Understanding the Variety of MarkLogic Use Cases
summary
Progress Data Platform with MarkLogic and Semaphore claims to solve “hard” multi‑model problems by ingesting relational, JSON, XML and triples into one store and exposing them via the Optic API for combined SQL SPARQL full‑text and geospatial queries For example it powers healthcare.gov in under a year, reduces missed search hits from 75% by using ontologies and mastering, supports bitemporal time travel for historical audits and runs millions of alerts/day with low latency
AI-written summary · about
chapters (15)
- 0:00Introduction to MarkLogic
- 1:34Hard data problems and security
- 5:46Core MarkLogic use cases
- 8:14Semaphore and ontologies
- 10:40Bitemporal data and alerts
- 14:35Optic API and data integration
- 16:22GenAI focus and progress
- 21:15GenAI security and ontologies
- 24:44Data quality and GenAI accuracy
- 27:51Regulatory compliance and fraud
- 31:00Legal discovery and XML standards
- 35:11XML-based standards in payments
- 38:26Workforce management solutions
- 41:56Talent acquisition and GenAI
- 44:24Summary and Q&A
related talks
05mFernando Mesa from MarkLogic interviewed at Strata Rx 2013
06mInterviewed at Gov 2.0 – Paul Norcini
46mBuilding Knowledge Graphs
09mJason Hunter on MarkMail.org: OSCON 2008
44mBuilding Knowledge Graphs
30mThe Future of Data is Words
40mData Intelligence Platform on AWS
32mDiscover the Modern Way to Build Real-Time Analytics Solutions at Any Scale
