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Introduction to Neo4j for the Emirates & Bahrain

Gal Bello, Neo4j

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Introduction to Neo4j for the Emirates & Bahrain

  1. 1. Gal Bello Field Engineer, Israel Feb, 2021
  2. 2. Agenda ❏ Hello! ❏ Neo4j, The Graph Company ❏ Our Technology ❏ Graph Data Science ❏ Neo4j in the Cloud ❏ Success Stories ❏ Demo! ❏ Q&A
  3. 3. Gal Bello Field Engineer, Israel Tagline: “Try! At max, you'll - succeed”
  4. 4. 7/10 20/25 7/10 Top Retail Firms Top Financial Firms Top Software Vendors Anyway You Like It Neo4j - The Graph Company The Industry’s Largest Dedicated Investment in Graphs Creator of the Property Graph and Cypher language at the core of the GQL ISO project Thousands of Customers World-Wide HQ in Silicon Valley, offices include London, Munich, Paris & Malmo Industry Leaders use Neo4j On-Prem DB-as-a-Service In the Cloud
  5. 5. A graph is set of discrete objects, each of which has some set of relationships with the other objects Seven Bridges of Konigsberg problem. Leonhard Euler, 1735
  6. 6. Graph is the Fastest Growing DBMS Category, Neo4j is the Leading Player FASTEST GROWING CATEGORY MOST POPULAR WITH DEVELOPERS STRONGEST COMMUNITY Developers LinkedIn Skills 41k+ members with 220k+ Meetups 72k+ Members globally
  7. 7. Highest possible scores in: ● Performance ● Scalability ● Workloads ● Data management ● Data loading/ingestion ● Queries/search ● Use cases ● API/extensibility ● Transactions ● High availability and disaster recovery ● Deployment options The Forrester WaveTM is copyrighted by Forrester Research, Inc. Forrester and Forrester Wave are trademarks of Forrester Research, Inc. The Forrester Wave is a graphical representation of Forrester's call on a market and is plotted using a detailed spreadsheet with exposed scores, weightings, and comments. Forrester does not endorse any vendor, product, or service depicted in the Forrester Wave. Information is based on best available resources. Opinions reflect judgment at the time and are subject to change. Neo4j: Leading the Graph Market
  8. 8. Connections in Data are as Valuable as the Data Itself
  9. 9. Harnessing Connections Drives Business Value Enhanced Decision Making Hyper Personalization Massive Data Integration Data Driven Discovery & Innovation Product Recommendations Personalized Health Care Media and Advertising Fraud Prevention Network Analysis Law Enforcement Drug Discovery Intelligence and Crime Detection Product & Process Innovation 360 view of customer Compliance Optimize Operations Data Science AI & ML Fraud Prediction Patient Journey Customer Disambiguation Transforming Industries
  10. 10. tolerates many real-world conditions which RDBMS can not “Finding relationships in combinations of diverse data, using graph techniques at scale, will form the foundation of modern data and analytics.” clear market leader a lot more innovative than its competitors Graph is a Unique Advantage
  11. 11. Enterprise-grade native graph database and tooling: • Store, reveal and query data relationships • Traverse and analyze any levels of depth in real-time • Add context to AI systems and network structures to data science Native Graph Technology • • • • • • • •
  12. 12. Neo4j Graph Database Platform
  13. 13. Index Free Adjacency
  14. 14. Conceive Code Compute Store Non-Native Graph DB Native Graph DB RDBMS Connectedness Differentiates Neo4j
  15. 15. Property Graph - Simply Powerful Employee City Company Nodes represent objects (nouns) Relationships are directional Relationships connect nodes are represent actions (verbs) Relationships can have properties (name/value pairs) Nodes can have properties (name/value pairs) name: date_of_birth: employee_ID: :HAS_CEO start_date: :LOCATED_IN
  16. 16. Nodes • Can have Labels to classify nodes • Labels have native indexes Relationships • Relate nodes by type and direction Properties • Attributes of Nodes & Relationships • Stored as Name/Value pairs • Can have indexes and composite indexes • Visibility security by user/role Neo4j Invented the Property Graph Model
