From Warehouse to Wisdom: Activating Business Data with Neo4j
summary
A tax data warehouse in Snowflake feeds a Neo4j graph to answer concrete questions like indirect ownership pushing investors over filing thresholds and aggregating investor exposure to high risk jurisdictions, with pipelines, a common data model, dev/QA/staging/prod automation and Bloom visuals. A first pilot uses a few seed entities, proves results, then scales to typical fund graphs of 150,000 nodes with longest paths of 15–16 hops, moving next to ML/AI and Snowflake → Neo4j integration.
AI-written summary · about
chapters (6)
- 0:00Introduction and team
- 2:48Why relationships matter in tax
- 8:04Building the tax data warehouse
- 16:32Developing the graph solution
- 24:28Key learnings and insights
- 27:44Future plans and closing
related talks
27mNeo4j GDS for Snowflake
13mLightning Talk: Highlights of the Snowflake Elastic Data Warehouse
27mHow To Develop & Operate An Agile Cloud Datawarehouse In A Rapidly Changing Multi-ERP Environment
28mUsing Dataops To Build And Manage Data Products On Snowflake
58mTales of Data Architecture Evolution
28mBuilding A Governed Data Lake
23mAcceleratinag Data Science and Machine Learning with Snowflake DataTech
23mMaturing The Snowflake Data Cloud At London Stock Exchange