pm next day
PD uses predictive analytics to profile crimes & criminals to improve solved crime rates and optimize resource usage
Crime Data
Crime record notes and call logs
Surveillance Data
Communication Data
Financial Data
Aspiring Repeat Offender profile…If maleAnd age 14-16And crime =‘car break in’And motive =‘peer pressure’Then repeat risk is HIGH ALERT DA…
Crime profile Team 4Cluster ‘Bogus Official’ - Burglary, - Visit by city official, - Entry ‘Back door’, - Victim “Elderly’
Predictive Modeling for Crime Pattern Detection
An organized crime unit wants to bust a drugs ringThe detectives are interested in identifying the central players within a narcotics network
Does it make sense to send out a CSI team?
Is it likely that they’ll find useful evidence?
Who are the key persons? Who are the leaders?21
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Johnny is arrested for breaking into a carHe is 15 years old and confesses that he wanted to belong to a group of friends
Will he become a repeat offender?
If YES: advise DA and later parole officer?
A citizen reports a burglaryReports that her house was burglarized while she was talking to a representative from the city council
Does this crime resemble others? Is it serial?
Do we have a team working on similar crimes that we can assign it to?
A Break-in into a shop is reportedThe perpetrators entered by breaking a window probably between 3am and 5am. Crime was discovered at 6 pm next day
PD uses predictive analytics to profile crimes & criminals to improve solved crime rates and optimize resource usage
Crime Data
Crime record notes and call logs
Surveillance Data
Communication Data
Financial Data
Aspiring Repeat Offender profile…If maleAnd age 14-16And crime =‘car break in’And motive =‘peer pressure’Then repeat risk is HIGH ALERT DA…
Crime profile Team 4Cluster ‘Bogus Official’ - Burglary, - Visit by city official, - Entry ‘Back door’, - Victim “Elderly’
CS profile No Deployment…If Break InAnd NightAnd report>12hrsAnd entry =‘broken window’And object=‘Commercial Property’Then probability evidence is 6%…
Predictive Modeling for Crime Pattern Detection
An organized crime unit wants to bust a drugs ringThe detectives are interested in identifying the central players within a narcotics network
Does it make sense to send out a CSI team?
Is it likely that they’ll find useful evidence?
Who are the key persons? Who are the leaders?22
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
An organized crime unit wants to bust a drugs ringThe detectives are interested in identifying the central players within a narcotics network
Johnny is arrested for breaking into a carHe is 15 years old and confesses that he wanted to belong to a group of friends
Will he become a repeat offender?
If YES: advise DA and later parole officer?
A citizen reports a burglaryReports that her house was burglarized while she was talking to a representative from the city council
Does this crime resemble others? Is it serial?
Do we have a team working on similar crimes that we can assign it to?
A Break-in into a shop is reportedThe perpetrators entered by breaking a window probably between 3am and 5am. Crime was discovered at 6 pm next day
PD uses predictive analytics to profile crimes & criminals to improve solved crime rates and optimize resource usage
Crime Data
Crime record notes and call logs
Surveillance Data
Communication Data
Financial Data
Aspiring Repeat Offender profile…If maleAnd age 14-16And crime =‘car break in’And motive =‘peer pressure’Then repeat risk is HIGH ALERT DA…
Crime profile Team 4Cluster ‘Bogus Official’ - Burglary, - Visit by city official, - Entry ‘Back door’, - Victim “Elderly’
CS profile No Deployment…If Break InAnd NightAnd report>12hrsAnd entry =‘broken window’And object=‘Commercial Property’Then probability evidence is 6%…
Key PlayersFocus on:• Keith Patterson• Colin Wiertz• Markus Haffey
Predictive Modeling for Crime Pattern Detection
Does it make sense to send out a CSI team?
Is it likely that they’ll find useful evidence?
Who are the key persons? Who are the leaders?23
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Johnny is arrested for breaking into a carHe is 15 years old and confesses that he wanted to belong to a group of friends
Will he become a repeat offender?
If YES: advise DA and later parole officer?
A citizen reports a burglaryReports that her house was burglarized while she was talking to a representative from the city council
Does this crime resemble others? Is it serial?
Do we have a team working on similar crimes that we can assign it to?
A Break-in into a shop is reportedThe perpetrators entered by breaking a window probably between 3am and 5am. Crime was discovered at 6 pm next day
PD uses predictive analytics to profile crimes & criminals to improve solved crime rates and optimize resource usage
Management Dashboard
Crime Data
Crime record notes and call logs
Surveillance Data
Communication Data
Financial Data
Predictive Modeling for Crime Pattern Detection
Aspiring Repeat Offender profile…If maleAnd age 14-16And crime =‘car break in’And motive =‘peer pressure’Then repeat risk is HIGH ALERT DA…
Crime profile Team 4Cluster ‘Bogus Official’ - Burglary, - Visit by city official, - Entry ‘Back door’, - Victim “Elderly’
CS profile No Deployment…If Break InAnd NightAnd report>12hrsAnd entry =‘broken window’And object=‘Commercial Property’Then probability evidence is 6%…
Key PlayersFocus on:• Keith Patterson• Colin Wiertz• Markus Haffey
An organized crime unit wants to bust a drugs ringThe detectives are interested in identifying the central players within a narcotics network
Does it make sense to send out a CSI team?