  17. 17. Graph Databases: Designed for Connected Data RELATIONAL DATABASES NoSQL DATABASES Real-Time storage & retrieval Real-Time Connected Insights Long running queries aggregation & filtering “Our Neo4j solution is literally thousands of times faster than the prior MySQL solution, with queries that require 10-100 times less code” Volker Pacher, Senior Developer
  18. 18. for Graph Data Science™ Neo4j Graph Data Science Library Scalable Graph Algorithms & Analytics Workspace Native Graph Creation & Persistence Neo4j Database Visual Graph Exploration & Prototyping Neo4j Bloom Practical Integrated Intuitive
  19. 19. Robust Graph Algorithms • Compute connectivity metrics and learn the topology of your graph • Highly parallelized and scale to 10’s of billions of nodes The Neo4j GDS Library Mutable In-Memory Workspace Computational Graph Native Graph Store Efficient & Flexible Analytics Workspace • Automatically reshapes transactional graphs into an in-memory analytics graph • Optimized for analytics with global traversals and aggregation • Create workflows and layer algorithms
  20. 20. • Degree Centrality • Closeness Centrality • Harmonic Centrality • Betweenness Centrality & Approx. • PageRank • Personalized PageRank • ArticleRank • Eigenvector Centrality • Triangle Count • Clustering Coefficients • Connected Components (Union Find) • Strongly Connected Components • Label Propagation • Louvain Modularity • Balanced Triad (identification) • 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 • Triangle Count • Local Clustering Coefficient • Connected Components (Union Find) • Strongly Connected Components • Label Propagation • Louvain Modularity • K-1 Coloring • Modularity Optimization • Euclidean Distance • Cosine Similarity • Node Similarity (Jaccard) • Overlap Similarity • Pearson Similarity • Approximate KNN Pathfinding & Search Centrality / Importance Community Detection Similarity Link Prediction • Adamic Adar • Common Neighbors • Preferential Attachment • Resource Allocations • Same Community • Total Neighbors ... Auxiliary Functions: • Random graph generation • Graph export • One hot encoding • Distributions & metrics Embeddings • Node2Vec • Random Projections • GraphSAGE
  21. 21. Strong Synergy between Graphs and Machine Learning & AI SURGING INTEREST CONTEXT FOR ML/AI AI research papers focused on graphs +100K Download, 20K in first 2 weeks ACROSS INDUSTRIES German Center for Diabetes Research Better Decisions with Knowledge Graphs for AI Higher ML Accuracy with Graph Feature Engineering
  22. 22. Neo4j Bloom’s Intuitive User Interface Search with type-ahead suggestions Flexible Color, Size and Icon schemes Visualize, Explore and Discover Pan, Zoom and Select Property Browser and editor
  23. 23. Designed for Enterprise-Grade Workloads Scalability Security Flexibility
  24. 24. The First Practical Way for Enterprises to do Graph Data Science Drastically simplified and standardized API that enables custom, flexible configurations Documentation, training, and examples so getting started is simple Explore graphs and algorithm results visually with Bloom Share insights across teams for better collaboration Friendly data science experience with logical guardrails like memory mgmt. & suggestive errors Reshaping, node & relationship aggregation / deduplication and multipartite algos
  25. 25. Explore & Collaborate with Neo4j Bloom Explore Graphs Visually Prototype Concepts Faster Collaborate Across Teams
  26. 26. Neo4j Solution Frameworks Accelerated POCs and Adoption Intelligent Recommendation Risk Management Human Capital Management Privacy Shield Data Orchestration
  27. 27. Neo4j Cloud: Flexible Deployment Models Fully-managed SaaS Consumption-based pricing Cloud-native Self-service deployment No access to underlying infrastructure and systems White-glove managed service by Neo4j experts Fully customizable deployment model and service levels Operate In own data centers or Virtual Private Cloud Database-as-a-Service Cloud Managed Services (CMS) For private, hybrid or lift-and-shift cloud Bring-your-own-license Full control of your environment Run in any cloud, in your account Self-hosted
