A Layered Approach to Data Management
summary
Argues that treating IoT as layered services avoids silos and enables reuse: a separate schema interpreter maps raw device feeds into a database, a governance layer enforces privacy and dynamic permissioning, and data broker microservices create aggregated or compressed streams. Describes i3 Systems’ recently released platform and a City of LA pilot that reuses sanitation-truck video to detect potholes, graffiti and schedule repairs, improving routing and operational efficiency.
AI-written summary · about
chapters (13)
- 0:00Intro
- 1:18Data Silos
- 3:30Limitations of Silos
- 5:12Layering the Internet
- 8:59Data Brokers
- 11:57Data Infrastructure
- 14:11Quotes
- 16:22Data Ecosystems
- 17:21i3 System
- 18:54Demo
- 22:42Cloud Applications
- 23:17Conclusion
- 25:57Q A
related talks
21mData Design Challenges for Enterprise IoT Applications
30mPlatform Oriented Data Architecture for Acceler...
32mBuilding Data-Driven IoT Apps on Cloud Foundry - Dormain Drewitz, Pivotal
43mHow Big Data is Powering the Internet of Things (IoT) Revolution
23mFrom Data Strategy to a Scalable Data Mesh – How to Successfully Navigate the Journey
29mBuilding up the Bosch Semantic Data Lake
27mData Mesh for the Cognitive City
01h 00mData Mesh: Beyond the Data Lake