neo4j.com/online-summit schedule

import.cypher

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nodes-2019.csv

id;title;start;end;track;type;description;speakers;company;level;tags;slug
10;Building a full-stack fraud-detection Solution with Kafka, GraphQL and Neo4j-Graph-Algorithms;10.10.2019 11:30 AM;10.10.2019 12:15 PM;Track 1;Regular Talk (~30 minutes);Graphs help drive financial fraud investigations, social media analyses, network & IT management use cases, recommendation engines, and knowledge management. These are all cases where patterns of interaction in your data (for example, a pattern of structured financial transactions) matter more than the individual data points (a single transfer). We’ll cover how to easily transform Kafka streams or tables into graphs, and query them declaratively using Cypher or GraphQL. In graph shape, we can enrich our social network streams with powerful graph algorithms that tell us about user and event influence through graph centrality, then streaming results back to Kafka. Stream/table duality becomes the stream / table / graph trinity. We will demonstrate the trinity by:<br><br>– Getting started with regular kafka streams,<br>– Using confluent hub’s Neo4j sink<br>– Exposing query-able graphs with Cypher & GraphQL<br>– Analyzing data with Neo4j’s graph algorithms<br>– Transforming graphs back into streams.<br><br>We’ll demonstrate how it can be used to tackle social network analysis problems and discuss how the approach can be extended to real-time financial fraud detection and more.;Mark Needham;Neo4j;Intermediate;streams,kafka,grandstack-graphql,data-science-algos,fraud-detection;fraud-solution-neo4j-kafka-algorithms-graphql-grandstack
11;Best Practices for Making (Very) Large Database Updates in Neo4j;10.10.2019 4:00 PM;10.10.2019 4:30 PM;Track 1;Regular Talk (~30 minutes);Ever got in trouble when trying to update a large amount of nodes and/or relationships in Neo4j? Scared by OutOfMemory, server slow-down, or frequent leader switch in a cluster? This session will show you best practices to make very large updates without negative impacts to your database services.;Fanghua(Joshua) Yu;Neo4j;Advanced;cypher,operations,etl;best-practices-large-database-updates-neo4j
13;Agile Property Graph Design Process;10.10.2019 1:45 PM;10.10.2019 2:30 PM;Track 2;Regular Talk (~30 minutes);How do you convert user requirements into a properly functioning property graph database design? This talk will outline a simple methodology you can implement on your current project.;John Singer;NodeEra Software;All;modeling;agile-property-graph-design-process-modeling
14;Fix your microservice architecture using graph analysis;10.10.2019 2:30 PM;10.10.2019 3:15 PM;Track 3;Regular Talk (~30 minutes);"So, for you brand new project, you decided to throw away your monolith and go for microservices.<br>But after a while, you realize things are not going as smoothly as expected ;-)<br><br>Hopefully, a graph can help to detect antipatterns, visualize your whole system, and even do cross-service impact analysis.<br>In this talk, we'll analyze a microservice system based on Spring Cloud, with jQAssistant and Neo4j. We will see how it can be helpful to answer questions like:<br><ul><li>do I have anti-patterns in my microservice architecture ?</li><li>which services / applications are impacted when doing a database refactoring ?</li><li>is my API documentation / specification up to date ?</li><li>how to get an up to date visualization of my whole system ?</li><li>and more !</li></ul>";Nicolas Mervaillie;GraphAware;Intermediate;architecture,spring,technology,analysis;microservice-architecture-graph-analysis
15;Graph data for the construction industry: Modelling heating, ventilation, electrical, and other building services;10.10.2019 3:15 PM;10.10.2019 4:00 PM;Track 3;Regular Talk (~30 minutes);The construction industry is in the midst of radical change. A significant driving force is in developing sustainable designs which meet the needs of the building occupants.<br /><br />This talk will showcase how graph data can provide rich insights and a common source of data throughout the design process.;Will Reynolds;Hoare Lea;All;dotnet,javascript,construction,cloud,AEC;graphs-construction-industry-modeling
16;Large Scale Social Networks - Challenges and Opportunities;10.10.2019 4:00 PM;10.10.2019 4:30 PM;Track 2;Regular Talk (~30 minutes);How to model a large scale Social Network in Neo4j using Cypher and User Defined Procedures and how to apply Graph Algorithms to personalise content and improve engagement.;Adam Cowley;Neo4j;Advanced;cypher,data-science-algos;large-scale-social-networks-challenges-opportunity-solutions