  28. 28. The world’s most popular graph database, as a cloud service Fully automated with zero administration Faster innovation with the power of graphs Scalable on-demand dynamically Worry-free security and reliability Simple pay-as-you-go pricing
  29. 29. Neo4j Aura: Built for the best developer experience Neo4j’s open source roots backed by the strongest graph community helps deliver the best developer experience to rapidly build rich graph-powered applications Easy Start in minutes Automatic upgrades, patches Scale on-demand instantly Zero downtime Powerful Lightning-fast queries with Native graph engine Flexible “whiteboard” data model Cypher - expressive, efficient and easy! Broad language driver support Reliable End-to-end encrypted Always ON Globally available on world-class infrastructure Self-healing, durable ACID compliant Affordable Pay-as-you-go Capacity-based pricing Billing by the hour Simple and predictable costs
  30. 30. Minka Neo4j for ACH Transaction Processing Background ● Minka, a Colombian fintech startup, along with ACH Colombia modernizing the country’s ACH payments system ● Enable real-time payments transactions with a new Blockchain based system, Transferencias Ya Business Problem ● Need to convert an outdated batch processed ACH to the new system and scale ● Need a robust, durable solution with guaranteed ACID transactions to build trust among users Solution and Benefits ● Aura powers transaction records and references for Transferencias Ya ● With Aura, day to day operations taken care of while system reliably operates and scales ● Pilot with 8 banks successful, expanding to all 27 banks supporting hundreds of complex transactions every second
  31. 31. Neo4j Cloud Managed Services (CMS) Enterprise-class, white-glove managed services for day-to-day operations, service and support of your Neo4j environment Dedicated team, always on-call Advanced monitoring and preventative maintenance Enterprise-grade security and compliance 24x7x365 remote services and support Public or Private Cloud Deployments Your data in your infrastructure, fully controlled versioning
  32. 32. The CMS Advantage Focus on Innovation … while we manage your day-to-day infrastructure operations Achieve Faster Time-to-value … with experts to manage your environment from day one. Minimize hiring, in-house training, and ramp-up. Reduce your Risk … and meet your security, compliance and business continuity needs with proven best practices. Accelerate your Cloud Journey … by enabling a fully managed enterprise cloud environment and moving your production Neo4j environment within days.
  33. 33. Highly Valuable Connected Data Use Cases Drive Enterprise Adoption
  34. 34. Handling Large Graph Workloads for Enterprises Real-time promotion recommendations Marriott’s Real-time Pricing Engine Handling Package Routing in Real-Time
  35. 35. Improving Analytics, ML & AI Across Industries Meredith Marketing to the Anonymous Financial Fraud Detection & Recovery Top 10 Bank AstraZeneca Patient Journeys
  36. 36. Dun & Bradstreet Neo4j for Tracking Beneficial Ownership Background ● Regulations and requirements around beneficial ownership ● Needed to let B2B clients book new business promptly via accelerated due diligence investigations Business Problem ● Investigations call for highly trained staff, and this activity is hard to scale. A single request might tie up key people for 10-15 days, resulting in lost revenue Solution and Benefits ● Use Neo4j to quickly query historic relationships between business owners and companies ● Query responses take milliseconds versus days of skilled manual research
  37. 37. Adobe Behance Social Network of 10M Graphic Artists Background ● Social network of 10M graphic artists ● Peer-to-peer evaluation of art and works-in-progress ● Job sourcing site for creatives ● Massive, millions of updates (reads & writes) to Activity Feed ● 150 Mongos to 48 Cassandras to 3 Neo4j’s! Business Problem ● Artists subscribe, appreciate and curate “galleries” of works of their own and from other artists ● Activities Feed is how everyone receives updates ● 1st implementation was 150 MongoDB instances ● 2nd implementation shrunk to 48 Cassandras, but it was still too slow and required heavy IT overhead Solution and Benefits ● 3rd implementation shrunk to 3 Neo4j instances ● Saved over $500k in annual AWS fees ● Reduced data footprint from 50TB to 40GB ● Significantly easier to introduce new features like, “New projects in your Network”
