This Week in Neo4j: Cybersecurity Analysis, BioCypher, Graph Data Science, Kubernetes, Wardley Maps, Hume 2.17, Cypher GraphAcademy Course


Welcome to this week’s newsletter, everyone! Check out the navigation of open-sourced cyber threat intelligence data with graph visualization and on-demand intelligence retrieval by Joshua Yu. Or try wrangling microbial data with Sixing Huang to create sharable graphs and accelerate the adoption of knowledge graphs in biomedical research.

Don’t forget to take advantage of the new series of workshops in March and April!

    • March 15, Intro to Neo4j, a hands-on introduction.
    • March 22, Intermediate Cypher Data Modeling and Importing Data: Advanced Cypher Functionality.
    • March 29, Building a Routing Application: Work With Geospatial Data.
    • April 12, Spring Data Neo4j: Concepts & Application Development: Configure and Access Neo4j Graph Databases From Spring Applications

    Learn more about it here.

    Cheers,
    Yolande Poirier

    P.S.: If you’re a developer building modern applications with GraphQL, don’t forget to take this short, two-minute survey. We want to hear from you!
     

    James Bowkett has over 20 years of experience as a lead developer delivering data-centric applications in the finance industry at various banks, hedge funds, and startups. He cares deeply about design and building quality into the heart of all software and is a firm advocate of XP practices such as TDD and BDD. Connect with him on LinkedIn.

    In his NODES 2022 presentation, “Tracing Your Data’s DNA”, he uses live demos and code examples to explore the creation of a data lineage graph using Change Data Capture (CDC) in source systems. Watch his talk!


     
    CYBERSECURITY: Empowering Open Source Cyber Threat Intelligence Analysis With Graph Visualization
    Fanghua (Joshua) Yu demonstrates a low code approach to combine Bloom – the graph visualization tool from Neo4j AuraDB – with open source intelligence platform OTX to enable more powerful visual threat investigations. Walk through the easy-to-follow instructions to do cyber threat investigation powered by graph visualization.
     
    HEALTHCARE: Microbial Knowledge Graph With BioCypher and SemSpect
    Sixing Huang presents solutions to common problems that occur when creating biological knowledge graphs. For data inconsistency, try label nodes and edges based on the Biolink model; and, for unwieldy datasets, there’s no-code SemSpect or Gemini apps that filter, aggregate, and summarize large amounts of graph data efficiently.
     
    NODES SESSION: Fundamentals of Neo4j Graph Data Science Series 2.x – Pipelines and More

    Mats Rydberg shows you how to manage and transform your graphs, use machine learning pipelines, and make the best use of your trained models – all with a focus on the dedicated GDS Python Client, which enables the data scientist to remain in a familiar environment without losing the strength of the Neo4j graph database in the backend.


    BRINGING NEO4J TO THE CLOUD: How to Deploy on Kubernetes

    Deploy Neo4j on a Kubernetes cluster with Helm charts. Follow the steps with Akash Jaiswal to clone charts, connect to a GKE cluster, and configure requirements for Neo4j on a Kubernetes cluster.

    KNOWLEDGE GRAPH: Wardley Mapping With Neo4j

    Wardley Maps: what they are, where they are used, and why they are different from – and can be usefully analyzed in – graphs. In this blog, Alexander Erdl summarizes the full-length Wardley Mapping video he made with Tom Asel from Tangible Concepts.

    NEW RELEASE: What’s New in Hume 2.17?

    Danica Stankovic announces the release of Hume 2.17. Hume is an enterprise-level graph analytics solution that allows you to convert multiple distributed data sources into a knowledge graph.

    NEW GRAPHACADEMY COURSE: Cypher Aggregations

    The new Cypher Aggregations course in Graph Academy’s Cypher Learning path is the subject of this article by Elaine Rosenberg. You’ll learn what aggregation is in Cypher and how it behaves at runtime. And you’ll run example code that uses the most widely-used aggregation functions in Cypher.

    TWEET OF THE WEEK: @tb_tomaz

    Don’t forget to retweet, if you like it!
     
    COMING UP NEXT

     
    … Of Special Interest

    • Grapho is an XR visualisation tool, and the result of ongoing research in VR interfaces for graph data manipulation. Check it out!
    • Neo4j graph database: what is it, how do you install it and how do you run basic database operations? Jithu Prabhakaran describes Nodes and Relationships, and CRUD operations on Cypher. Check it out.