Toward AI Standards: Context Makes AI More Robust
By Jocelyn Hoppa
July 15, 2019|Reading time: 4 minutes
Read this third blog in our series “Toward AI Standards” and discover how graph technology adds context to data relationships for more robust AI solutions.
Explore: ai • AI application • AI solution • Boeing • chatbot • Data Relationships • fraud detection • graph algorithms • graph analysis • graph platform • machine learning • neo4j
Transforming the Enterprise: AI at Scale with Neo4j
By Jocelyn Hoppa
April 24, 2019|Reading time: 18 minutes
Discover how Ernst and Young takes advantage of graph-driven enterprise AI and machine learning to develop stronger fraud-detection and customer 360 mapping tools.
Explore: AI at scale • customer 360 • enterprise AI • fraud detection • Graph Analytics • graph database • graph learning • graph recommendation engine • graphconnect • machine learning
Fraud Detection Using Graph Technology
By Jocelyn Hoppa
November 16, 2018|Reading time: 4 minutes
Graph technology refers to the storage, management and querying of data graphical representation. Here, your indices become vertices and your relationships are converted into edges. Through analysis of the fine-grained relationships, by using graph analysis, you can find out oddities… Read more →
Explore: Connected Data • data analysis • data modeling • fraud detection • graph algorithms • graph database • graph technology • machine learning • money laundering • social media networks
Graph Algorithms in Neo4j: Use Cases for Graph Transactions & Analytics
By Jocelyn Hoppa
November 5, 2018|Reading time: 4 minutes
Today’s most pressing data challenges center around connections, not just tabulating discrete data. Graph analytics accelerate breakthroughs across industries with more intelligent solutions. This blog series is designed to help you better leverage graph analytics so you can effectively innovate… Read more →
Explore: ai • customer 360 • eBay • fraud detection • graph algorithms • Graph Analytics • identity and access management • Network Monitoring • real-time recommendations • Social Networks
How to Know What You Know:
5-Minute Interview with Dr. Alessandro Negro, Chief Scientist at GraphAware
By Jocelyn Hoppa
November 2, 2018|Reading time: 4 minutes
“I want to know what I know. That describes what knowledge graphs do for companies,” said Dr. Alessandro Negro, Chief Scientist at GraphAware. In this week’s five-minute interview, we discuss how GraphAware uses natural language processing to help companies gain… Read more →
Explore: 5-minute interview • data model • fraud detection • graph algorithms • graph technology • Knowledge Graph • machine learning • natural language processing • Recommendation Engine • textual data
We Just Closed the Largest Single Investment in the Graph Space. Now What?
By Bryce Merkl Sasaki
November 1, 2018|Reading time: 5 minutes
I’m thrilled to announce that Neo4j has just closed $80 million in a series E funding round. We are happy to welcome One Peak Partners and Morgan Stanley Expansion Capital to the graph of Neo4j funders. I’d also like to… Read more →
Explore: ai • artificial intelligence • Connected Data • fraud detection • graph database • graph technology • machine learning • ML • neo4j • Recommendation Engine
5 Noteworthy Use Cases of Graph Technology and Graph Analytics
By Jocelyn Hoppa
October 23, 2018|Reading time: 4 minutes
When discussions about any technological concept begin to trend in online media and among business stakeholders, it is only natural to wonder whether it is all hype or whether the technology actually solves any real business problems. Gartner’s well-publicized hype… Read more →
Explore: fraud detection • Graph Analytics • graph database • graph technology • Graph Theory • identity access management • machine learning • regulatory compliance • Relational Databases • supply chain
Mapping a Connected World: The Value of Geospatial Graph Visualization
By Jocelyn Hoppa
September 27, 2018|Reading time: 6 minutes
One of the world’s first maps featured the night sky. Surprisingly, it also featured connected data. Over 1,000 years ago, Chinese astronomers used manuscript to plot 1,300 stars, recognizing the importance of making connections between clusters to identify constellations. Their… Read more →
Explore: cyber threats • cypher • data model • fraud detection • geospatial information • graph database • graph visualization • Keylines
Taking the First Step: How to Lead a Local Neo4j GraphDB Meetup
By Jocelyn Hoppa
August 2, 2018|Reading time: 3 minutes
