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Using Graphs for Next-Gen Master
Data Management with Pitney Bowes
Spectrum
Aaron Wallace
Global Product Manager
Pitney Bowes Software
@aaronw_pb
powered by
powered by
Consume
Search
Integrate
Visualize
Complete View of Individual
InteractionsSingle view of Individual
+ relationships
+ all interactions
Transactional Information with
Business Applications
Interactions Information from
Social Media
Sales, Billing, Customer center,
Support, etc
Applying analytical capability
to create insight
Insights
Explore Data
Predict
Optimize Interactions
Complete View of Individual
Interactions
Single view of Individual
+ relationships
+ all interactions
Transactional Information with
Business Applications
Interactions Information from
Social Media
Sales, Billing, Customer center,
Support, etc
Single View of
Individual
Relationships
Products and services
Purchased
Household Relationships
Organizational
Relationships
Location
Relationships
Social Network
Single View of
Individual *
* Individual could be a customer, prospect,
victim, terrorist, etc
Data integration
Data cleansing (data
quality)
Data supplementation
(Reference data)
Data enrichment
(geocoding)
Master Data Management
powered by
Graph Modeling
powered by
Choosing Graph and Neo4j
• Started with graph databases
and Neo4j in 2010
• Early prototypes revealed key
differentiators for MDM space
• Why Neo4j?
• Java
• Multi-platform
• High Performance
• ACID
• Market Leader
powered by
Best of Suite CIM
• Platform approach must account
for all key Customer Information
Management functions
• Data Quality
• Data Integration
• Data Enrichment
• Master Data Management
• Data Governance
powered by
Market Perspective
• Gartner
• On the rise in Hype Cycle reports
• “The amount of business situations in which
graphs constitute the ideal presentation
framework is staggering”
• Forrester
• Hub for Context
• “Much more intuitive, analytic, and intelligent
for master data”
powered by
Demonstration - Spectrum
Use Case – Master Data
for Retail Marketing
Analysis
SAN FRANCISCO | 10.22.2014
powered by
Thank You

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Using Graphs for Next Gen Master Data management with Pitney Bowes Spectrum

  • 1. Using Graphs for Next-Gen Master Data Management with Pitney Bowes Spectrum Aaron Wallace Global Product Manager Pitney Bowes Software @aaronw_pb powered by
  • 2. powered by Consume Search Integrate Visualize Complete View of Individual InteractionsSingle view of Individual + relationships + all interactions Transactional Information with Business Applications Interactions Information from Social Media Sales, Billing, Customer center, Support, etc Applying analytical capability to create insight Insights Explore Data Predict Optimize Interactions Complete View of Individual Interactions Single view of Individual + relationships + all interactions Transactional Information with Business Applications Interactions Information from Social Media Sales, Billing, Customer center, Support, etc Single View of Individual Relationships Products and services Purchased Household Relationships Organizational Relationships Location Relationships Social Network Single View of Individual * * Individual could be a customer, prospect, victim, terrorist, etc Data integration Data cleansing (data quality) Data supplementation (Reference data) Data enrichment (geocoding) Master Data Management
  • 4. powered by Choosing Graph and Neo4j • Started with graph databases and Neo4j in 2010 • Early prototypes revealed key differentiators for MDM space • Why Neo4j? • Java • Multi-platform • High Performance • ACID • Market Leader
  • 5. powered by Best of Suite CIM • Platform approach must account for all key Customer Information Management functions • Data Quality • Data Integration • Data Enrichment • Master Data Management • Data Governance
  • 6. powered by Market Perspective • Gartner • On the rise in Hype Cycle reports • “The amount of business situations in which graphs constitute the ideal presentation framework is staggering” • Forrester • Hub for Context • “Much more intuitive, analytic, and intelligent for master data”
  • 7. powered by Demonstration - Spectrum Use Case – Master Data for Retail Marketing Analysis
  • 8. SAN FRANCISCO | 10.22.2014 powered by Thank You