17;Chaos engineering with Neo4j;10.10.2019 12:15 PM;10.10.2019 1:00 PM;Track 2;Regular Talk (~30 minutes);In the last couple of years chaos engineering became very popular. You can get fewer surprise breakdowns in production, as well as foreknowledge of how to save the day when bad things happen. In this talk I will show you how to do chaos engineering if Neo4j is part of your application stack.;Janos Szendi Varga;freelancer;Advanced;architecture,java,operations;chaos-engineering-neo4j
18;How to keep track of change - versioning approaches in Neo4j;10.10.2019 3:15 PM;10.10.2019 4:00 PM;Track 2;Regular Talk (~30 minutes);Versioning data is a critical element in many data applications. It is used in finance, identity and access management and master data management to name but a few industries and use cases.<br><br>Versioning enables us to:<br><ul><li>track changes made to data</li><li>make corrections without deleting anything</li><li>'travel' through time to understand state changes</li></ul><br>In this talk we are going to looking at time-based versioning in Neo4j, exploring approaches to track:<br><ul><li>an object's state</li><li>relationship changes</li><li>ommited records</li></ul>;Lju Lazarevic;Neo4j;Intermediate;versioning;change-tracking-versioning-approaches-neo4j
2;Building a Graph of History with The Codex;10.10.2019 4:00 PM;10.10.2019 4:30 PM;Track 3;Regular Talk (~30 minutes);The Codex attempts to deeply integrate text and data by building a graph network of people, places, events and concepts embedded in texts. A standoff-property text editor allows the graph meta-model to be built from multidimensional annotation. NLP services are incorporated to drive semantic search.;Iian Neill;Visiting Researcher,Digital Academy of the University of Mainz;Intermediate;javascript,nlp,dotnet,digital-humanities;graph-of-history-codex
24;Predicting and Prosecuting Crime in Rio de Janeiro: A Machine Learning Story;10.10.2019 11:05 AM;10.10.2019 11:30 AM;Track 5;Lightning Talk (10 minutes);The role of prosecutor is different in Brazil than in other countries. However, the application and workforce benefits of ML are the same in many countries and several industries. How to use big data and graph db to predict and identify crimes?;Daniel Belchior;Public Prosecutor Office Brazil;All;ai-ml,crime,investigation;predicting-prosecuting-crime-rio-de-janeiro-machine-learning-ml
27;How the GRANDstack Makes Handling Complex Data Easy;10.10.2019 1:20 PM;10.10.2019 1:45 PM;Track 5;Lightning Talk (10 minutes);Using neo4j along with the GRANDstack has allowed me to build an application that deals with highly connected data in a manner I don't think would be possible with a SQL data base. The neo4j-graphql-js integration makes turning your Neo4j instance into a modern React application a snap.;Michael Porter;Muddy Boots Code;All;grandstack-graphql,javascript;grandstack-graphql-easy-data-handling
28;Public Transport São Paulo in a graph database;10.10.2019 12:15 PM;10.10.2019 12:35 PM;Track 5;Lightning Talk (10 minutes);Tired of getting lost in the traffic of São Paulo? All your problems are solved! With this database you can easily find your way across the Metropolitan transport network from São Paulo, finding the best and shortest path across the city.;Igor Gustavo Oliveira Rozani;e-Core;All;transport-infrastructure;public-transport-graph-sao-paulo
3;Exploring the U.S. National Bridge Index;10.10.2019 12:35 PM;10.10.2019 12:55 PM;Track 5;Lightning Talk (10 minutes);Bridges around the country are rapidly deteriorating. The National Bridge Index represents an annual snapshot of the state of U.S. bridge infrastructure. We'll explore the steps from decoding & processing the data to developing a graph schema before exploring a web app build on the GRANDstack.;Michael McKenzie;Calibre;All;ai-ml,crime,investigation,grandstack-graphql,javascript,transport-infrastructure;exploring-national-bridge-index
30;We're not just relational anymore: Teaching Neo4j as part of an introductory database course;10.10.2019 11:50 AM;10.10.2019 12:15 PM;Track 5;Lightning Talk (10 minutes);Today's students need to know more than just the relational model to be competitive. Adding Neo4j to the curriculum sparks interest and excitement in the classroom. Novice databases users benefit from concrete examples and play spaces where they can explore. Learn about how we teach Neo4j at Rice.;Risa Myers;Rice University;All;education,digital-humanities,introduction;teaching-neo4j-introduction-college
