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 →
Keywords: Connected Data • data analysis • data modeling • fraud detection • graph algorithms • graph database • graph technology • machine learning • money laundering • social media networks
Simplicity Wins: We’re Shifting to a Open Core Licensing Model for Neo4j Enterprise Edition
By Bryce Merkl Sasaki
November 15, 2018|
Reading time: 2 minutes
TL;DR: Starting with Neo4j 3.5, Enterprise Edition source code will no longer be published to the open source commons, including future versions. This does not impact Neo4j Community Edition. We will continue to deliver the world’s best and most comprehensive… Read more →
Keywords: cypher • graph algorithms • graph database • graph technology • neo4j • Neo4j Community • Neo4j Desktop • Neo4j Graph Platform • open core • open source
Creating a Data Distribution Knowledge Base Using Neo4j
By Jocelyn Hoppa
November 14, 2018|
Reading time: 10 minutes
Editor’s Note: This presentation was given by Syed Haniff at GraphConnect Europe in May 2017. Presentation Summary UBS bank was relying on a data distribution model that was no longer serving its internal consumers, largely because it required its users… Read more →
Keywords: data distribution platform • data insights • data lineage • graph database • graphconnect • knowledge base • metadata • neo4j • reference data • UBS
Graph Databases for Beginners: ACID vs. BASE Explained
By Bryce Merkl Sasaki
November 13, 2018|
Reading time: 4 minutes
When it comes to NoSQL databases, data consistency models can sometimes be strikingly different than those used by relational databases (as well as quite different from other NoSQL stores). The two most common consistency models are known by the acronyms… Read more →
Keywords: ACID • aggregate stores • base • consistency model • data consistency • graph database • neo4j • nosql • nosql database • relational database
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 →
Keywords: ai • artificial intelligence • Connected Data • fraud detection • graph database • graph technology • machine learning • ML • neo4j • Recommendation Engine
Graphs in Time and Space: A Visual Example
By Jocelyn Hoppa
October 31, 2018|
Reading time: 7 minutes
Editor’s Note: This presentation was given by Dan Williams at GraphConnect Europe in May 2017. Presentation Summary Graph databases are helping to solve some of today’s most pressing challenges. From managing critical infrastructure and understanding cyber threats to detecting fraud,… Read more →
Keywords: Cambridge Intelligence • data insights • Data Visualization • graph data visualization • graph database • graph topology • graph visualization • graphconnect • Keylines
Graph Algorithms in Neo4j: The Rise of Graph Analytics
By Jocelyn Hoppa
October 29, 2018|
Reading time: 4 minutes
According to Gartner’s 2018 Magic Quadrant for Data Management Solutions, the biggest reason for using the Neo4j graph database “is to drive innovation.” This blog series is designed to help organizations better leverage graph analytics to effectively innovate and develop… Read more →
Keywords: ai • Connected Data • eBay • google • graph algorithms • Graph Analytics • graph database • Graph Theory • linkedin • machine learning • Uber
NLP at Scale for Maintenance and Supply Chain Management
By Jocelyn Hoppa
October 24, 2018|
Reading time: 14 minutes
Editor’s Note: This presentation was given by Ryan Chandler at GraphConnect New York in October 2017. Presentation Summary Caterpillar is a 90-year-old company that manufactures large industrial machinery, including some autonomous vehicles. For the last decade, the company has been… Read more →
Keywords: artificial intelligence • Caterpillar • cypher • graph database • graph query • graphconnect • knowledge representation • machine learning • natural language processing • supply chain management
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 →
Keywords: fraud detection • Graph Analytics • graph database • graph technology • Graph Theory • identity access management • machine learning • regulatory compliance • Relational Databases • supply chain
Graph Algorithms in Neo4j: The Power of Graph Analytics
By Jocelyn Hoppa
October 22, 2018|
Reading time: 4 minutes