I discovered Neo4j and became instantly captivated. Finding something that made data make sense, was fun, approachable, and easier to learn, I read articles and white papers, watched videos online… but it wasn’t enough. I needed to connect, with people,… Read more →
Explore: Big Data • Connected Data • data science • fraud detection • graph algorithms • Graph Databases • graphitude • neo4j meetup • nodes • relationships
Graph Databases for Beginners: Data Modeling Pitfalls to Avoid
By Bryce Merkl Sasaki
July 31, 2018|Reading time: 6 minutes
With the advent of graph database technology, data modeling has become accessible to masses. Mapping business needs into a well-defined structure for data storage and organization has made a sortie du temple (of sorts) from the realm of the well-educated… Read more →
Explore: Connected Data • cybersecurity • data model • data modeling • fraud detection • graph data model • graph data modeling • graph database • graph model • graph technology
This Week in Neo4j – Moving Adobe Behance from Cassandra to Neo4j, New Go Driver, Emil on The New Stack Makers Podcast
By Mark Needham
July 21, 2018|Reading time: 5 minutes
Welcome to this week in Neo4j where we round up what’s been happening in the world of graph databases in the last 7 days. This week David Fox explains how his team at Adobe moved from a 48 instance Cassandra… Read more →
Explore: Adobe • APOC • emil eifrem • fraud detection • google cloud platform • Google Kubernetes Engine • python • RDF • twin4j • yFiles
Graph Technology for Enterprise Master Data Management (MDM)
By Rachel Howard
July 14, 2017|Reading time: 8 minutes
Editor’s Note: This presentation was given by Aaron Wallace at GraphConnect San Francisco in October 2016. Presentation Summary Modern enterprises need to have a full, 360-view of their customers drive their bottom line. This requires the integration of data from… Read more →
Explore: customer information management • data quality • fraud detection • graphconnect • Knowledge Graph • Master Data Management • MDM • metadata management • Pitney Bowes • single customer view
Financial Services & Neo4j: Anti-Money Laundering
By Bryce Merkl Sasaki
June 26, 2017|Reading time: 3 minutes
Reducing the risk of money laundering presents a similar challenge to that of fraud detection when it comes to today’s financial services landscape. Firms need to know where funds come from and where they are headed, but criminals use indirection… Read more →
Explore: AML • anti-money laundering • cypher • Data Visualization • financial services • fraud detection • graph technology • money transfer • smurfing • sql
Financial Services & Neo4j: Fraud Detection
By Bryce Merkl Sasaki
June 19, 2017|Reading time: 5 minutes
Identifying and stopping fraudulent activity is harder than ever for financial services organizations. Standard anti-fraud technologies — such as a deviation from normal purchasing patterns — use discrete data. This is useful for catching individual criminals acting alone, but discrete… Read more →
Explore: Connected Data • cypher • Data Visualization • financial services • Fortune 500 • fraud detection • fraud ring • graph technology • Microsoft SQL Server • relational database
Fraud Prevention with Neo4j: A 5-Minute Overview
By Bryce Merkl Sasaki
April 21, 2017|Reading time: 4 minutes
Fraud is becoming increasingly difficult to discover and prevent as fraudsters are increasingly employing complex techniques and advanced technologies to perpetrate fraud. Who Are Today’s Fraudsters? Today, fraudsters are organized in groups, possess synthetic or manufactured identities – which in… Read more →
Explore: credit card fraud • data science • ecommerce fraud • financial services • fraud detection • fraud pattern • fraud prevention • Fraud Rings • Insurance Fraud • pattern analysis
The 5-Minute Interview: Chuck Kane, Director of Global Solutions at Pitney Bowes
By Rachel Howard
March 17, 2017|Reading time: 3 minutes
“Moving from relational to graph, it takes time to learn to step back from your data and ask, ‘What more can I do?’” said Chuck Kane, Director of Global Solutions at Pitney Bowes. The company partnered with Neo4j to provide… Read more →
Explore: 5-minute interview • AML • Connected Data • Data Relationships • fraud detection • graph database • neo4j • pattern analysis • Pitney Bowes • relational database
The 5-Minute Interview: Andrés Natanael Soria, Senior Software Architect at Cablevisión
By Rachel Howard
March 10, 2017|Reading time: 2 minutes
“Due to native graph storage, the Neo4j queries run really quickly, which is amazing,” said Andrés Natanael Soria, Senior Software Engineer at Cablevisión Fibertel. The company uses a broadband network to provide cable television and internet services to customers throughout… Read more →
