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Hello on Global Graph Celebration Day!

Hello on Global Graph Celebration Day!

– Hi, my name is Karin Wolok and I’m the Community Manager at Neo4j. I’m here to tell you a little bit about why people all around the world are excited about Global
Graph Celebration Day. What is Global Graph Celebration Day? A little over 300 years ago on April 15th, a man named Leonhard Euler was born. Euler later became a
legendary mathematician whose legacy endures today. In 1735 he decided to take on a problem that was regularly discussed by the residents in Königsberg, Germany. The city had seven bridges which connected two large
islands with the mainland. People had always wondered
if it was possible to cross each bridge once, and only once, to get back to their
original starting point. To tackle this problem,
Euler drew a picture consisting of dots, vertexes, representing the land masses, and lines, edges,
representing the bridges, that connected those land masses. This allowed him to simply trace the graph without actually lifting his pencil. After Euler discovered
that it was not possible, he coined the term for a graph where you can walk each edge exactly once, and return to the same vertex. This condition was called
the Eulerian circuit. This, my friends, was the
birth of graph theory. Neo4j is an ACID-compliant, schema-free, transactional graph database that allows you to store your data in the shape of a graph. It has index-free
adjacency that allows you to hop through many
connections very quickly. Neo4j can be a powerful tool to see how things are
connected to one another, find patterns in your data, pathfinding, and just
generally making sense of complexly connected data. This enables people who
see the worlds in graphs to tackle their connected data problems. Graphs are everywhere. Here’s how graphs, and this technology, are innovating our world today. – Hi everyone, I’m Pierre Romera. I am the CTO of the ICIJ. The ICIJ is a small organization that run huge investigations around data and global issues. What we did before was The Panama Papers or the Paradise Papers
that were amazing project that involved a lot of
journalists around the world. Those two projects represent
around four terabytes of data, close to thirty millions of documents. So we had to create tools in databases to be able to read everything
that was in those documents. To do so, we built a lot of
tools and scripts program that were able to extract
data to build databases. So from unstructured data,
we got structured data. At the end we had this huge database built at the top of Neo4j where every entities, offshore
entities, offshore companies were connected to people in many places in secure jurisdiction. Because of that we were able
to establish hidden pattern in the data and we were able to find connection between those people and connect the dot to be
able to build new stories. At the end, because of that, we are able to publish stories
involving very high-profile and demonstrating the potential tax evasion and illegal behavior that was in those jurisdiction. So thanks to the graph
that we were able to find hidden stories in the data. – I am Hilary Mason, the general manager for Machine Learning at Cloudera. So I was the founder of Fast Forward Labs about four and a half years ago where we do applied machine
learning research and advising to help customers really accelerate and embrace machine learning
and A.I. opportunities. We were acquired by
Cloudera about a year ago and are now Cloudera Fast Forward Labs. This morning I spoke about
the power of metaphor and how we think about the
problems we need to solve and how that metaphor can then drive the architectural decisions we make. And so, we work pretty
broadly in machine learning across a variety of industries,
use cases and techniques and within that we find that there are a few
really powerful metaphors that tend to resonate and, of course, graphs are one of those dominant metaphors where it just makes a lot
of intuitive sense to us that the world is represented
in nodes and edges and characteristics of the relationships between those nodes. – My name is David Meza. I’m the Chief Knowledge Architect at NASA Johnson Space Center. So how we use Neo4j at NASA: there’s a lot of different little projects that we’re working on, primarily when I started at
Neo4j about four years ago, I was looking at a concept
where we could explore our lessons learned database a lot faster and help our engineers and
scientists find information in those databases rather than going through your standard key-list search and being able to look
at the relationships between the different
lessons across the decades because as NASA we’ve
got fifty years of data. And even recently allowed
somebody in our Orion projects to be able to go back and
look at our Apollo information and prevented an issue they were having and it actually saved
them well over two years on that project and about
a million dollars too, of taxpayer funds. My name is Alicia Powers. I am the Senior Vice President at New York City Economic
Development Corporation. I work in the research department. I’m a data scientist. Well I came to Neo4j to
work on a hobby project. I was really interested
in understanding food and tried to build a
recommendation engine. So what made Neo4j stand
out to me was the ability to really see connections between different aspects of eating. So, not only do you have a person, you have when they’re
eating, how they’re eating, how much they’re eating. There’re all these
different points of data that you can use to make
a recommendation engine and if you’re using like a SQL or even a document database, it’s really hard to start
to see the patterns visually and I’m a visual learner, I love pictures and Neo4j presents the data in a way that people actually see the data, experience the data, live the data. – My name’s David Fox and I’m
a Software Engineer at Adobe and I work specifically on our Behance social network product. So the use case was our activity feed. So it’s a really user-facing
feature on Behance. It’s our homepage right now, you’ll see the feed of
activity from people you follow and curator categories you follow. So kind of content from our curators. – I’m Daniel Himmelstein. I’m a Data Scientist at
University of Pennsylvania. My use of Neo4j focuses
on encoding biological and medical knowledge into a network. And I decided that Neo4j
networks were the best way to encode this type of
knowledge, the knowledge produced by millions of studies
over the past fifty years into a network or into a computer. So we use Neo4j to represent the rich types that nodes or relationships can have in real world biological data. – My name is Alexander Jarasch. I’m from the German Center for
Diabetes Research in Germany which is a federal non-profit organization and we are studying diabetes in university hospitals
and basic research. We have Neo4j as a knowledge graph or a graph over our relational databases and we use Neo4j to connect
the different types of data, the different disciplines
across the locations, across species and across
different research areas. – My name is Ann Grubbs. I am the Chief Data Engineer for space I.T. at Lockheed Martin. We are using Neo4j as a
master data management tool. So we’re trying to get our product DNA laid out so that we can use that as a reference for other applications. So for analytics and to
understand how our business works. – My name is Andy Robbins. I’m a Red Teamer Penetration
Tester at SpecterOps, formerly from the Adaptive
Threat Division at Veris Group. I’ve been pentesting and red teaming for the past five years. Basically, we get paid to
break into organizations, steal their data and give them
a report on how we did it. So the most interesting
Neo4j project that we work on is a project called Bloodhound. Bloodhound is the result
of months of effort by myself, Rohan Berserker
and Will Schroeder and also based on years
of work by Will Schroeder with situational awareness in active directory environments. Basically, the Bloodhound lets a pentester or a red teamer do, is
map out the privileges in an enterprise and
also map out attack paths that go from a low privilege user all the way to a high privilege user or to a computer that
has a certain data asset or data objective on it. – Thanks for joining us for
Global Graph Celebration Day. Happy connecting.

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