31;Modeling a Tournament in Neo4j;10.10.2019 1:45 PM;10.10.2019 2:05 PM;Track 5;Lightning Talk (10 minutes);Scheduling and organizing a martial arts tournament can be a challenging task due to the variety of ages, ranks, division, competitors, and judges that makeup the tournament. We'll explore an approach to develop a tournament application with Neo4j and built on the GRANDstack.;Michael McKenzie;United Fighting Arts Federation;All;grandstack-graphql,javascript;modeling-tournament-neo4j
32;ML-based Graph Embeddings;10.10.2019 11:30 AM;10.10.2019 11:50 AM;Track 5;Lightning Talk (10 minutes);Graphs encode a surprising amount of information in their structure alone. How do machine learning techniques extract this data, and what can we do with it? Using a network of national cuisines Braintree has cooked up a flavour-based similarity metric for the food scientists at Unilever.;Frederick Russo;Braintree;All;ai-ml,food;machine-learning-graph-embeddings-ml
33;Bolt-On Your Web App to Neo4j;10.10.2019 10:45 AM;10.10.2019 11:05 AM;Track 5;Lightning Talk (10 minutes);This talk is about turning SemSpect into a Neo4j Graph App by extending the existing client-server communication with support for the Bolt protocol in a “REST over Bolt” fashion. In particular we focus on how to support both, HTTP REST and Bolt, as API protocols in our web application.;"Christian Ranz; Michael Opitz";derivo GmbH & codastic;Intermediate;graph-apps,java,apoc-procedures;graph-app-bolt-procedures-semspect
34;It Depends (and why it's the most frequent answer to modelling questions);10.10.2019 10:00 AM;10.10.2019 10:20 AM;Track 5;Lightning Talk (10 minutes);"The answer to most general purpose graph modelling questions is ""it depends"". This talk demonstrates the pitfalls of modelling without knowing use cases- it shows how two sets of people can produce two different models for the same set of data elements, and how use cases should guide the model.";Luanne Misquitta;GraphAware;Beginner;modeling;dependency-modeling
39;Ten to Dine: Building Possibility Spaces with Neo4j and ReactJS;10.10.2019 10:00 AM;10.10.2019 10:45 AM;Track 4;Regular Talk (~30 minutes);Databases can be more than boxes to house data. By connecting our data in a graph structure, we can transform them into possibility spaces. I will demonstrate how a database becomes a universe using a combination of Neo4j, ReactJS, and the sultry-but-familiar backdrop of a noir murder mystery.;"Brandon Campbell; Kelson Smith";Northrop Grumman;All;ai-ml,crime,investigation,javascript,investigation-crime;murder-mystery-app-fullstack
40;Making Graph Algorithms 'Clique';10.10.2019 10:00 AM;10.10.2019 10:45 AM;Track 3;Regular Talk (~30 minutes);This talk will explain how to use several graph algorithms using the characters, plots, and tropes of classic teen films. Expect a fun, light-hearted, and enlightening look at these powerful tools. It'll be so very!;Joe Depeau;Neo4j;Intermediate;ai-ml,data-science-algos,introduction;graph-algorithms-clique-highschool-social
41;Software Applications are Graphs:: What You Always Wanted to Know About How Structr Works;10.10.2019 10:45 AM;10.10.2019 11:30 AM;Track 4;Regular Talk (~30 minutes);In this talk Axel will give exclusive and deep insights into the technology of Structr whose basic principle is to store the entire definition of software applications, i.e. the semantic data model, the user interface and the dynamic behavior, in Neo4j in the form of coherent graphs.;Axel Morgner;Structr GmbH;All,Advanced;ai-ml,crime,investigation,graph-apps,java,modeling,javascript;software-application-graphs-how-structr-works
42;Challenges in knowledge graph visualization;10.10.2019 3:15 PM;10.10.2019 3:35 PM;Track 5;Lightning Talk (10 minutes);Visualizing a complex graph is a task of graph simplification and providing well-thought visual cues, the best UI goes unnoticed. This talk will summarize current approaches and present a novel user interaction pattern, which takes advantage of a performant Neo4j graph engine.;Jan Zak;GraphAware;Intermediate;graph-visualization,javascript,knowledge-graph;challenges-knowledge-graph-visualization
