GraphTour 2020 - Customer Journey with Neo4j Services

•

0 likes•153 views

This document provides an overview of Neo4j's customer journey and solutions for working with graph databases. It includes sections on problem identification and modeling sessions, desired business outcomes and data integration. It also shows examples of graph queries and discusses architecture, sizing and implementation considerations. The document aims to illustrate Neo4j's full end-to-end process for helping customers adopt graph databases from initial problem assessment through solution delivery.

Yossi Krichli
Country Manager - Israel
Yossi.krichli@neo4j.com
Gal Bello
Field Engineer Lead - Israel
Gal.Bello@neo4j.com

2
Problem Consider Decide Release Solution
Awareness Evaluate Implement Adopt Advocate
Innovation Lab
Modelling session
Project Reference
Bootcamp
Proof of concept
Solution design
Expert Services
Staff Augmentation
Project delivery
Solution Audit
Upgrade
Neo4j Solutions
Cloud managed
services
Neo4j – Customer Journey – The full picture

4
“Graph Problem Problem”
Use Case - Design Thinking
Data Modelling - Entities, Relationship, Properties
“Money Queries” - Desired Business outcome
Data Integration - ETL (data injection)
Architecture Overview – Scaling, Performance, Sizing
Prototyping
“From (Graph) Problem to a Solution”

7
Customers
RELATIONAL
DB
Insurance
Policies
DOCUMENT
STORE
WIDE
COLUMN
STORE
Marketing
DB
DOCUMENT
STORE
Life
Insurance
RELATIONAL
DB
Car
Insurance
Internet/
Direct
Insurance
KEY VALUE
STORE
Connector
Apps and Systems
Real-Time
Queries
Combining Disparate
Data Silos
Leverage Cross-Silo
Connections
Provide an integrated
view to overcome
challenges of legacy
systems
Data Integration (injection)

$9 “Money Queries” - Cypher GQL In Action! MATCH (:Person { name:“Dan”} ) -[:MARRIED_TO]-> (spouse) MARRIED_TO Dan Ann NODE RELATIONSHIP TYPE LABEL PROPERTY VARIABLE$

12
Risk Management (for FS)Intelligent Recommendations Network Management
Human Capital ManagementPrivacy Shield (GDPR, CCPA, …)Fraud Analysis Framework
Neo4j Solution Frameworks – accelerating T2M

Relationships are highly predictive of behavior, yet most data science models overlook this information because it's difficult to extract network structure for use in machine learning (ML). With graphs, relationships are embedded in the data itself, making it practical to add these predictive capabilities to your existing practices. That’s why we’re presenting and demoing the use of graph-native ML to make breakthrough predictions. This will cover: - Different approaches to graph feature engineering, from queries and algorithms to embeddings - How ML techniques leverage everything from classical network science to deep learning and graph convolutional neural networks - How to generate representations of your graph using graph embeddings, create ML models for link prediction or node classification, and apply these models to add missing information to an existing graph/incoming data - Why no-code visualization and prototyping is important

Making connections matter: 2 use cases on graphs & analytics solutions

Neo4j

Supply chain optimization is an unusual balancing act that requires finesse, skill and timely data. Every supply chain’s the key questions to be answered are: What to Buy? -- what are the factors in determining your optimal product mix and set of suppliers. How much to Buy? -- what are the most and least popular items at any given time interval When to Buy? -- long lags in delivery timing may tax limit your flexibility and influence your inventory management practices. We will illustrate an API-based solution that utilizes a Graph database platform to add demonstrable value to Supply Planning.

Your Roadmap for An Enterprise Graph Strategy

Neo4j

1. The Importance of Graphs in Government

Neo4j

Worst Practices in Artificial Intelligence

William Tsoi

Build it…will they come by Shawn Trainer

Data Con LA

What's hot

Neo4j Graph Use Cases, Bruno Ungermann, Neo4j

Neo4j

4. Document Discovery with Graph Data Science

Neo4j

AI, ML and Graph Algorithms: Real Life Use Cases with Neo4j

Ivan Zoratti

Neo4j GraphTalk Amsterdam - Next Generation Solutions using Neo4j

Neo4j

GraphTour 2020 - BT: Use of Graph Database in P2P / P2MP Connectivity for Vid...

