Neo4j GraphTour New York_ State of the State_Amit Chaudhry Neo4j
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Neo4j GraphTour New York_ State of the State_Amit Chaudhry Neo4j
- 1. Neo4j Graph Tour, New York October 16, 2019 Amit Chaudhry, VP, Neo4j
- 3. Agenda • Graphs 101 • Data Management Trends • Case Studies • The Future of Graphs
- 4. Networks of People Business Processes Knowledge Networks E.g., Risk management, Supply chain, Payments E.g., Employees, Customers, Suppliers, Partners, Influencers E.g., Enterprise content, Domain specific content, eCommerce content Data connections are increasing as rapidly as data volumes The Rise of Connections in Data Electronic Networks On-prem & cloud computing, Cellular, Telco & Internet, IoT, Blockchain
- 5. Strictly ConfidentialStrictly Confidential So What is a Graph Database? • A Graph Database uses as set of nodes, relationships and properties to represent and store data • Graph databases hold the relationships between data as a priority. • These relationships help discover new insights between the data Node Node Relationship
- 6. Frederik Obermaier, Süddeutsche Zeitung, on the importance of networks in journalism. From Panel at Columbia University Feb 23, 2018. “I’ve only come across 3 or 4 stories in my career that weren’t about networks.”
- 8. ACCOUNT ADDRESS PERSON PERSON NAME STREET BANK NAME COMPANY BANK BAHAMAS 2.6 TB 11.5 million documents Emails, Scanned Documents, Bank Statements etc…
- 9. 2.6 TB 11.5 million documents Emails, Scanned Documents, Bank Statements etc… Person B Bank US Account 123 Person A Acme Inc Bank Bahama s Address XNODE RELATIONSHIP
- 10. 2.6 TB 11.5 million documents Emails, Scanned Documents, Bank Statements etc…
- 14. ICIJ Pulitzer Price Winner 2017
- 15. Common Graph Use Cases Fraud Detection Real-Time Recommendations Network & IT Operations Master Data Management Knowledge Graph Identity & Access Management airbnb
- 16. “Forrester estimates that over 25% of enterprises will be using graph databases by 2017.” Forrester, 2014
- 17. Popularity of Graphs DB-engines Ranking of Database Categories • Graph DBMS • Key-value stores • Document stores • Wide column store • RDF stores • Time stores • Native XML DBMS • Object oriented DBMS • Multivalue DBMS • Relational DBMS Graph DB 2013 2014 2015 2016 2017 2018 2019
- 18. Trend No. 5: Graph … The application of graph processing and graph DBMSs will grow at 100 percent annually through 2022 to continuously accelerate data preparation and enable more complex and adaptive data science. … Graph analytics will grow in the next few years due to the need to ask complex questions across complex data, which is not always practical or even possible at scale using SQL queries. https://www.gartner.com/en/newsroom/press-releases/2019-02-18-gartner-identifies-top-10-data-and-analytics-technolo February 18, 2019
- 19. The Hadoop Market is Unsteady
- 20. From Collections to Connections
- 21. Mainstream Markets Demand Skills
- 22. Breaking News: Database Market History
- 24. Strictly ConfidentialStrictly Confidential Strategic initiative, led by Thomas Kurian, CEO of Google Cloud • Goal to be #2 Enterprise Cloud as the “open source friendly” alternative to AWS • Work with known/proven leaders across key areas • Neo4j/GCP integrated solution beta by EoY 2019 • Initial release of Neo4j DBaaS will be available via the Google marketplace 24 Google Cloud Partnership • Fully managed services running in the cloud, with best efforts made to optimize performance and latency between the service and application. • A single user interface to manage apps, which includes the ability to provision and manage the service from the Google Cloud Console. • Unified billing, so you get one invoice from Google Cloud that includes the partner’s service. • Google Cloud support to manage and log support tickets in a single window and not have to deal with different providers.
