Neo4j & network analysis with Jenner

Jenner brings graph databases and network analysis into the SAS-compatible DATA step and PROC world. Connect to Neo4j or Memgraph with a LIBNAME, query them with Cypher/GQL, run graph algorithms, draw interactive network diagrams, and still use the SAS-compatible network-optimization and analysis procedures — all in one program.

This repository shows the whole stack, anchored by a real-world flagship notebook and a no-database visualization demo. Everything is provided in 15 languages (see Languages).

Capabilities

New — Jenner's graph family (no SAS equivalent)

Feature	What it does
LIBNAME … GRAPH ENGINE=NEO4J (or MEMGRAPH)	Bind a graph database to a libref, like any other library.
PROC GQL	Run Cypher / GQL queries against the graph and write the result set to a Jenner dataset.
PROC LINKS	Run graph algorithms — PageRank, community detection, shortest path, centrality — against the graph, writing per-node / per-edge results to a dataset.
PROC NETVIZ	Render a graph as an interactive Cytoscape.js network diagram (inline in the Jupyter kernel, or a self-contained HTML file from the CLI).

SAS-compatible network procedures

Feature	What it does
PROC OPTNET	Network optimization over Jenner datasets — shortest path, TSP, minimum-cost flow, connected components, cycles, cliques, and more. A port of SAS/OR PROC OPTNET.
PROC NETWORK	Classical network analysis over Jenner datasets — centralities, communities, biconnected components, paths. A port of SAS Viya PROC NETWORK.

The new family works on a live graph database; the SAS-compatible procedures work on links/nodes datasets you already have. They compose: pull a subgraph with PROC GQL, score it with PROC LINKS or PROC NETWORK, optimize with PROC OPTNET, and draw it with PROC NETVIZ.

Flagship notebook — ICIJ offshore-leaks fraud analytics

notebooks/en/icij_fraud_analytics.ipynb runs an end-to-end fraud-analytics pipeline against the real ICIJ Paradise Papers leak (163,435 nodes — offshore entities, officers, addresses, and intermediaries). It connects with LIBNAME … GRAPH ENGINE=NEO4J, explores with PROC GQL, and scores risk with PROC NETWORK — a complete, database-backed graph workflow.

The notebook connects to a Neo4j graph (the Jenner Workspace platform hosts the ICIJ dataset). Point the LIBNAME at your own Neo4j/Memgraph to run it against your data.

Visualization demo — no database required

demos/netviz_showcase/ renders an offshore-ownership graph as an interactive network diagram from plain datasets — run it with just the jenner CLI:

jenner demos/netviz_showcase/demo.jenner .
# -> demos/netviz_showcase/offshore_network.html

Requirements

• The jenner binary on your PATH.
• For the graph family (LIBNAME GRAPH, PROC GQL, PROC LINKS): a reachable Neo4j or Memgraph instance, and a jenner built with the neo4j feature.
• The PROC NETVIZ demo and the SAS-compatible procedures need no database.

Layout

notebooks/en/   the flagship ICIJ notebook (English)
demos/          netviz_showcase — no-database network-diagram demo
i18n/<lang>/    localized README + notebook per language

Languages

Each language folder has a localized README and a translated notebook:

Čeština	Dansk	Deutsch	Ελληνικά
Español	Suomi	Français	Italiano
日本語	한국어	Nederlands	Polski
Português	Svenska	中文

License

MIT. The ICIJ data is © ICIJ and used under their terms; see the notebook.