According to Gartner, “graph analysis is possibly the single most effective competitive differentiator for organizations pursuing data-driven operations and decisions.” Why did Gartner say this? Because graphs are the best structure for today’s complex and ever changing data, and if… Read more →
Keywords: Connected Data • Gartner • graph algorithms • graph analysis • Graph Analytics • graph database • graph models • Graph Theory • neo4j • Network Science
Chip Design on Graphs: 5-Minute Interview with Chuck Calio, Offering Manager, IBM PowerAI
By Jocelyn Hoppa
October 19, 2018|
Reading time: 4 minutes
We use Neo4j to design our next-generation Power chips, said Chuck Calio, Offering Manager IBM PowerAI at IBM. The future of graph technology is in AI, but it’s not the only use case. From designing hardware (naturally a graph) to… Read more →
Keywords: 5-minute interview • ai • dynamic pricing • graph algorithms • graph database • graph technology • machine learning • Master Data Management • nosql • Recommendation Engine
Decyphering Your Graph Model
By Jocelyn Hoppa
October 17, 2018|
Reading time: 7 minutes
Editor’s Note: This presentation was given by Dom Davis at GraphConnect Europe in May 2017. Presentation Summary Graphs really are everywhere, and building your graph database model from the highest possible vantage point using natural language – and the language… Read more →
Keywords: configuration management database • cypher • graph database • graph database model • graph model • graphconnect • natural language model • neo4j • property graph • relational database
Graph Algorithms in Neo4j: Connected Data & Graph Analysis
By Jocelyn Hoppa
October 15, 2018|
Reading time: 5 minutes
Until recently, adopting graph analytics required significant expertise and determination, since tools and integrations were difficult and few knew how to apply graph algorithms to their quandaries and business challenges. It is our goal to help change this. We are… Read more →
Keywords: Big Data • big data analysis • Connected Data • data valence • graph algorithms • graph analysis • Graph Analytics • graph database • Network Science • statistical analysis
Enterprise AI for IT Ops: 5-Minute Interview with Clayton Ching, Global Head of Customer Success at Digitate
By Jocelyn Hoppa
October 12, 2018|
Reading time: 4 minutes
“I believe everyone in the IT ops space is going to have to implement graph data a lot sooner than they think,” said Clayton Ching, Global Head of Customer Success at Digitate. IT operations is complex, with thousands of systems… Read more →
Keywords: 5-minute interview • ai • enterprise applications • graph database • graph technology • it infrastructure • IT ops • nosql • Relational Databases • SAP ERP
Effective Internal Risk Models for FRTB Compliance: Risk Management with Neo4j [Infographic]
By Jocelyn Hoppa
October 8, 2018|
Reading time: 1 minute
In this series on the FRTB, we delved into what is required for effective internal risk models using a graph database like Neo4j. In previous weeks, we looked at the requirements of FRTB compliance and the relationship between risk modeling… Read more →
Keywords: data lineage • data silos • frtb compliance • FRTB Risk Management • graph database • investment risk • neo4j • risk assessment • trace risk data lineage • trading desks
Graphs Are Game-Changing for Cybersecurity: 5-Minute Interview with Eric Spiegelberg, Senior Consultant at GraphAware
By Jocelyn Hoppa
October 5, 2018|
Reading time: 4 minutes
“Cyber threat intelligence is high volume, unstructured and highly related. That last attribute makes it great for graphs,” said Eric Spiegelberg, Senior Consultant at GraphAware. In this week’s five-minute interview (conducted at GraphConnect New York), we discuss GraphAware’s work on… Read more →
Keywords: 5-minute interview • cyber threat • cybersecurity • graph database • graph technology • GraphAware • graphconnect • natural language processing • nlp • Panama Papers
Effective Internal Risk Models for FRTB Compliance: Modern Graph Technology Is the Answer
By Jocelyn Hoppa
October 1, 2018|
Reading time: 4 minutes
Relational database technology can’t handle what is coming in banking and risk modeling. By the 2020s, Accenture predicts current banking business models will be swept away by a tide of ever-evolving technology and other rapidly occurring changes. The right foundation… Read more →