Neo4j

Kick Off – Graphs: The Fuel Behind Innovation and Transformation in Every Field

Neo4j

Neo4j: What's Under the Hood & How Knowing This Can Help You

Neo4j

Introduction to the Neo4j Graph Platform & use cases

Neo4j

Neo4j Innovation Lab, Stefan Wendin, Neo4j

Neo4j

GraphTour 2020 - Neo4j Innovation Lab

Neo4j

Graphs in Life Sciences

Neo4j

Neo4j Innovation Lab – Bringing the Best of Data Science and Design Thinking ...

Neo4j

Transforming Innovation: Digital Twin for the Win!

Neo4j

Enterprise Ready: A Look at Neo4j in Production at Neo4j GraphDay New York City

Neo4j

How do You Graph

Ben Krug

Neo4j GraphTalk Düsseldorf - Einführung in Graphdatenbanken und Neo4j

Neo4j

Graph technology meetup slides

Sean Mulvehill

A Connections-first Approach to Supply Chain Optimization

Neo4j

Your Roadmap for An Enterprise Graph Strategy

Neo4j

1. The Importance of Graphs in Government

Neo4j

What's hot (20)

Neo4j Graph Use Cases, Bruno Ungermann, Neo4j

4. Document Discovery with Graph Data Science

AI, ML and Graph Algorithms: Real Life Use Cases with Neo4j

Neo4j GraphTalk Amsterdam - Next Generation Solutions using Neo4j

GraphTour 2020 - BT: Use of Graph Database in P2P / P2MP Connectivity for Vid...

Kick Off – Graphs: The Fuel Behind Innovation and Transformation in Every Field

Neo4j: What's Under the Hood & How Knowing This Can Help You

Introduction to the Neo4j Graph Platform & use cases

Neo4j Innovation Lab, Stefan Wendin, Neo4j

GraphTour 2020 - Neo4j Innovation Lab

Graphs in Life Sciences

Neo4j Innovation Lab – Bringing the Best of Data Science and Design Thinking ...

Transforming Innovation: Digital Twin for the Win!

Enterprise Ready: A Look at Neo4j in Production at Neo4j GraphDay New York City

How do You Graph

Neo4j GraphTalk Düsseldorf - Einführung in Graphdatenbanken und Neo4j

Graph technology meetup slides

A Connections-first Approach to Supply Chain Optimization

Your Roadmap for An Enterprise Graph Strategy

1. The Importance of Graphs in Government

Similar to GraphTour 2020 - Customer Journey with Neo4j Services

Worst Practices in Artificial Intelligence

William Tsoi

Build it…will they come by Shawn Trainer

Data Con LA

Data Intelligence: How the Amalgamation of Data, Science, and Technology is C...

Caserta

Roadmap for Enterprise Graph Strategy

Neo4j

Yhat - Applied Data Science - Feb 2016

Austin Ogilvie

Neo4j Graph Data Platform: Making Your Data More Intelligent

Neo4j

Customer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTX

tsigitnist02

Where the Warehouse Ends: A New Age of Information Access

Inside Analysis

The Briefing Room with Barry Devlin and Composite Software Live Webcast May 21, 2013 All good things must come to an end, and even though the data warehouse will remain a prominent force in the information age, the handwriting is all over the enterprise: the center of gravity is moving. Whether due to Big Data or real-time demands, Cloud computing or globalization, today's leading organizations have analytical needs that the warehouse simply cannot accommodate. That's why data virtualization continues to attract attention. Register for this episode of The Briefing Room to hear veteran Analyst Barry Devlin explain why the traditional model for data warehousing is being outmoded by a range of more flexible methods for accessing and analyzing information assets. He'll be briefed by David Besemer of Composite Software who will discuss how his company's data virtualization platform can be used to provide access to all manner of information sources, including data warehouses, Big Data silos, as well as partner and public data sources on demand. Visit: http://www.insideanalysis.com

Sightix

slevi1970

Machine Learning with GraphLab Create

Turi, Inc.