43;"Collaboration insights from data access analytics: ""Follow the data""";10.10.2019 4:00 PM;10.10.2019 4:30 PM;Track 4;Regular Talk (~30 minutes);Today's applications interact with data in a distributed and decentralized world. Using graphs at scale, we can infer workflows and communities by following access to common data elements across users and applications. We walk through a real world product example of this with millions of users.;Ravi Krishnaswamy;Autodesk Inc.;Intermediate;analysis,spark,etl-data-integration,modeling;data-access-analytics-follow-the-data
47;Unearthing Historical Networks Using Neo4j and Archival Documents: An Introduction to Archivepelago;10.10.2019 2:05 PM;10.10.2019 2:30 PM;Track 5;Lightning Talk (10 minutes);What if Facebook or LinkedIn existed a hundred years ago?<br><br>Using archival documents we can reconstruct a picture of the professional and social relationships. This talk will show how we are using letters and other writings to map networks of gay and lesbian writers in the 19th and 20th centuries.;Corey D Clawson;Rutgers University;All;digital-humanities,modeling;historical-networks-archive-documents-archivepelago
49;Intuitive Graph BI Through Visual Graph Transformation;10.10.2019 4:00 PM;10.10.2019 4:20 PM;Track 5;Lightning Talk (10 minutes);The relational data model underlying Business Intelligence tools assumes that a data model can and should be defined before analysis. This renders solutions inflexible in the face of edge cases and shifting use cases. The author proposes a system for the fluid transformation of graph data models.;Weidong Yang;Kineviz;Advanced;etl-data-integration,knowledge-graph,graph-visualization;graph-bi-visual-transformation
5;Uncovering Medical Fraud in New York City's most Vulnerable Neighborhoods;10.10.2019 1:00 PM;10.10.2019 1:20 PM;Track 5;Lightning Talk (10 minutes);Healthfirst provides health insurance for 1.4M New Yorkers. Our in-house Fraud, Waste and Abuse platform featuring Neo4J allows us to deliver high quality leads to our investigators which helps keep millions of dollars within a system designed to reach some of NYC's most under served populations.;Kenneth Schwartz;Healthfirst;All;healthcare-biotech,ai-ml,data-science-algos,fraud-detection;uncovering-medical-fraud-nyc
50;How to build a knowledge graph from scratch even if you are not really a full-blown developer;10.10.2019 11:30 AM;10.10.2019 12:15 PM;Track 4;Regular Talk (~30 minutes);How do you capture knowledge about a complicated domain in the life sciences if many of the data you need is not available for download? Learn about building a cancer drug discovery knowledge graph using tools to capture, connect, store, query and visualize a landscape of biotech/pharma companies.;Wolfgang Hoeck;Live Data Concepts;All;healthcare-biotech,cypher,etl,knowledge-graph,bloom,graph-visualization;knowledge-graph-cancer-modeling-import-explore-bloom
51;Making patterns show themselves;10.10.2019 3:15 PM;10.10.2019 4:00 PM;Track 4;Regular Talk (~30 minutes);Let's look over four use-cases where graphs powered pattern discovery:<br>- recommendations for going out over Facebook<br>- light-leakage of corporate information over LinkedIn<br>- highly-accurate, troll resilient, social trust and reputation engine<br>- influence Empires over Facebook;Calin Constantinov;University of Craiova;All;recommendation,social-network;making-pattern-show-themselves-investigation-social-network
52;Social media monitoring with ML-powered Knowledge Graph;10.10.2019 1:45 PM;10.10.2019 2:30 PM;Track 4;Regular Talk (~30 minutes);Ever wondered how can be ML used to build Knowledge Graph for allowing businesses to successfully differentiate and compete today? We will show how Computer Vision, NLP/U, knowledge enrichment and graph-native algorithms fit together to build powerful insights from various unstructured data sources.;"Vlasta Kus; Golven Leroy";GraphAware;All;nlp,ai-ml,knowledge-graph;social-media-monitoring-knowledge-graph-ml
53;To be or not to be. Full Text Search tips and tricks.;10.10.2019 1:00 PM;10.10.2019 1:45 PM;Track 4;Regular Talk (~30 minutes);"""To be or not to be"". Search for me.";Christophe Willemsen;GraphAware;Beginner;cypher,search;full-text-search-tips-to-be-or-not-to-be
57;Keynote and Announcements;10.10.2019 8:00 AM;10.10.2019 9:30 AM;Track 1;Regular Talk (~30 minutes);Co-Creator and CEO of Neo4j Emil Eifrem will MC the keynote at our online developer conference. Join to hear about the latest in graphs and Neo4j as well as some exciting announcements.;Emil Eifrem;Neo4j;All;introduction,announcements;keynote-neo4j-announcements-ceo