Explore: 5-minute interview • apache kafka • data model • docker • fraud detection • impact analysis • native graph storage • network failure detection • Recommendation Engine • sql
Couchbase & JDBC Integrations for Neo4j 3.x
By Bryce Merkl Sasaki
November 22, 2016|Reading time: 3 minutes
Editor’s Note: This presentation was given by Lorenzo Speranzoni at GraphConnect Europe in April 2016. Here’s a quick review of what he covered: Converting JSON documents into nodes Couchbase integration architecture How the JDBC driver makes use of the Bolt… Read more →
Explore: bolt • Couchbase • fraud detection • graph database • graphconnect • jdbc • json • neo4j 3.0 • Recommendation Engine • Spotify
Detect & Investigate Financial Crime Patterns with Linkurious
By Bryce Merkl Sasaki
October 7, 2016|Reading time: 5 minutes
Linkurious is a Bronze sponsor of GraphConnect San Francisco. Meet their team on October 13-14th at the Hyatt Regency SF. Using Graphs to Fight Financial Crime Financial crime can take many forms: money laundering, terrorism funding, corruption, tax evasion, insurance… Read more →
Explore: AML • anti-money laundering • cypher • financial crime • fraud detection • Geospatial • Insurance Fraud • Linkurious • tax evasion • terrorism funding
The 5-Minute Interview: Mar Cabra, Editor at the ICIJ
By Bryce Merkl Sasaki
June 24, 2016|Reading time: 7 minutes
For this week’s 5-Minute Interview, I sat down with Mar Cabra, the Data & Research Unit Editor at the International Consortium of Investigative Journalists (ICIJ). I caught up with Mar at GraphConnect Europe after her standing-room-only keynote: “How the ICIJ… Read more →
Explore: 5-minute interview • data analysis • ETL tool • fraud detection • graph visualization • graphconnect • icij • Linkurious • Mossack Fonseca • Panama Papers
The 5-Minute Interview: Jean Villedieu, Co-Founder of Linkurious
By Bryce Merkl Sasaki
June 10, 2016|Reading time: 3 minutes
For this week’s 5-Minute Interview, I chatted with Jean Villedieu, a co-founder of Linkurious. I sat down with Jean at GraphConnect Europe last April. Here’s what we discussed: Q: For people who might not be familiar with it, what is… Read more →
Explore: 5-minute interview • anti-fraud • cybersecurity • fraud detection • graph visualization • graphconnect • knowledge management • Linkurious • Network Management • Panama Papers
Stop Fraud Rings in Their Tracks with Graph Databases [Infographic]
By Bryce Merkl Sasaki
May 16, 2016|Reading time: 1 minute
Fraud rings are big business. First-party bank fraud costs banks (and their customers) over $16 billion each year in the United States, and insurance fraud costs nearly $80 billion annually. And fraud rings organized around ecommerce fraud rack up nearly… Read more →
Explore: bank fraud • ecommerce fraud • fraud analytics • fraud detection • Fraud Rings • Graph Databases • infographic • Insurance Fraud • neo4j • organized fraud
(Un)common Use Cases for Graph Databases
By Bryce Merkl Sasaki
April 18, 2016|Reading time: 4 minutes
At GraphAware, we live and breathe Neo4j. For three years, we have been helping customers around the world embrace this amazing technology as a solution to many interesting problems. Mainstream applications of graphs, such as real-time recommendations, fraud detection, impact… Read more →
Explore: cypher • fraud detection • graph database • GraphAware • graphconnect • investment portfolio • law enforcement • neo4j • real-time recommendation • rules engine
Graphs Are Everywhere and Their Possibilities Are Endless
By Bryce Merkl Sasaki
April 13, 2016|Reading time: 3 minutes
Graphs are everywhere, and with the ability of a graph database to solve multiple business problems, pre-empt potential situations and – most importantly – save companies huge amounts of money in the meantime, why shouldn’t you use Neo4j? Graphs in… Read more →
Explore: Connected Data • eSynergy solutions • first-party fraud • fraud detection • graph • logistics • Master Data Management • neo4j training • synthetic identity • triadic closure
From the Neo4j Community: February 2016
By Bryce Merkl Sasaki
March 8, 2016|Reading time: 3 minutes
In the Neo4j community last month, love was in the air. That love expressed itself as more nodes than ever in our community content. From articles and podcasts to GraphGists and other projects, our global graph of community members keeps… Read more →
Explore: cypher • data pipeline • elasticsearch • fraud detection • graph database • graph visualization • Master Data Management • metadata management • Neo4j Community • real-time recommendations