  38. 38. US Army / Calibre Systems Equipment Logistics Background ● US IT consulting firm helped US Army streamline equipment deployments and maintenance spending ● Saving lives by improving the operational readiness of Army equipment like tanks, radios, transports, aircraft, weaponry, etc. Business Problem ● Needed to modernize procurement, budget and logistics processes for equipment & spare parts ● Millions of connections among a tank’s bill-of-materials, for example ● Improve “what if” cost calculations when planning missions and troop deployments ● Mainframe systems required over 60 man-hrs to calculate changes… planning took too long Solution and Benefits ● Shed cost estimation times by 88% ● Improved parts delivery timing and accuracy ● DBA labor required dropped by 77% ● Equipment TCO more predictable ● Safer soldiers
  39. 39. COMCAST Xfinity xFi Smart Home/ IoT Background ● Largest Cable TV & Internet Provider in US with 3rd Largest network on the planet ● xFi is consumer experience in 3M houses with internet, router, devices, security, voice & telephony Business Problem ● Integrate all experience in a smart home ● Create innovative ideas based on cross-platform and household member preferences ● Add integrated value of xFinity triple play & quad-play services (internet, VoIP, cable TV & home security) Solution and Benefits ● Custom content per household member ● Security reminders (kids are home, garage left open) ● Serves millions of households ● Makes content recommendations based on occupant, time of day, permissions and preferences
  40. 40. Caterpillar Heavy Equipment Manufacturing Background ● Fortune 100 heavy equipment manufacturer ● 27 Million warranty & service documents parsed Business Problem ● Improve maintenance predictability ● Need a knowledge base for 27 million warranty documents and maintenance orders ● Graphs gather context for AI to identify ‘prime examples’ of connections among parts, suppliers, customers and their mechanics anticipate when equipment will need servicing and by whom Solution and Benefits ● Knowledge graph created through Natural Language Processing (NLP) of decades of historical service documents ● Common ontology for complaints, symptoms & parts ● Anticipates when equipment will need servicing ● Improves customer and brand satisfaction ● Maximizes lifespan and value of equipment
  41. 41. Meredith Inc. Digital Media Identity Resolution Background ● Media conglomerate with $3.2 Billion revenue ● Owner of popular web properties including: People, Travel+Leisure, Better Homes & Gardens Business Problem ● Users are often anonymous across sites and devices with online cookies that constantly change ● External data is expensive, hard to validate and quickly suffers from cookie loss ● Poor understanding of visitor behavior reduces recommendation effectiveness, leading to fewer clicks and less revenue Solution and Benefits ● 612% Increase in visits tracked per profile ● 4.4 TB of data: +14 Bn nodes +20Bn relationships ● Graph algorithms to find data “clusters” that represent unique user behavior ● Transformed 346M cookies to 163M unique users with richer & longer lived profiles ● Connecting various data streams for continuous user identification
  42. 42. AstraZeneca Patient Journey Analytics Background ● Global pharmaceutical with $22.1Billion revenue ● Focus on oncology, cardiovascular, renal, metabolism, respiratory Business Problem ● Complex diseases develop over years with many, many doctor visits, tests and evolving diagnosis ● How to identify early warnings, intervene faster & improve outcomes ● No two patients are the same, so how are similarities found Solution and Benefits ● Used Neo4j Graph Data Science Library to map and predict patient journeys ● Kidney disease intervention project ● 3 yrs of visits, tests & diagnosis with 10’s of Bn of records ● Knowledge Graph, graph queries & algorithms ● Community detection to help find similarities over time ● Finding influence points where experienced physicians may be able to guide and assist