David Adams - Linkedin Information Architect Business Analyst - Web / Social ...

David Adams

Accelerating Innovation through Graph Thinking

Neo4j

Webinar: BI Team Backlogged with Information Demands?

Balanced Insight, Inc.

Is your business intelligence team backlogged with information demands? You're not alone. Business users have an insatiable appetite for information, yet current delivery methods can't keep pace. Join us for an educational webinar discussing how to meet users' demands for information with your existing business intelligence platform and staff. During our session, you will learn how to automate business intelligence solution delivery.

Building a New Platform for Customer Analytics

Caserta

Cloud Computing Basics III

RightScale

5 big data at work linking discovery and bi to improve business outcomes from...Dr. Wilfred Lin (Ph.D.)

Job Suneel MandamJob Suneel

SoniaP_ResumeSonia Pampattiwar

SplunkLive! Splunk for Business AnalyticsSplunk

DataOps: Nine steps to transform your data science impact Strata London May 18

Harvinder Atwal

According to Forrester Research, only 22% of companies are currently seeing a significant return from data science expenditures. Most data science implementations are high-cost IT projects, local applications that are not built to scale for production workflows, or laptop decision support projects that never impact customers. Despite this high failure rate, we keep hearing the same mantra and solutions over and over again. Everybody talks about how to create models, but not many people talk about getting them into production where they can impact customers. Harvinder Atwal offers an entertaining and practical introduction to DataOps, a new and independent approach to delivering data science value at scale, used at companies like Facebook, Uber, LinkedIn, Twitter, and eBay. The key to adding value through DataOps is to adapt and borrow principles from Agile, Lean, and DevOps. However, DataOps is not just about shipping working machine learning models; it starts with better alignment of data science with the rest of the organization and its goals. Harvinder shares experience-based solutions for increasing your velocity of value creation, including Agile prioritization and collaboration, new operational processes for an end-to-end data lifecycle, developer principles for data scientists, cloud solution architectures to reduce data friction, self-service tools giving data scientists freedom from bottlenecks, and more. The DataOps methodology will enable you to eliminate daily barriers, putting your data scientists in control of delivering ever-faster cutting-edge innovation for your organization and customers.

Similar to GraphTour 2020 - Customer Journey with Neo4j Services (20)

Worst Practices in Artificial Intelligence

Build it…will they come by Shawn Trainer

Data Intelligence: How the Amalgamation of Data, Science, and Technology is C...

Roadmap for Enterprise Graph Strategy

Yhat - Applied Data Science - Feb 2016

Neo4j Graph Data Platform: Making Your Data More Intelligent

Customer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTX

Where the Warehouse Ends: A New Age of Information Access

Sightix

Machine Learning with GraphLab Create

David Adams - Linkedin Information Architect Business Analyst - Web / Social ...

Accelerating Innovation through Graph Thinking

Webinar: BI Team Backlogged with Information Demands?

Building a New Platform for Customer Analytics

Cloud Computing Basics III

5 big data at work linking discovery and bi to improve business outcomes from...

Job Suneel Mandam

SoniaP_Resume

SplunkLive! Splunk for Business Analytics

DataOps: Nine steps to transform your data science impact Strata London May 18

More from Neo4j

Atelier - Architecture d’applications de Graphes - GraphSummit Paris

Neo4j

Atelier - Architecture d’applications de Graphes Participez à cet atelier pratique animé par des experts de Neo4j qui vous guideront pour découvrir l’intelligence contextuelle. En utilisant un jeu de données réel, nous construirons étape par étape une solution de graphes ; de la construction du modèle de données de graphes à l’exécution de requêtes et à la visualisation des données. L’approche sera applicable à de multiples cas d’usages et industries.

Atelier - Innover avec l’IA Générative et les graphes de connaissances

Neo4j

Atelier - Innover avec l’IA Générative et les graphes de connaissances Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement. Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.

Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris

Neo4j

Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris

Neo4j

FLOA - Détection de Fraude - GraphSummit Paris

Neo4j

SOPRA STERIA - GraphRAG : repousser les limitations du RAG via l’utilisation ...

Neo4j

Romain CAMPOURCY – Architecte Solution, Sopra Steria Patrick MEYER – Architecte IA Groupe, Sopra Steria La Génération de Récupération Augmentée (RAG) permet la réponse à des questions d’utilisateur sur un domaine métier à l’aide de grands modèles de langage. Cette technique fonctionne correctement lorsque la documentation est simple mais trouve des limitations dès que les sources sont complexes. Au travers d’un projet que nous avons réalisé, nous vous présenterons l’approche GraphRAG, une nouvelle approche qui utilise une base Neo4j générée pour améliorer la compréhension des documents et la synthèse d’informations. Cette méthode surpasse l’approche RAG en fournissant des réponses plus holistiques et précises.

ADEO - Knowledge Graph pour le e-commerce, entre challenges et opportunités ...

Neo4j

Charles Gouwy, Business Product Leader, Adeo Services (Groupe Leroy Merlin) Alors que leur Knowledge Graph est déjà intégré sur l’ensemble des expériences d’achat de leur plateforme e-commerce depuis plus de 3 ans, nous verrons quelles sont les nouvelles opportunités et challenges qui s’ouvrent encore à eux grâce à leur utilisation d’une base de donnée de graphes et l’émergence de l’IA.

GraphSummit Paris - The art of the possible with Graph Technology

Neo4j

GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...

Neo4j

Dr. Sean Tan, Head of Data Science, Changi Airport Group Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.

GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...

Neo4j

Leonard Jayamohan, Partner & Generative AI Lead, Deloitte This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.

GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024

Neo4j

GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024

Neo4j

GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...

Neo4j

Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.

GraphAware - Transforming policing with graph-based intelligence analysis

Neo4j

Petr Matuska, Sales & Sales Engineering Lead, GraphAware Western Australia Police Force’s adoption of Neo4j and the GraphAware Hume graph analytics platform marks a significant advancement in data-driven policing. Facing the challenges of growing volumes of valuable data scattered in disconnected silos, the organisation successfully implemented Neo4j database and Hume, consolidating data from various sources into a dynamic knowledge graph. The result was a connected view of intelligence, making it easier for analysts to solve crime faster. The partnership between Neo4j and GraphAware in this project demonstrates the transformative impact of graph technology on law enforcement’s ability to leverage growing volumes of valuable data to prevent crime and protect communities.

GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product Updates

Neo4j

KLARNA - Language Models and Knowledge Graphs: A Systems Approach

Neo4j

INGKA DIGITAL: Linked Metadata by Design

Neo4j

Your enemies use GenAI too - staying ahead of fraud with Neo4j

Neo4j

Delivered by Michael Down at Gartner Data & Analytics Summit London 2024 - Your enemies use GenAI too: Staying ahead of fraud with Neo4j. Fraudsters exploit the latest technologies like generative AI to stay undetected. Static applications can’t adapt quickly enough. Learn why you should build flexible fraud detection apps on Neo4j’s native graph database combined with advanced data science algorithms. Uncover complex fraud patterns in real-time and shut down schemes before they cause damage.

BT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptx

Neo4j

Delivered by Sreenath Gopalakrishna, Director of Software Engineering at BT, and Dr Jim Webber, Chief Scientist at Neo4j, at Gartner Data & Analytics Summit London 2024 this presentation examines how knowledge graphs and GenAI combine in real-world solutions. BT Group has used the Neo4j Graph Database to enable impressive digital transformation programs over the last 6 years. By re-imagining their operational support systems to adopt self-serve and data lead principles they have substantially reduced the number of applications and complexity of their operations. The result has been a substantial reduction in risk and costs while improving time to value, innovation, and process automation. Future innovation plans include the exploration of uses of EKG + Generative AI.

Workshop: Enabling GenAI Breakthroughs with Knowledge Graphs - GraphSummit Milan

Neo4j

More from Neo4j (20)