58;Graphs in AI and ML;10.10.2019 12:15 PM;10.10.2019 1:00 PM;Track 1;Regular Talk (~30 minutes);"This presentation will talk about how to get started using graphs to improve machine learning models. We'll start by reviewing when graphs are useful and provide valuable new insights, and then walk through real world examples of using graphs to improve your machine learning pipeline at varying stages of complexity:<br />
<ul>
<li>Building and querying a knowledge graph,</li>
<li>Using cypher queries to manually engineer features</li>
<li>Using graph algorithms for unsupervised feature engineering</li>
<li>Graph embeddings for custom features, and</li>
<li>Graph neural networks&nbsp;</li>
</ul>
After listening to this talk, you'll have a clear understanding of different ways you can use graphs in machine learning, and how Neo4j can facilitate your process.";"Jake Graham; Alicia Frame";Neo4j;Intermediate;ai-ml,data-science-algos,knowledge-graph,fraud-detection;graphs-machine-learning-artificial-intelligence-ml-ai
59;Intro to Neo4j for Developers;10.10.2019 10:00 AM;10.10.2019 10:45 AM;Track 1;Regular Talk (~30 minutes);In this connected world, traditional data stores often make it difficult to find valuable relationships. By making them a key component of the model, contextualizing a set of data becomes incredibly simple.<br><br>In this session, we will walk through what a graph database is and how it can transform your applications and data. We will explore creating, querying, and displaying data and learn how to use simple tools to interact with the database. We will cover the whiteboard-friendly model and the basics of the Cypher query language. Live demos will show developers how to interface with the database and the data in it.<br><br>Join us to learn how graph databases are used to improve the data world and help developers easily extract/import connected data!;Jennifer Reif;Neo4j;Beginner;introduction,cypher,java;neo4j-introduction-developers
6;Coding a graph application from scratch with GRANDstack;10.10.2019 3:35 PM;10.10.2019 4:00 PM;Track 5;Lightning Talk (10 minutes);The GRANDstack is a rich ecosystem of tools that developers use to rapidly build and prototype graph applications. Coding from scratch, Christian shows how easy it is to create a graph web application for any use case.;Christian Miles;Cambridge Intelligence;Intermediate;grandstack-graphql,javascript,graph-visualization;coding-a-graph-app-from-scratch-grandstack
60;Neo4j Bolt Driver Architecture Now and in The Future;10.10.2019 10:45 AM;10.10.2019 11:30 AM;Track 2;Regular Talk (~30 minutes);;;Neo4j;Advanced;java,javascript,dotnet,python;neo4j-bolt-architecture
61;GRANDstack: Graphs ALL the Way Down;10.10.2019 11:30 AM;10.10.2019 12:15 PM;Track 3;Regular Talk (~30 minutes);"GRANDstack is a full-stack framework for building applications with GraphQL, React, Apollo, and Neo4j Database. Learn why GraphQL has been quickly gaining adoption and why representing data as a graph is a win when building your API - both for API developers and consumers, and especially if you are working with graph data in the data layer, such as with a graph database like Neo4j.<br><br>In this talk we will cover some of the advantages of GraphQL over REST, as well as challenges with adopting GraphQL. We also dive into backend considerations for GraphQL and show how to leverage the power of representing your API data with graph using GraphQL and graph databases on the backend.<br><br>After this talk you will:<br><ul><li>Understand the basics of GraphQL</li><li>&nbsp;Be able to query a GraphQL API</li><li>Understand how a GraphQL service is built</li><li>Be exposed to some of the tooling in the GraphQL ecosystem, including database and frontend framework integrations</li><li>How to build full-stack applications with GRANDstack</li></ul>";William Lyon;Neo4j;Beginner;grandstack-graphql,javascript;grandstack-graphql-deep-dive-neo4j
62;All-new SDN-RX: Reactive Spring Data Neo4j;10.10.2019 2:30 PM;10.10.2019 3:15 PM;Track 1;Regular Talk (~30 minutes);"<!-- p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; line-height: 15.0px; font: 13.0px 'Helvetica Neue'; color: #000000; -webkit-text-stroke: #000000; background-color: #ffffff} span.s1 {font-kerning: none} -->
<p>Starting with version 4.0 Neo4j will support the reactive programming model. To provide this feature for the Spring (Data) community, we decided to re-create Spring Data Neo4j from scratch purely based on the newest Java Driver and the Spring framework. With this foundation you can expect an even better support for mapping of your business domain in the Spring ecosystem.</p>";Gerrit Meier;Neo4j;Intermediate;java,spring;spring-data-neo4j-reactive-sdn-rx