- 25. Retail 7 of top 10 Finance 20 of top 25 7 of top 10 Software Hospitality 3 of top 5 Telco 4 of top 5 Airlines 3 of top 5 Logistics 3 of top 5 76% FORTUNE 100 have adopted or are piloting Neo4j
- 27. Background • Over 7M citizens suffer from Diabetes • Connecting over 400 researchers • Incorporates over 50 databases, 100k’s of Excel workbooks, 30 database of biological samples • Sought to examine disease from as many angles as possible. Business Problem • Genes are connected by proteins or to metabolites, and patients are connected with their diets, etc… • Needed to improve the utilization of immensely technical data • Needed to cater to doctors and researchers with simple navigation, communication and connections of the graph. Solution and Benefits • Dr. Alexander Jarasch, Head of Bioinformatics and Data Management • Scientists can conduct parallel research without asking the same questions or repeating tests • Built views like a liver sample knowledge graph DZD - German Center for Diabetes Research Medical Genomic Research29 EE Customer since 2016 Q
- 28. Background • Fortune 100 heavy equipment manufacturer • 27 Million warranty & service documents parsed • Foundation for AI-based supply chain management 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 • Text to knowledge graph • Common ontology for complaints, symptoms & parts • Anticipates when equipment will need servicing • Improves customer and brand satisfaction • Maximizes lifespan and value of equipment Caterpillar Heavy Equipment Manufacturing Parts Assembly & Equipment Maintenance30
- 29. 32
- 30. Home Security Internet of things Institutional Memory Entertainment Recommendations Home Operations Personalization Voice Enabled Smart Home
- 31. Background • Largest Cable TV & Internet Provider in US • 3rd Largest network on the planet • xFi is consumer experience in 3M houses • Internet, router, devices, security, voice & telephony • Transformational customer experience 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 • Has Siri-like voice commands COMCAST Xfinity xFi TELECOMMUNICATIONS Smart Home / Internet of Things34 EE Customer since 2016 Q
- 32. AI & Graphs
- 33. Strictly ConfidentialStrictly Confidential The Market Sees Strong Synergy between Graphs and Artificial Intelligence 36 AI research papers focused on graphs SURGING INTEREST New Book: 20K Downloads in first 2 weeks CONNECTED CONTEXT FOR AI/ML CUSTOMER TRACTION German Center for Diabetes Research
- 34. “Increasingly we're learning that you can make better predictions about people by getting all the information from their friends and their friends’ friends than you can from the information you have about the person themselves”
- 35. Wrap Up
- 36. April 20-22, 2020 | New York Connect Your Data. Build The Future. graphconnect.com
Editor's Notes
- You are in great company..lots of best and the brightest companies from around the area are represented here… JP Morgan, Prudential, Moody’s, UBS, E&Y, Citibank , Mckinsey, Bloomberg etc
- What is the opportunity? What is creating this opportunity? Reinstate the “Connections in data are as valuable as the data itself” Whether you are doing customer analytics, fraud detection, or risk assessment, you need connected data. While linking a few data points or data sources is often simple, creating connections with significant amounts of heterogeneous data requires a radically new approach. Enterprise architects should read this report to learn how the new and emerging graph database technology offers the ability to link pieces of data easily to create more meaningful and actionable insights.
- “The first story is about the Panama Papers, which was the biggest news story of 2016, but its impact is still very live: a couple of months ago the prime minister of Pakistan resigned over findings in the Panama Papers, and just last week he was actually formally indicted for corruption.” “In this particular story, the heroes are two journalists at the Suddeutsche Zeitung who were provided with a”<click>
- “Now if we look at this more abstract we can see that we have concepts and how they are related to each other.” “In the graph world we call these<click>Nodes and<click>Relationships.” “It turns out with these very simple abstractions — <enumerate them> — we can build and model *everything*. It turns out that this model is very flexible. Easy to evolve. Etc.” … “and your data model will organically evolve with you as as your needs change.”
- “What’s equally amazing is if you wrap this data model in an infrastructure that can support not just 7 nodes but”<click>
- “a million nodes, or 11.5 million nodes, or a billion nodes, or 100 billion nodes.”
- “Ok, so back to our story. Remember that second pattern we discussed before, where someone was connected through his wife to an offshore bank account. Well, here’s the real world example of that: the Icelandic prime minister Sigmundur Gunnlaugsson. Excuse me! The *former* prime minister of Iceland. That’s the type of impact the Panama Papers had.”
- “As mentioned, it rapidly became one of the biggest news stories last year and was written up in virtually every major newspaper in every country in the world.”
- And of course when they do something like this something-something last month
- At the time, this was considered a bold and shocking prediction.
- 60% -> 85%
- You are spending your time wisely…more and more skills needed
- Put together by our friends at GraphAware.
- We see this at Neo4j, where as of today 76% of the F100 have either piloted or adopted Neo4j! That’s a staggering amount. But that’s not enough. As of right now, most of the leading organizations in most of the biggest verticals in the world rely on Neo4j. We already talked about Software and Insurance, but just to give you a sense: 20 of the top 25 global financial services organizations (and 20 of the top 20 US banks) are using Neo4j, 4 of the top 5 telcos and 3 of the top 5 airlines. Graphs have truly arrived in the enterprise.
- “And today, we have 470 startups in that program. Look at these logos. You may not recognize all of them, or maybe even one of them. But everyone of them has the power of Google in their hand. And I’ll be willing to bet that at least one out of these 470 startups will become a household name in the next ten years.”
- https://www.forbes.com/sites/danwoods/2018/11/30/fighting-diabetes-with-graph-analytics/#3efdbaad45dc
- http://www.odbms.org/blog/2018/07/on-using-graph-database-technology-at-behance-interview-with-david-fox/
- I’d like to close with a topic that you’ve all heard about, and that many of you may already be working in, and that’s AI. And more precisely, how graphs are starting to be used in AI.
- Why do other databases also talk about the same use cases? SHOUT OUT TO CATERPILLAR
- “We have an exciting day ahead of us. Let me take this first hour to take a step back and talk a little about the state of the graph space today, and much more importantly talk about where I believe the space is going. “It’s been a year since we had a GraphConnect here in the US, and what a year it has been. Graphs have had an impact on an order that we’ve never seen before. Let me give you a couple of examples.”