2006 Address

Transcription

2006 Address

Visual Analytics
Chris Westphal
Visual Analytics Inc
www.visualanalytics.com
Copyright © 2006-2013 – All Rights Reserved
240-215-6600 • www.visualanalytics.com
–1–
Prerequisites for Analysis
It’s not rocket science…
Need to use your noodle
It’s not nuclear science…
…but it does require some intelligence
Need to think “outside the box”
Need to know your data
!
Need to learn new techniques
–2–
1+1=a
What does…
…. a money launderer look like?
…. a criminal look like?
…. an insider trader look like?
…. a generic disorder in DNA look like?
…. a manufacturing defect look like?
…. a terrorist look like?
–3–
How Do We Do It?
How can we find something when we
don’t know what it looks like???
 Black Holes
 Math Postulates / E=MC2
 Gödel's Incompleteness Theorem
If it could only be this easy…
www.staples.com
–4–
Rely on Visualization to...
 Observe without preconception
 Exploit cognitive ability to interpret data
 Manage large quantities of disparate data
 Integrate multiple data sources and formats
 Expose relationships, patterns, and trends
Visualization can be the analyst’s best cognitive tool
–5–
Different Visual Paradigms
Link Analysis
Landscape Displays
Quantitative Diagrams
Visualizations are not mutually exclusive and can be combined
–6–
Want to Expose Patterns & Trends
 Need to use right visual
presentation for exposing
patterns.
 Many times the pattern is not
obvious – and using alternative
presentations can help expose
the anomaly.
It’s like trying to find a
needle in a haystack
 How will business processes
change once the patterns are
found?
–7–
Where Are the Patterns?
–8–
What Do Patterns Look Like?
?
–9–
Finding Patterns in the Data
Pattern #1
Pattern #3
Pattern #2
The method of data presentation is key to exposing hidden patterns
– 10 –
Understanding the Patterns
Is this pattern
important?
Person
Tax revenue collection
ID-Num
ID-Num
ID-Num
X1
X2
Insurance claims
Person
Person
Person
Retail marketing - moving
Retail marketing - mailers
Y1
Warranty repairs - fraud
Depends on the context...
– 11 –
Address
Address
Address
Person
Person
Item
Return
Return
Which Pattern is More Important?
Pattern #2
Pattern #1
SSN
SSN
SUBJECT
SUBJECT
SUBJECT
SSN
SSN
SUBJECT
SUBJECT
SSN
SUBJECT
SSN
SUBJECT
– 12 –
SSN
Do these Patterns Make Sense?
Pattern #1
Pattern #2
ID NUMBER
SSN
SSN
SUBJECT
REPORT
ORG
ADDRESS
PHONE
= SS Death Master Hit
SSN
– 13 –
Is this a Reliable Pattern?
Pattern #1
PHONE
EVENT 05/16/05
EVENT 01/01/02
EVENT 06/03/05
SUBJECT
SUBJECT
EVENT 01/05/02
EVENT 06/27/05
EVENT 01/11/02
ADDRESS
Pattern #2
– 14 –
EVENT 07/01/05
Is this an Important Pattern?
– 15 –
What Does this Pattern Tell Us?
– 16 –
Who is the Most Important Person?
– 17 –
General Pattern Types
Financial
Transactions
Financial
Transactions
Real Property
Assets
Real Property
Assets
Criminal
History
Criminal
History
Horizontal Patterns
(within same domain)
Vertical Patterns
(across domains)
Patterns can occur both within and across data sets
– 18 –
Integration of Multiple Sources
Analytical Sources
vs.
Referential Sources
Watch lists
Case reports
Verifications
3rd Party Ref.
TELEPHONE
CRIMINAL
– 19 –
TERRORISM
Some Simple Questions…
What do these companies have in common?
CARIBBEAN HAPPY LINES
MODERN ELECTRONIC COMPANY
SACKS FACTORY
Where can this telephone number be found?
202-289-9313
What is located at this address?
801 Mount Vernon Place, NW
Washington, DC 20001
What is the vehicle make/model of this VIN?
5GTDN136568134689
Who owns this Social Security Number?
078-05-1120
– 20 –
1) OFAC list 2) Greyhound Bus Station 3) DC Convention Center 4) Hummer/H3 5) The Woolworth Card
Some Simple Questions…
Who is the FBI’s most wanted fugitive ?
What happened on 03/11/2004 ?
Where is 38.898748° 77.037684° ?
Who owns this IP address: 198.81.129.100 ?
Where is ZIP code 96616-2876 found ?
– 21 –
1) Usama Bin Laden 2) Madrid Bombings 3) White House 4) CIA 5) USS Ronald Regan
Exposing the Important Facts
SUBJECT
SUBJECT
?
ADDRESS
PHONE
SUBJECT
SUBJECT
SUBJECT
SUBJECT
SUBJECT
PHONE
SUBJECT
SUBJECT
EVENT
ADDRESS
ADDRESS
SUBJECT
SUBJECT
EVENT
EVENT
– 22 –
EVENT
Analysis of the Warranty Data
Show all vehicles with fewer than 100 miles
brand new cars
many will still be on the dealership lot
not realistic mileage for general service repairs
Show labor only
entire cost is based on mechanic time
no parts replaced (not traceable)
no work was outsourced (not external)
Extracted Set
Repair Type
Review Details
1 hour - $45
1 hour - $60
1 hour - $50
1 hour - $65
Cigarette Lighters
– 23 –
1 hour - $45
Analysis of an Embezzlement
Show corporate AMEX charges for employees
look for charges directly to an airline
airfare is to be done by travel agent
cost of tickets usually reflects full fare
Show on-line expense reports for employees
choose only those with airfare charges
inter-relate the AMEX charges
look for debit-expense-credit pattern
Extracted Set
Time Sequence
Debit
Expense Credit
AMEX Credit
– 24 –
Conclusion
 Use of different visual paradigms
– Link analysis
– Clustering
– Sequences
 Incorporate multiple sources
– Analytical
– Referential
 Understand the data
 Interpret the visual
 Interactive process
– 25 –

2006 Address

Transcription

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