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.
Featured Community Member: Felienne Hermans
This week’s featured community member is Felienne Hermans, Assistant Professor at Delft University of Technology.
Felienne Hermans – This Week’s Featured Community Member
Felienne became known in the Neo4j community for her popular talk ‘spreadsheets are graphs’, which she presented at GraphConnect Europe 2015, GOTO Berlin 2015, and several other conferences and meetups. You can also read a transcript of the talk if you’re not a fan of video content.
Felienne uses Neo4j to do graph analysis on spreadsheets to help find code smells and areas of spreadsheets that need refactoring. She explains this in detail in her interview on Rik Van Bruggen’s Graphistania podcast.
And this week Felienne achieved tenure!
On behalf of the Neo4j community, congratulations Felienne and thanks for all your work!
Graph of Thrones, Salesforce, Fraud Analysis
- Jhonathan de Souza shared the slides from “Graph of Thrones – Neo4j + Game of Thrones”. This one’s in Portuguese and if you’re having Game of Thrones withdrawal symptoms now that Season 7 is over you can always watch our Graph of Thrones online meetup from a couple of weeks ago.
- Joe Gaska has created graphconnect, which allows you to quickly connect your Salesforce objects to the Harding Point object graph. Harding Point then uses an AI powered neural network to find hidden paths to revenue, cost savings, and reduce operational burden.
- Bobby Narang wrote up his experience attending the Streamsets + Salesforce + Neo4j meetup in San Francisco last week. This one was recorded so you can watch it on our YouTube channel if you weren’t able to attend in person.
- Elise Devaux explains how BforBank detects and investigates fraud faster with Linkurious and Neo4j, which includes this quote by BforBank‘s Alexandre Dressayre: “several factors motivated the choice of the Linkurious solution, notably the bundle offered by the company. An off-the-shelf visualization and analysis software along with the Neo4j graph database solution was a perfect fit for us.”
Online Meetup: Analysing the football transfer window
We showed how to import CSV data, clean it up, make implicit relationships explicit, and find some unexpected insights using the Cypher query language.
Work Order Management, Kotlin Procedures, Graphing Causal Events
- Max De Marzi wrote Work Order Management with Neo4j in which he shows how to build an evented work order model.
- Byron Ruth shows how to use NATS Streaming with Minio and Neo4j for causal graphing of events in a short YouTube video.
- Marco Falcier has created neo4j-kotlin-procedure-example, in which he shows how to create a Neo4j stored procedure using the Jetbrains’ Kotlin programming language.
- On StackOverflow I found a couple of interesting questions where the answer requires you to use variable length pattern matching. This is one of the most fun features to use in Cypher, so have a look and see if you need those types of queries in your application.
What’s happening next week in the world of graph databases?
September 5th 2017
September 5th 2017
September 6th 2017
September 6th 2017
Mark Needham, Pete Moore, Simon Eversfield
September 7th 2017
Tweet of the Week
My favourite tweet this week was by Iryna Feuerstein:
Don’t forget to RT if you liked it too.
That’s all for this week. Have a great weekend!
About the Author
Mark Needham, Developer Relations Engineer
Mark Needham is a graph advocate and developer relations engineer at Neo4j.
As a developer relations engineer, Mark helps users embrace graph data and Neo4j, building sophisticated solutions to challenging data problems. Mark previously worked in engineering on the clustering team, helping to build the Causal Clustering feature released in Neo4j 3.1. Mark writes about his experiences of being a graphista on a popular blog at markhneedham.com. He tweets at @markhneedham.