This document advertises a webinar about planning cloud migrations with confidence. The webinar will discuss how graph analytics can help intelligently plan, execute, monitor, and optimize cloud migrations. It will feature presentations on graph databases for cloud migration, challenges of migration projects, and how to use a graph-based data warehouse tool to support migration efforts through execution, planning, monitoring and oversight capabilities. The webinar aims to help attendees avoid common pitfalls in migration projects and revolutionize analytics to gain benefits like greater adoption, confidence, reuse, and control of data quality and security.
3. 90%
of migration projects
experience disruptions
75%
of migration projects
don’t meet deadlines
INTEGRATE • MODEL • VISUALIZE • ANALYZE • ORCHESTRATE • AUTOMATE
4. INTEGRATE • MODEL • VISUALIZE • ANALYZE • ORCHESTRATE • AUTOMATE
Intelligently plan, execute,
monitor, and optimize your cloud
migration with graph analytics
5. Introduction to Graph for Cloud Migration with Neo4j
Sammy Dagher, Sales Engineer, Neo4j
Intelligent Cloud Migration
Phil Meredith, CEO & Founder, Process Tempo
Migration Challenges + Limitations: An Overview
Daria Chadwick, Marketer, Process Tempo
9. INTEGRATE • MODEL • VISUALIZE • ANALYZE • ORCHESTRATE • AUTOMATE
Having a clear understanding of what needs to be migrated and why
10. INTEGRATE • MODEL • VISUALIZE • ANALYZE • ORCHESTRATE • AUTOMATE
Collaboration and communication difficulties
11. INTEGRATE • MODEL • VISUALIZE • ANALYZE • ORCHESTRATE • AUTOMATE
• Generate as much as visibility as possible into your existing IT infrastructure
using the graph.
• Pre-migration: Establish scope only after you’ve established visibility.
• Mid-migration: Leverage graph to generate visibility and evaluate your current
scope before moving forward. You may have to make changes.
• Don’t forget about your people! Make their day-to-day work more productive
from both an individual perspective and a team one by providing them with
accurate, clean, and unified set of data and an effective way to collaborate on it.
12.
13. INTEGRATE • MODEL • VISUALIZE • ANALYZE • ORCHESTRATE • AUTOMATE
What is Neo4j?
The industry’s largest dedicated investment in Graph Database Ecosystem
Industry Leaders use Neo4j
Creator of the Labeled Property
Graph
Thousands of Customers World-
Wide
Graph Database Leader with
more than 50% of Market Share
Innovation Leader with Highest
concentration of Graph
Innovators, Experts, Analysts,
Developers and Publications
HQ in Silicon Valley, offices include
Boston, London, Munich, Paris, Malmo,
Sydney, Singapore, India, APAC
20 of 20 Top Financial Institutions
9 of 10 Top High Tech Companies (Including
those who have competitive products, use
Neo4j internally for their mission critical
applications)
7 of 10 Top Retailers
8 of 10 Top Insurance Companies
8 of 10 Top Automakers
3 of 5 Top Hotels
7 of 10 Top Telecoms
Global Governments - Civilian, Defense and
Intelligence using Neo4j EE to Analyze,
Optimize & Protect
14. MARRIED_TO
DRIVES
name: “Dan”
born: May 29, 1986
twitter: “@dan”
name: “Ann”
born: Dec 5, 1984
since:
Jan 10, 2017
brand: “Volvo”
model: “V70”
Nodes
• Represent the objects in the
graph
• Can have one or more labels
(noun)
Relationships
• Relate nodes by type (verb) and
direction
Properties
• Name-value pairs that can go
on nodes (adjective) and
relationships (adverb)
LOVES
LOVES
O
W
N
S
PERSON
CAR
LOVES
PERSON
since:
Jan 12, 2017
since:
Jan 10, 2017
15. Why Graph for Cloud
Migration?
