Web2 0-Summit-Jonas-distrib(2)

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1

Cops & RobbersLas Vegas Style

Jeff Jonas, Chief Scientist, IBM Entity Analytics

Blogging at www.JeffJonas.TypePad.com



2

Background

Founded Systems Research & Development(SRD) in 1983

Moved to Las Vegas in early 90’s

Assisted gaming industry in betterunderstanding who they were doing businesswith (e.g., the MIT Team)

Acquired by IBM January 2005Now Chief Scientist of IBM Entity Analytics



3

My Living Room – December 31, 2005



4

Cheating Las Vegas



5

The “Cold” Deck : $250,000 Gone in 15 Minutes

[Video Redacted]



6

More AboutCorporate Amnesia



ProspectDatabase

EmployeeDatabase

HumanResourcesDepartment

CorporateSecurity

Department

InvestigationsDatabase

Marketing department is mailing offers to a

person currently in jail for stealing from you!

MarketingDepartment

Perception Isolation … Produces Corporate Amnesia



Enterprise Intelligence

RequiresPersistent Context

The Brain!



For Example



10

Marc R Smith123 Main St713 730 5769

M. Randal SmithDOB: 06/07/74

713 731 5577

Mark Randy Smith123 Main Street713 731 5577

ProspectDatabase

FraudDatabase

Record #A-701The Query

Record #B-9103

SensorsObservations

Consider the Query Against these Observations



11



713 731 5577


The Query Record #A-701

Record #B-9103

ProspectDatabase

FraudDatabase

SensorsObservations

Some Observations are Discoverable



12



713 731 5577


The Query Record #A-701

Record #B-9103

ProspectDatabase

FraudDatabase

SensorsObservations

Other Observables … are Undiscoverable



13


713 731 5577


FEATURES:Mark Randy Smith, M. Randal Smith

123 Main Street, 713 731 5577DOB 06/07/74

EVENTS:

Internet InquiryArrest

ReconstructedIdentities

If You First Construct Context (Features and Events)

SensorsObservations

Record #A-701

Record #B-9103

ProspectDatabase

FraudDatabase



14

PersistentContext

Mark

FEATURES:Mark Randy Smith, M. Randal Smith

123 Main Street713 731 5577

DOB 06/07/74

Accumulating and Persisting this Context


713 731 5577


SensorsObservations

Record #A-701

Record #B-9103

ProspectDatabase

FraudDatabase



15



Record #A-701


713 731 5577

Record #B-9103

Queries

Now the Un-discoverable …



16


Record #A-701


713 731 5577

Record #B-9103

FEATURES:Mark Randy Smith, Randal Smith123 Main Street

713 731 5577DOB 06/07/74

PersistentContext Observations

… After Accumulating and Persisting Context …


Queries



17



713 731 5577DOB 06/07/74


Record #A-701


713 731 5577

Record #B-9103

Queries PersistentContext Observations

Enables Enterprise Discovery



18



713 731 5577DOB 06/07/74


Record #A-701


713 731 5577

Record #B-9103

Queries PersistentContext Observations

Enables Enterprise Discovery



19


The query could be:- A user with a question

Or, also could be data:- An account opening- A new watch list entry- A background check- An address change- A vendor application- A customer inquiry

Queries

EXCEPT: Always Treat Data as a Query



20

1st principle

If you do not process every newpiece of key data (perception)

first like a query … then you willnot know if it matters … until

someone asks.



21

Prospect

Database

EmployeeDatabase


CorporateSecurity

Department

Investigations

Database

“The Data is a Query” Beats “Boil the Ocean”

Midnight Batch Analytics?

MarketingDepartment



22

Emile SwelterSan Francisco12/03/72


Record #A-701

M. Randal Smith

DOB: 06/07/74713 731 5577

Record #B-9103

?

Queries PersistentContext

Observations

And … Any Query can be Treated as Data …



23


Record #A-701

M. Randal Smith

DOB: 06/07/74713 731 5577

Record #B-9103

PersistentContext

ObservationsQueries


… In Which Case the Query can Stick (Persist)



24

PersistentContext

Notable, Stick in the Same Data Space



25

Question answeredwhen it becomes true!

Emilee Swelter

321 Ovington PlaceSan Francisco03/12/72

New ObservationPersistentContext


Queries

Now, New Observations Answer Persistent Queries



26

2nd principle

Treat queries like data to avoidasking every question every day.



27


713 731 5577


ProspectDatabase

FraudDatabase

Record #A-701

Record #B-9103

ObservationsPersistentContext

Mark

FEATURES:Mark Randy Smith, Randal Smith

123 Main Street713 731 5577

DOB 06/07/74

Sensors

This is Context Construction (A Librarian Function)



28


713 731 5577


ProspectDatabase

FraudDatabase

Record #A-701

Record #B-9103

ObservationsPersistentContext

Mark

FEATURES:Mark Randy Smith, Randal Smith

123 Main Street713 731 5577

DOB 06/07/74

Sensors

!

The Ideal Moment for Enterprise Awareness



29

3rd principle

Enterprise awareness iscomputationally most efficient

when performed at the momentthe observation is perceived.



30

The “data finds the data” …

and “relevance finds the user.”

Towards Enterprise Intelligence

Introducing Perpetual Analytics



31

Real Technology

Scalable to >3Bhistorical observations

while handling >2,000real-time perceptions a

second



32

Privacy and Civil Liberties – Policy Think

What perceptions can or shouldbe placed into context (in onebrain)?

What if someone steals the

brain?

What if the librarian is corrupt?



33 The Brain!

EmployeeDatabase


Analytics in the Anonymized Data Space

Mark Randy Smith

Cd5dced41028cb …



34

The Main Think – Towards Enterprise Intelligence

Without persistent context you have nobrain

Treat data and queries with equal rights

More intelligence possible when thinking onstreaming perceptions

More or less perceptions, that is thequestion



35

Battling Corporate Amnesia is Broadly Useful

National security

Financial services

Health care

Heavily focused on threat and fraud

intelligence



36



Blogging at www.JeffJonas.TypePad.com



37

Bonus Section!

If 6%



38

If a .6%difference

matters thismuch…

… no wondertraditionalinformation

systems lack somuchintelligence!



39


713 731 5577DOB 06/07/74

FEATURES:Mark Randy Smith, Randal Smith, Randy Smith123 Main Street, Flat 6 20 Lennox Gardens

713 731 5577, 796 064 03 04DOB 06/07/74, Passport: 001003429002

2 Observations 6 Observations

More ObservationsMore

More Observations = Better Context



40

Stable(e.g., Analytics withSequence Neutrality)

Data Loading Over Time

P e r c e n t

o f

E r r o r Reload #11 Reload #12

Unstable(e.g., data warehousingwhich requires periodic

reloads to handle data drift)

Drift

Sequence Neutrality is Critical for Context Stability





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