63;Graph Algorithms for Community Detection & Recommendations;10.10.2019 1:00 PM;10.10.2019 1:45 PM;Track 1;Regular Talk (~30 minutes);;"Amy Hodler; Mark Needham";Neo4j;Intermediate;data-science-algos;graph-algorithms-community-detection-recommendation
64;Graph Embeddings;10.10.2019 1:45 PM;10.10.2019 2:30 PM;Track 1;Regular Talk (~30 minutes);"An embedding is a low dimensional representation of a complex data set - essentially the translation of multidimensional data into a fixed length vector. Embeddings, once generated, can be used to quickly find nearest neighbors, as inputs in machine learning models, or to visualize the distribution of items in multidimensional space. A particularly exciting field of research is in<strong> graph embeddings</strong> which are embeddings representing some aspect of graph topology, connectivity, or network structure. Graph embeddings can represent nodes, edges, paths, or entire graphs, and have been used for a variety of applications ranging from efficient recommendation algorithms, knowledge graph completion and relational inference, and predicting changes in network structure (eg. protein folding, chemical reactions, etc).&nbsp;<br /><br />We're actively implementing several prototype embeddings within Neo4j, and I'll talk about how they work, why we chose them, and what they can be used for.<br />";Alicia Frame;Neo4j;Advanced;ai-ml;graph-embeddings-machine-learning-ml
65;Graph Data Modeling Tips & Tricks;10.10.2019 2:30 PM;10.10.2019 3:15 PM;Track 2;Regular Talk (~30 minutes);"One of the first things we have to do when working with Neo4j is figuring out how to model our data.&nbsp; This session will teach you what to keep in mind when modeling data from a performance point of view. Once you understand the way data is saved in Neo4j it will help you make better decisions or at least concious choices in how to best model your data for your particular use case. We will review a few ways to model one set of data, and the many choices you may be faced with when doing your own models. Remember, there is no right way to model data in Neo4j, but plenty of wrong ways.";Max De Marzi;Neo4j;All,Intermediate;ai-ml,crime,investigation,modeling;graph-data-modeling-tricks
66;APOC Pearls: The Best Tips & Tricks;10.10.2019 12:15 PM;10.10.2019 1:00 PM;Track 3;Regular Talk (~30 minutes);APOC has become the de-facto standard utility library for Neo4j. In this talk, I will demonstrate some of the lesser known but very useful components of APOC that will save you a lot of work. You will also learn how to combine individual functions into powerful constructs to achieve impressive feats<br><br>This will be a fast-paced demo/live-coding talk.;Michael Hunger;Neo4j;All,Advanced;ai-ml,crime,investigation,apoc-procedures;apoc-tips-tricks-useful-tools-standard-library
67;Creating a Data Marvel (Comics) with Spring & Neo4j;10.10.2019 3:15 PM;10.10.2019 4:00 PM;Track 1;Regular Talk (~30 minutes);"Many of us have a great deal of experience working with traditional relational databases, and with so-called NoSQL databases (both document stores & key/value pairs) as well. Graph databases provide capabilities that we may not have fully leveraged…​yet.<br>Come to this session to learn how to exploit the power of Neo4j quickly and powerfully using Spring Boot and Spring Data. The presenter will explain how to handle importing a real-world data set (complete with obstacles and workarounds) to the graph, then live-code a Spring Boot+Spring Data application to demonstrate how to really USE it.<br>Learn how to elevate the relationships&nbsp;among your data&nbsp;to the same level&nbsp;as&nbsp;your data and tap the full power of Spring Data & Neo4j!";Jennifer Reif;Neo4j;All,Beginner;ai-ml,crime,investigation,java,spring,modeling,etl;mavel-comics-spring-data-neo4j-modeling-import-querying
68;Building Spatial Search Algorithms for Neo4j;10.10.2019 10:45 AM;10.10.2019 11:30 AM;Track 3;Regular Talk (~30 minutes);Graphs and Geospatial are natural partners. And yet, Neo4j has native support for only the simplest spatial type, the Point. Is this a problem? What if you want to perform more complex spatial searches, spatial modeling or spatial algorithms using complex types like polygons and multi-polygons? At graphconnect 2018 we showed you how to write a web app that demonstrated route finding using A-Star and spatial search using a point-in-polygon algorithm. This talk will take that further, showing you how to write your own spatial algorithms for more complex analyses and how to integrate them into a web-app through user defined functions accessible with Cypher queries. To demonstrate this we will use a new library we've been working on to prototype complex spatial algorithms within Neo4j.<br />;Craig Taverner;Neo4j;Advanced;spatial,transport-infrastructure;spatial-search-algorithms-neo4j