• Modeling your infrastructure
as a graph enables you to:
–Plan
• Migration of applications to the
cloud
• Prioritize components for migration
–Execute
• Move applications/services/APIs to
the cloud without any loose end
dependencies
–Monitor
• Have a blueprint for your cloud/on-
prem hybrid infrastructure going
forward
16. Examples of Cloud Migration
• Infrastructure-first approach
–Shutting down a data center
–Moving applications from one data center
to another
–Retiring hardware that hosts custom
software
• Application-first approach
–Choosing “cloud ready” applications first
–Prioritizing applications with less
influence/dependencies
–Prioritizing more critical business
applications first
18. Data Center A
Server Server
Server
Server
Server
Server
Server
Server
Server
Server
Application
Application
Application
API
19. Pathfinding &
Search
• Shortest Path
• Single-Source Shortest Path
• All Pairs Shortest Path
• A* Shortest Path
• Yen’s K Shortest Path
• Minimum Weight Spanning Tree
• K-Spanning Tree (MST)
• Random Walk
• Breadth & Depth First Search
Centrality &
Importance
• Degree Centrality
• Closeness Centrality
• Harmonic Centrality
• Betweenness Centrality & Approx.
• PageRank
• Personalized PageRank
• ArticleRank
• Eigenvector Centrality
• Hyperlink Induced Topic Search (HITS)
• Influence Maximization (Greedy, CELF)
Community
Detection
• Triangle Count
• Local Clustering Coefficient
• Connected Components (Union
Find)
• Strongly Connected Components
• Label Propagation
• Louvain Modularity
• K-1 Coloring
• Modularity Optimization
• Speaker Listener Label Propagation
Supervised
Machine
Learning
• Node Classification
• Link Prediction
… and more!
Heuristic Link
Prediction
• Adamic Adar
• Common Neighbors
• Preferential Attachment
• Resource Allocations
• Same Community
• Total Neighbors
Similarity
• Node Similarity
• K-Nearest Neighbors (KNN)
• Jaccard Similarity
• Cosine Similarity
• Pearson Similarity
• Euclidean Distance
• Approximate Nearest Neighbors
(ANN)
Graph
Embeddings
• Node2Vec
• FastRP
• FastRPExtended
• GraphSAGE
• Synthetic Graph Generation
• Scale Properties
• Collapse Paths
• One Hot Encoding
• Split Relationships
• Graph Export
• Pregel API (write your own algos)
20. • PageRank Algorithm
– Measures the importance of each node
within the graph, based on the number
incoming relationships and the importance
of the corresponding source nodes.
– Used to create “Complexity” score
Application
Application
Application
Application
Application
Highest “Complexity”
23. Challenges to Successful Migrations
Multiple parties involved
• Architecture
• Finance
• Development
• SMEs
Obscurity
• Multiple disconnected systems
• Multiple environments
• Disconnected processes
Continuous change
• Internal resistance
• Poor data quality
24. What is Needed
Executive Sponsorship
• A vision and a roadmap
• A clear value statement
• Attainable milestones
• Executive oversight
Clarity
• A single source of truth
• A common language
• A common data model
• Dependency and Impact Analysis
Effective Coordination
• Multiple teams involved
• Multiple, overlapping processes
• A common platform
Adaptability
• Change is constant
• A no-code approach
25. Amazing things
happen at the
intersection of:
• Modern Data Warehousing
• Integrated Governance
• Self-Service Dashboards
• Embedded Workflow
Greater
Adoption
Greater
Confidence
Greater
Reuse
Greater
Control
Data
Quality
Data
Security
Data
Consistency
Data
Value
Self-Service
Dashboards &
Reports
Modern Graph
Data Warehouse
Integrated
Governance
Embedded
Workflow
What is Process Tempo
26. How We Help Support Migration
Efforts
Execution
• Workflow
• Knowledge capture
• Alerting
Planning & Optimization
• We address complexity
• Collaboration across teams
Monitoring and Oversight
• Executive Dashboards
• Stakeholder Dashboards
• Exception Reporting
27. How We Help Support Migration
Efforts
Versus
• Disconnected
• Error Prone
• Limited
• Integrated
• Accurate
• Interactive
• Secure
28. How it works
<- - Write Back - -
Data Scientists |
Data Engineers |
Administrators |
| Planners
| Executives
| Stakeholders
Dashboard
Form
30. • Put Your Supply Chain Data To Work
• Reduce API Security Risk with Graph Analytics
• Plan Your Cloud Migration with Confidence
Webinar Series: Revolutionizing Business
Analytics with Graph Applications
Watch back on processtempo.com
Get started by scheduling a call: calendly.com/processtempo