  43. 43. Neo4j Leadership and Commitment First mover advantage and product maturity Thriving ecosystem; world’s largest graph community & partner network Thought leadership and vision Deep IP that is difficult to replicate Proven GTM success with Enterprise - referenceable case studies from marquee customer base and track record of customer success, stickiness & expansion Runs everywhere – all major cloud environments, hybrid & private clouds, on-premise and OEM embedded
  44. 44. Appendix
  45. 45. Neo4j—The Graph Innovator
  46. 46. Adapt & Optimization by Harnessing Connections Hyper- Personalization Better Decisions Massive Data Integration Data Science AI & ML Data Driven Discovery & Innovation
  47. 47. Neo4j Graph Platform
  48. 48. Neo4j — Changing the World Knowledge Graph for humans & ML Fraud Detection Knowledge Graph for humans
  49. 49. eBay App for Google Assistant Online Retail Background ● Personal shopping assistant ● Converses with buyer via text, picture and voice to provide real-time recommendations ● Combines AI and natural language understanding (NLU) in Neo4j Knowledge Graph ● First of many apps in eBay's AI Platform Business Problem ● Improve personal context in online shopping ● Transform buyer-provided context into ideal purchase recommendations over social platforms ● "Feels like talking to a friend" Solution and Benefits ● 3 developers, 8M nodes, 20M relationships ● Needed high-performance traversals to respond to live customer requests ● Easy to train new algorithms and grow model ● Generating revenue since launch
  50. 50. ● Operational workloads ● Analytics workloads ● Native property graph model ● Dynamic schema ● Cypher - Declarative query language ● Procedural language extensions ● Worldwide developer community ● Manage 10’s billions of nodes ● Run graph algorithms on billions of nodes Your Neo4j Advantage ● Index-free adjacency ● Millions of hops per second ● Interactive graph exploration ● Graph representation of data
  51. 51. Neo4j Solutions [accelerate adoption] Solutions Mission Ideate, market and support the sale and delivery of innovative, market-leading, Neo4j-based Business Solutions for our Enterprise Customers and Partners Customer Benefits Lowers Risk and TCO Speeds up POCs & solution visualization for internal selling Rapid Time-To-Value, reduces development & testing time by 50% Built on extensible & customizable frameworks supported by Neo4j
  52. 52. Patient Journey Human Capital Management Fraud & AML Framework Supply Chain Framework Hive Knowledge Graph • Content management • Collaboration & reuse • Analytical tools for increasing enterprise efficiency • Workforce rebalancing & analysis • Skills assessment • Predict employee flight risk, plan successions, analyze lifetime value • Unintended drug efficacy • Journey map & prediction • At-risk population identification • Procedure risk score • Reduce false positives • Find collaborators & rings • Support compliance and investigations • Outbound supply chain logistics • Route planning and network analysis
  53. 53. Cypher Workbench Risk Management Keymaker (Applied Analytics Pipeline) • Cloud modeling environment • Online and offline modes • Collaboration features • Model validation and constraints • Investment / Credit / Party Risk Management • Compliance (FRTB, BCBS 239, CCAR, BASEL) • Faster decisions using suggestions / predictions • Combine ML & Connected Data analysis into single analytics pipeline • Hyper-Personalization • Explainable scored results • Highly performant & scalable architecture Kettle/HOP for Neo4j • Privacy compliance (GDPR, CCPA, LGPD, FCPL, …) Privacy Shield • Fast visual data ingestion pipeline development • Support for most popular data sources out of the box • Templated best practice pipelines • Maintainability of ingestion logic • Citizen journey / 360 • Pseudo-anonymization
  54. 54. ❏ Try It: ❏ Learn It: ❏ Join Us: ❏ Contact Us: ❏ Linked In: @Gal Bello