69;Monitoring Neo4j Servers and Clusters;10.10.2019 1:00 PM;10.10.2019 1:45 PM;Track 3;Regular Talk (~30 minutes);"A database is a complicated piece of software that takes care and feeding. Because it’s a core component, you need to know whether it’s running well, and if not, why not. Monitoring is about gathering data to determine this, and figuring out what you need to do to make your system better.<br><br>In this session we'll cover some of the basics about cluster health that you'll want to understand about your Neo4j instance.&nbsp; We'll use Halin and its diagnostic features to explore the configuration of a working cluster, find issues, and learn how we can improve the run-time health and performance of a Neo4j system.";David Allen;Neo4j;Intermediate;operations,cloud;monitoring-neo4j-servers-clusters-halin
7;Discovering the Soul of a Product With Neo4j;10.10.2019 1:00 PM;10.10.2019 1:45 PM;Track 2;Regular Talk (~30 minutes);At Under Armour many disjointed systems are involved in bringing a product to market. Customer service reps and data scientists don't always have access to the data they need. We set out to capture that data from each system, expose it with the GRANDstack and make it available to our teammates.;Pat Brown;Under Armour;All;javascript,etl-data-integration,data-science-algos,ai-ml,grandstack-graphql,manufacturing;discover-soul-product-neo4j
71;Graph Visualization: Main aspects, challenges and solutions;10.10.2019 10:45 AM;10.10.2019 11:30 AM;Track 1;Regular Talk (~30 minutes);"We are going to explore main aspects of Graph Visualisation; finding data, laying it out and rendering. We will discuss challenges of each step and present some solutions we’ve applied along with libraries and tools available (mostly web based)";Irfan Nuri Karaca;Neo4j;Advanced,Intermediate;cypher,etl-data-integration,knowledge-graph,linked-data,javascript,graph-visualization;visualizing-graph-data-javascript
72;Data Integration for Neo4j using Kettle;10.10.2019 1:45 PM;10.10.2019 2:30 PM;Track 3;Regular Talk (~30 minutes);"Loading data into Neo4j can be a complex endeavour if you take into account data extraction, calculations, lookups, cleanup of data quality and so on.&nbsp; In this presentation we'll show you how to make your life easier when dealing with these challenges.&nbsp; We'll go over the basic Kettle toolset and the various Neo4j integration points with a number of live demos.&nbsp; Finally we'll point you to the downloads and documentation to get started right away with Kettle and Neo4j.";Matt Casters;Neo4j;All,Intermediate;ai-ml,crime,investigation,etl,modeling;data-integration-kettle-neo4j
73;Neosemantics - A Linked Data Toolkit for Neo4j;10.10.2019 10:45 AM;10.10.2019 11:30 AM;Track 2;Regular Talk (~30 minutes);"<a href=""http://jbarrasa.github.io/neosemantics/"" target=""_blank"">NSMNTX</a> is a plugin that enables the use of RDF/Linked Data in Neo4j and I'm glad to announce that it is joining <a href=""https://neo4j.com/labs"" target=""_blank"">Neo4j Labs</a>.<br><br>In this lightning talk I will describe the key features in NSMNTX including<br><ul><li>Lossless import/export of RDF and Ontologies</li><li>Model mapping</li><li>Inferencing...</li></ul><br>I will also give you ideas on when and how to use NSMNTX, how can you get started and where to find help and documentation.";Jesus Barrasa;Neo4j;Advanced;cypher,etl-data-integration,knowledge-graph,linked-data;neosemantics-linked-data-rdf-toolkit
74;RDKit (cheminformatics) Neo4j Integration;10.10.2019 2:30 PM;10.10.2019 2:50 PM;Track 5;Lightning Talk (10 minutes);Chemical data models usually require a database to be able to deal with chemical structures to be utilized for structure based queries to either identify records or as filtering criteria.<br>Motivation of this GSoC project was implementation of connection of RDKit, a well known and widely used open source software for dealing with chemical structures, with neo4j, a well known and widely used graph database.<br><br>• store and index chemical structure information on Neo4j nodes<br>• conduct exact as well as sub-structure searches to identify entry points to the graph<br>• filter paths with exact and sub-structures to create focussed results;Evgeny Sorokin;Student;Intermediate;healthcare-biotech,etl-data-integration;rdkit-neo4j-integration
