Download pptx - Graph Thinking: Why it Matters

Graph ThinkingAndreas Kollegger

Product Designer

Graph Thinkingthe missing link

in your data

Chilenje ClinicLusaka, Zambia

• Patient Care

• Decision Support

• Public Health Research

• WHO Reporting

Medical Record System

• Current data

• Prior history

• Local context

• How is the data related?

• What patterns emerge from the relationships?

• Which patterns matter?

• "Assessment" makes connections, creating new data

How does this work?

Some datais missing...

• Epidemiology

• Cultural Norms

• Environmental Factors

• Agricultural Practices

• Patient Relationships

• Doctor Relationships

• Related Research

• ...

How much datado you need?

"The person with the most data, wins."

– Tim O'Reilly

1. Close relationships determinerelevance

Number of relationships increases importance

What datado you need?

Naturally, that leads topattern matching...

The internet

Genetic Ancestry of One Single Corn Variety

Andreas' Linkedin Network

Andreas Kollegger

Graph Thinking has created some of the most successful companies in the world

WHAT IS A GRAPH?

A way of representing data

DATA DATA

Relational Database

Good for: Well-understood data

structures that don’t change too frequently


Known problems involving discrete parts of the data, or

minimal connectivity

Graph Database

Relational Database

Good for: Well-understood data

structures that don’t change too frequently

Known problems involving discrete parts of the data, or

minimal connectivity


Good for: Dynamic systems: where the data topology is difficult to

predictDynamic requirements:

the evolve with the business Problems where the relationships in data contribute

meaning & value

THE PROPERTY GRAPH DATA

MODEL

A Graph Is

ROAD

TRAFFIC

LIGHTS

A Graph Is

HA

S

AVAILABLE

HOTEL

ROOMS

AVAILABLE

A Graph Is

KNOWS

KN

OW

S

KNOWS

WO

RK

S_AT

WORKS_AT

WORKS_AT

COMPANY

STANFORD

STU

DIE

D_A

T

KNOWS

NEO

COLUMBIA

STU

DIE

D_A

T

STUDIED_AT

STUDIED_AT

NAME:ANNE

A Graph

SINCE:2012

RELATIONSHIPS

NODE

PROPERTY

A Graph

NAME:ANNE

SINCE:2012

Graph Thinking in PracticeReal Time Recommendations

Master Data Management

Fraud Detection

Identity & Access Management

Graph Based SearchNetwork & IT-Operations



Fraud Detection



VIEW

ED

GRAPH THINKING:Real Time Recommendations

VIEWED

BOUG

HT

VIEWED BOUGHT

BOUGHT

BO

UG

HT

BOUG

HT

“As the current market leader in graph databases, and with enterprise features for scalability and availability, Neo4j is the right choice to meet our demands.” Marcos Wada

Software Developer, Walmart

Graph Thinking with Neo4jReal Time Recommendations


Fraud Detection





Fraud Detection



GRAPH THINKING:Master Data Management

MANAGES

MANAGES

LEADS

REGION

MANAGES

MANAGES

REGION

LEADS

LEADS

COLL

ABO

RATE

S

Neo4j is the heart of Cisco HMP: used for governance and single source of truth and a one-stop shop for all of Cisco’s hierarchies.



Fraud Detection





Fraud Detection



OPENED_ACCOUNT

HAS IS_ISSUED

GRAPH THINKING:Fraud Detection

HA

S

LIVES LIVES

IS_ISSUED

OPE

NED

_AC

COUN

T

“Graph databases offer new methods of uncovering fraud rings and other sophisticated scams with a high-level of accuracy, and are capable of stopping advanced fraud scenarios in real-time.”

Gorka SadowskiCyber Security Expert



Fraud Detection



GRAPH THINKING:Graph Based Search

PUBLISH

INCLUDE

INCLUDE

CREATE

CAPT

URE

IN

INSO

URCE

USES

USES

IN

IN

USES



Fraud Detection



SOURCE SOURCE

Uses Neo4j to manage the digital assets inside of its next generation in-flight entertainment system.



Fraud Detection





Fraud Detection



BROWSES

CONN

ECTS

BRIDGES

ROUTES

POW

ERS

ROUTES

POWERSPOWERS

HOSTS

QUERIES

GRAPH THINKING:Network & IT-Operations

Uses Neo4j for network topology analysis for big telco service providers



Fraud Detection



GRAPH THINKING:Identity And Access Management

TRUSTS

TRUSTS

ID

ID

AUTHENTICATES AUTH

ENTI

CATE

S



Fraud Detection



OWNS

OWNSC

AN

_REA

D

UBS was the recipient of the 2014 Graphie Award for “Best Identify And Access Management App”



Fraud Detection



WHY GRAPH THINKING?

IntuitivnessSpeedAgility


Intuitivness


Speed

“We found Neo4j to be literally thousands of times faster than our prior MySQL solution, with queries that require 10-100 times less code. Today, Neo4j

provides eBay with functionality that was previously impossible.”- Volker Pacher, Senior Developer

“Minutes to milliseconds” performanceQueries up to 1000x faster than RDBMS or other

NoSQL


A Naturally Adaptive ModelA Query Language Designed

for Connectedness

+

=Agility

CypherTypical Complex SQL Join The Same Query using Cypher

MATCH (boss)-[:MANAGES*0..3]->(sub), (sub)-[:MANAGES*1..3]->(report)WHERE boss.name = “John Doe”RETURN sub.name AS Subordinate, count(report) AS Total

Project ImpactLess time writing queries• More time understanding the answers• Leaving time to ask the next question

Less time debugging queries: • More time writing the next piece of code• Improved quality of overall code base

Code that’s easier to read:• Faster ramp-up for new project members• Improved maintainability & troubleshooting

Ann DanLoves

CYPHER

Ann DanLoves

Ann DanLoves

(Dan)(Ann) -[:LOVES]->

Ann DanLoves

(:Person {name:”Ann"}) –[:LOVES]-> (:Person {name:"Dan"})

Ann DanLoves

(:Person {name:”Ann"}) –[:LOVES]-> (:Person {name:"Dan"})

Ann DanLoves

Node Relationship Node

(:Person {name:"Ann"}) –[:LOVES]-> (:Person {name:"Dan"})

Query: Whom does Ann love?

MATCH (:Person {name:"Ann"})–[:LOVES]->(whom)

RETURN whom

Users Love Cypher

Graph Thinkingfocuses on relationships

to turn data into informationand uses patterns to find meaning

It's all about relationships & patterns

THANK YOU!