Is it likely that they’ll find useful evidence?
Who are the key persons? Who are the leaders?24
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Capture Predict Act
Crime Data
Crime record notes and call logs
Surveillance Data
Communication Data
Financial Data
25
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Capture Predict ActCapture Predict Act
Crime Data
Crime record notes and call logs
Surveillance Data
Communication Data
Financial Data
Crime Pattern & Hotspot Clustering
Automated Link AnalysisProfiles & Associations
Predictive Modeling for Crime Pattern Detection
26
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Capture Predict ActCapture Predict Act
Crime Data
Crime record notes and call logs
Surveillance Data
Communication Data
Financial Data
Crime Pattern & Hotspot Clustering
Automated Link AnalysisProfiles & Associations
Criminal Career Scoring Model
MO Typology Model
Crime Scene Assessment Model
Predictive Modeling for Crime Pattern Detection
27
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Capture Predict ActCapture Predict Act
Crime Data
Crime record notes and call logs
Surveillance Data
Communication Data
Financial Data
Crime Pattern & Hotspot Clustering
Automated Link AnalysisProfiles & Associations
Criminal Career Scoring Model
MO Typology Model
Crime Scene Assessment Model
Arresting Officer
Case AssignmentOfficer
CSI Resource Planner
Alert!Aspiring Repeat Offender Risk HIGHAdvise DA and inform parole officer
Alert!Serial Crime ProfileMO fits Team 4
Alert!Very Low Likelihood EvidenceProbability <10% No Deployment
Predictive Modeling for Crime Pattern Detection
28
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Capture Predict ActCapture Predict Act
Crime Data
Crime record notes and call logs
Surveillance Data
Communication Data
Financial Data
Crime Pattern & Hotspot Clustering
Automated Link AnalysisProfiles & Associations
Criminal Career Scoring Model
MO Typology Model
Crime Scene Assessment Model
Investigative Model Template Repository
Arresting Officer
Case AssignmentOfficer
CSI Resource Planner
Investigating Officer
Predictive Modeling for Crime Pattern Detection
Feedback resultsFeedback loop of new data to improve and adapt predictions
Key PlayersFocus on:• Keith Patterson• Colin Wiertz• Markus Haffey
Alert!Aspiring Repeat Offender Risk HIGHAdvise DA and inform parole officer
Alert!Serial Crime ProfileMO fits Team 4
Alert!Very Low Likelihood EvidenceProbability <10% No Deployment
29
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Capture Predict ActCapture Predict Act
Crime Data
Crime record notes and call logs
Surveillance Data
Communication Data
Financial Data
Crime Pattern & Hotspot Clustering
Automated Link AnalysisProfiles & Associations
Criminal Career Scoring Model
MO Typology Model
Crime Scene Assessment Model
Investigative Model Template Repository
Arresting Officer
Case AssignmentOfficer
CSI Resource Planner
Analytical Process Automation & OptimizationAutomate prediction & deployment process
Analytical Process Management & ControlMonitor & manage analytics process
Predictive Modeling for Crime Pattern Detection
Feedback resultsFeedback loop of new data to improve and adapt predictions
Investigating Officer
Key PlayersFocus on:• Keith Patterson• Colin Wiertz• Markus Haffey
Alert!Aspiring Repeat Offender Risk HIGHAdvise DA and inform parole officer
Alert!Serial Crime ProfileMO fits Team 4
Alert!Very Low Likelihood EvidenceProbability <10% No Deployment
30
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
Capture Predict ActCapture Predict Act
Crime Data
Crime record notes and call logs
Surveillance Data
Communication Data
Financial Data
Crime Pattern & Hotspot Clustering
Automated Link AnalysisProfiles & Associations
Criminal Career Scoring Model
MO Typology Model
Crime Scene Assessment Model
Investigative Model Template Repository
Arresting Officer
Case AssignmentOfficer
CSI Resource Planner
Analytical Process Automation & OptimizationAutomate prediction & deployment process
Analytical Process Management & ControlMonitor & manage analytics process
Predictive Modeling for Crime Pattern Detection
Management Dashboard
Feedback resultsFeedback loop of new data to improve and adapt predictions
Investigating Officer
Key PlayersFocus on:• Keith Patterson• Colin Wiertz• Markus Haffey
Alert!Aspiring Repeat Offender Risk HIGHAdvise DA and inform parole officer
Alert!Serial Crime ProfileMO fits Team 4
Alert!Very Low Likelihood EvidenceProbability <10% No Deployment
31
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
32
Start from business understanding… not from data or technique…
© 2011 IBM Corporation
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
33
…and use a methodology!
© 2011 IBM Corporation
Questions
Van informatie op Orde naar Informatie van Waarde – 27 januari 2011
34