75;Streaming Graph Data with Kafka;10.10.2019 12:15 PM;10.10.2019 1:00 PM;Track 4;Regular Talk (~30 minutes);"In this presentation we give an high level overview of the Neo4j-Kafka integration and the Confluent partnership.&nbsp;<br>Providing change-data-capture and ingestion capabilities as Neo4j Extension and the Kafka Connect Neo4j Sink on Confluent Hub allows you to integrate real-time streaming with graph querying and analytics.";Andrea Santurbano;Neo4j,Larus;All,Intermediate;ai-ml,crime,investigation,etl-data-integration,streams;streaming-graphs-kafka
76;Tuning Cypher;10.10.2019 2:30 PM;10.10.2019 3:15 PM;Track 4;Regular Talk (~30 minutes);Cypher is really easy to write. On large datasets or complex queries you sometimes might not get the performance you want out of the box. In this session Andrew demonstrates the most useful tips on analysing and then step-by-step tuning Cypher queries to perform within your requirements.<br><br>You will learn which metrics to watch out for and how to read query plans.;Andrew Bowman;Neo4j;Advanced;cypher,apoc-procedures,operations;tuning-cypher
77;Intro to Graphlytic - graph visualization application;10.10.2019 2:50 PM;10.10.2019 3:15 PM;Track 5;Lightning Talk (10 minutes);Graphlytic (@graphlytic) is a customizable web application for graph visualization, analysis and automation. We are using Graphlytic in various use cases, mainly code refactoring, fraud detection, communication visualization, workflow analysis and IT infrastructure modeling. In this talk we want to show main features of Graphlytic and how to use them in different scenarios.;Michal Habala;Graphlytic;All;graph-visualization,graph-apps,analysis;intro-graphlytic-graph-visualization
78;Improve your Cypher Performance with the Query Log Analyzer;10.10.2019 10:20 AM;10.10.2019 10:45 AM;Track 5;Lightning Talk (10 minutes);In this lightning talk I will explain the usage of the Query Log Analyzer including:<br>* Query Log Summary<br>* Query Optimizations<br>* Future functionality;Kees Vegter;Neo4j;Advanced;cypher,graph-apps,analysis;cypher-performance-query-log-analyzer
79;Leveraging Graph Algorithms In Visualizations With Neovis.js;10.10.2019 1:00 PM;10.10.2019 1:20 PM;Track 5;Lightning Talk (10 minutes);"See how to use combine graph visualization and graph algorithms to make sense of data in this live coding lightning session. We'll see how we can use centrality &nbsp;and community detection algorithms to enhance a graph visualization using the Neovis.js graph visualization library along with Neo4j Graph Algorithms.";William Lyon;Neo4j;Beginner;graph-visualization,javascript,cypher,data-science-algos;graph-algos-visualization-neovis
8;Recommendations in UDC (Unified Data Catalog) Powered by Apache Spark & Neo4J;10.10.2019 11:30 AM;10.10.2019 12:15 PM;Track 2;Regular Talk (~30 minutes);"Unified view of an enterprise's data assets is extremely powerful in solving data problems. But searching & viewing relevant information turns into an overwhelming experience. Recommending data assets by ""connecting"" [users, orgs, searches, queries, more] makes data catalog extremely relevant.";"Deepak Chandramouli; Harsh Bhimani";PayPal;All;data-science-algos,spark,python,manufacturing,cypher,recommendation;recommendations-unified-data-catalog-spark-neo4j
80;Schema-Based Security in Neo4j 4.0;10.10.2019 4:00 PM;10.10.2019 4:30 PM;Track 2;Regular Talk (~30 minutes);The next major Neo4j release is around the corner and will, among many other exciting news, contain a more fine-grained schema-based security model. In this talk you will get a sneak-peak of how the new administration commands will look and what you can achieve with them.<br><br>;Louise Söderström;Neo4j;Advanced;operations,security;schema-based-security
9;Databases on Kubernetes Using a Custom Operator: Day 1, Day 2, and Beyond;10.10.2019 10:00 AM;10.10.2019 10:45 AM;Track 2;Regular Talk (~30 minutes);We started the journey of building a managed cloud version of the graph database Neo4j. A bit later we started developing an operator to manage multiple database clusters in k8s.<br>In this session we want to share the lessons we learned writing this operator and using it in production for over a year.;Johannes Unterstein;Neo4j;All;cloud,k8s,technology;databases-kubernetes-k8s-custom-operator

I'm glad you shared your code from the conference.

There's a misspelling in the cypher, epocMillis should be epochMillis. It's missing the letter h

Thanks a lot, fixed.