Jesus Barrasa, Neo4j GraphTalk Helsinki

1. Next-Generation Solutions
with Neo4j
GraphTalk - Helsinki - 3rd October 2018
Dr. Jesús Barrasa - @BarrasaDV
Director Telecom Solutions

2. Two of the world’s three largest CSPs
have chosen to adopt Neo4j to build
mission critical solutions.

3. Half of the 2018 leaders of the Gartner
Magic Quadrant for OSS embed Neo4j in
their key products.

4. Two of the Top five US multichannel video
service providers have chosen Neo4j to
build key customer centric solutions

5. IoT OSS/BSS
Governance &
Metadata Mgmnt
IAM &
Fraud Analysis
Common Graph Use Cases in Telco
Digital
Transformation
• Smart Homes • Assurance
• Fulfilment
• CRM/Support
• Planning &
Optimisation
• Regulatory
compliance
• Data Lineage
• Consent Mgmnt
• Identity &
Access Mgmnt
• CJA / CEM
• Customer 360
• Eligibility Engine

6. why?

7. Shared Requirements
Capture Complexity
Allow Flexibility
High Performance
Bridge Business - IT gap
Rich, Dynamic, human
friendly Graph Model on
a Native Graph Platform

8. ”Graph analysis is possibly the single most effective
competitive differentiator for organisations pursuing
data-driven operations and decisions“

9. Graph Thinking

10. Audience Experiment:
Dependency modelling

11. Look at this data…
Element Depends On
A B
A C
A D
C H
D J
E F
E G
F J
G L
H I
J N
J M
L M

12. Element Depends On
A B
A C
A D
C H
D J
E F
E G
F J
G L
H I
J N
J M
L M
Time challenge #1: Does A depend on F ?
?

13. Look at this data again…

14. Time challenge #2: Does E depend on M ?
?
M
E

15. MATCH (a:Element { id: “A”})
MATCH p = (a)-[:DEPENDS_ON*]->(n { id: “N”})
RETURN p
SELECT
d1.ElementId, d2.ElementId, d3.ElementId
FROM dpndncs AS d1
INNER JOIN dpndncs AS d2
ON d1.dependsOnElemId = d2.ElemId
INNER JOIN dpndncs AS d3
ON d2.dependsOnElemId = d3.ElemId
… <arbitrary number of joins>…
WHERE d1.ElementId = “A”
AND d3.ElementId = “N”
Element Depends On
A B
A C
A D
C H
D J
E F
E G
F J
G L
H I
J N
J M
L M
Does X depend on Y ?

16. Is X affected by a failure in Y?
Does X depend on Y ?
=

17. Things get more complicated: Detecting SPOFs

18. Detect the SPOF for Element E

19. (spof)<-[:DEPENDS_ON*]-(x:Element)-[:DEPENDS_ON*]->(spof)
Detect the SPOF on a graph?

20. SPOF on tables anyone ?
ElemId dependsOnElemId
A B
A C
A D
C H
D J
E F
E G
F J
G L
H I
J N
J M
L M

21. Service
Assurance
Traffic
Engineering

22. We have a complex multilayer network and
we have two problems: 1. Design + Planning
2. Fault Management
Build me a graph!

23. Route oriented Model
Shortest/most efficient path from A to B
Find diverse routes between A and B

24. Route oriented Model

25. Dependency oriented Model

26. Dependency oriented Model

27. Dual Model

30. Neo4j
Bloom
Custom Viz
Third party BI tool
Neo4j Browser

31. Traffic Engineering
Diverse Routing
?

32. Traffic Engineering
Diverse Routing
Path Analysis
Least cost path from A to B
+
Dependency Analysis
No shared underlying
resources

33. Network Planning Example

34. CALL spatial.closest('l1', $origin , 0.3) YIELD node AS oN
CALL spatial.closest(‘l1', $dest , 0.3) YIELD node AS dN
MATCH shortest = shortestPath((oN)-[r:LINK*..5]-(dN))
RETURN *
Combining Geospatial with path exploration

35. CALL spatial.closest('l1', $origin , 0.3) YIELD node AS oN
CALL spatial.closest(‘l1', $dest , 0.3) YIELD node AS dN
MATCH shortest = shortestPath((oN)-[r:LINK*..5]-(dN))
RETURN *
Combining Geospatial with path exploration

36. CALL spatial.closest('l1', $origin , 0.3) YIELD node AS oN
CALL spatial.closest(‘l1', $dest , 0.3) YIELD node AS dN
MATCH shortest = shortestPath((oN)-[r:LINK*..5]-(dN))
RETURN *
Combining Geospatial with path exploration

37. CALL spatial.closest('l1', $origin , 0.3) YIELD node AS oN
CALL spatial.closest(‘l1', $dest , 0.3) YIELD node AS dN
MATCH shortest = shortestPath((oN)-[r:LINK*..5]-(dN))
RETURN *
Combining Geospatial with path exploration

39. 🏦 :DEPENDS_ON
:DEPENDS_ON
:DEPENDS_ON
IF/AX2431
💥
Customer
Event Correlation
Event Prioritisation
Fault Management
(Deep) Impact/Root Cause Analysis

40. MATCH (fe:Link { linkId: $id})<-[:CARRIED_BY*]-(s:Service)
RETURN max(s.priority) AS severity
(Deep) Impact/Root Cause Analysis
{ alarmType: “LOS”,
notifyingEntity: “IF/AX/0/3”, …}

41. Graph Size: ~50M nodes (avg depth: 6)Graph Size: ~1K nodes (avg depth: 5)
Simulation: 128 clients, synchronous requests with1ms wait between requests
AT SCALE
50000x increase in size of dataset -> 1.14x impact in query performance
Graph Native Matters!!!
(Deep) Impact/Root Cause Analysis

42. Customer Journey Analysis

43. What is CJA?
4

44. Why is CJA important?
Because customers…
have an improved opinion of businesses that
remember previous interactions with them
value personalised and relevant information

45. Why is CJA important?
Because organisations…
want to give managers an overview of the
customer’s experience
want to uncover and solve gaps between
channels, departments, devices... bringing
significant business value

46. Three recurring concepts:
CUSTOMER
TIME
MULTICHANNEL

47. The tool: Customer Journey Maps

48. “ Journey maps are based largely on the assumption
that customer experience is unchanging and
controllable, and thus can be captured as a
standardised process. But a customer’s journey isn’t a
simple and finite series of steps: it’s a complex and
sometimes contradictory set of interactions over
multiple channels. Map that! ”
Jonathan Browne. Forrester Research

49. ActiveCJM on Neo4j
Visualisable
Flexible & Dynamic
Agile
Actionable
Identification of key milestones in
relevant journeys
JOURNEY
DISCOVERY/DESIGN
Identifying & connecting relevant
data sources
DATA COLLECTION
Construction of automated DD
integrations.
-> Next best action, Notifications,
Recommendations, etc
BUILD AUTOMATED
INTERACTIONS

50. Demo

51. CRM
Service
Usage
Helpdesk
Incidents &
service
perf.
Marketing
Automated
Processing
Analysis Active Predictive Model
Recommendations
Next Best Accion
Active
CJM

52. Conclusions

53. Graph thinking : Rethink your problem as a graph
Graph: Efficient / flexible / expressive
representation of your data
Graph Native Matters!
Neo4j platform gives you a head start

54. Kiitos!