Keywords: bank regulations • BCBS • data connections • data lineage • data silos • financial services • frtb compliance • graph database • graph technology • risk • risk model
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 →
Keywords: cyber threats • cypher • data model • fraud detection • geospatial information • graph database • graph visualization • Keylines
ICYMI: (Mostly) Everything Important that Happened at GraphConnect 2018
By Bryce Merkl Sasaki
September 25, 2018|
Reading time: 4 minutes
Unless you live under a graph database rock, then you know that the biggest graph technology event of the year – GraphConnect 2018 – happened last week, and it was wondrous to behold. From September 20-22, Neo4j customers, partners, celebrities,… Read more →
Keywords: artificial intelligence • Connected Data • graph database • graph platform • graph technology • graphconnect • Graphs4Good • Hilary Mason • machine learning • Neo4j 3.5
Bring Order to Chaos: A Graph-Based Journey from Textual Data to Wisdom
By Jocelyn Hoppa
September 19, 2018|
Reading time: 10 minutes
Data is everywhere. News, blog posts, emails, videos and chats are just a few examples of the multiple streams of data we encounter on a daily basis. The majority of these streams contain textual data – written language – containing… Read more →
Keywords: ai • Connected Data • cypher • enterprise search engine • graph database • GraphAware Hume • Knowledge Graph • machine learning • nlp • Recommendation Engine
Custom Visualization Solutions: Getting the Most Out of Your Data
By Jocelyn Hoppa
September 18, 2018|
Reading time: 6 minutes
Neo4j is perfect for storing and processing large amounts of connected data. For example, in web analytics, where click-paths and custom events get logged, it is easy to get that data into Neo4j. Once the data is in the graph… Read more →
Keywords: Connected Data • cypher • Data Visualization • diagram data • diagram visualization • graph database • graphconnect • neo4j • Recommendation Engines • yFiles
5 Ways to Tackle Big Graph Data with KeyLines and Neo4j
By Jocelyn Hoppa
September 11, 2018|
Reading time: 6 minutes
Understanding big graph data requires two things: a robust graph database and a powerful graph visualization engine. That’s why hundreds of developers have combined Neo4j with the KeyLines graph visualization toolkit to create effective, interactive tools for exploring and making… Read more →
Keywords: Big Data • cypher • data funnel • data management • data modeling • Data Visualization • graph analysis tools • graph database • graph visualization • Keylines
Effective Internal Risk Models for FRTB Compliance: The Importance of Risk Model Approval
By Jocelyn Hoppa
September 10, 2018|
Reading time: 4 minutes
Sweeping regulations are changing the way banks handle risk. The Fundamental Review of the Trading Book (FRTB) represents an important shift designed to provide a firm foundation for the future. While laws passed after the financial crisis offered a patchwork,… Read more →
Keywords: Basel IV • BCBS • data lineage • data silos • FRTB • graph database • internal risk model approval • internal risk models • risk compliance • risk management
Graph Databases for Beginners: Graph Theory & Predictive Modeling
By Joy Chao
September 5, 2018|
Reading time: 9 minutes
There’s a common one-liner, “I hate math…but I love counting money.” Except for total and complete nerds, a lot of people didn’t like mathematics while growing up. In fact, of all school subjects, it’s the most consistently derided in pop… Read more →
Keywords: graph database • Graph Theory • local bridge • Network Science • predictive analysis • predictive modeling • Social Graph • social science • structural balance • triadic closure
Powering Recommendations with a Graph Database: A Rapid Retail Example
By Jocelyn Hoppa
September 3, 2018|
Reading time: 5 minutes
It’s one thing to say that Neo4j streamlines real-time recommendations; it’s another to show you the code so you can see for yourself. In this series, we discuss how real-time recommendations support a number of different use cases, from product… Read more →
Keywords: cypher • entity-relationship diagram • facebook • graph database • graph technology • neo4j • real-time recommendations • Recommendations • Retail Recommendations • schema
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