Data Modeling in Telecoms - GraphConnect NY 2013
•Download as ODP, PDF•
1 like•1,079 views
This document discusses using graph databases like Neo4j for data modeling in telecommunications. It provides examples of how Neo4j can be used to model cellular network topology, geographic spatial indexes, open street map data, user access management, event log correlation, network management and critical infrastructure, and business intelligence and statistics. Neo4j is well suited for these types of models due to its high performance on complex traversals and ability to match the domain model to the database schema.
Recommended
Recommended
More Related Content
Similar to Data Modeling in Telecoms - GraphConnect NY 2013
Similar to Data Modeling in Telecoms - GraphConnect NY 2013 (20)
More from Craig Taverner
More from Craig Taverner (8)
Recently uploaded
Recently uploaded (20)
Data Modeling in Telecoms - GraphConnect NY 2013
- 1. Data Modeling in Telecoms
- 2. AmanziTel / DingLi ● Customer Experience Management ● Cellular Telephone Networks ● Neo4j OEM since 2009 ● AmanziTel in Sweden ● DingLi in China
- 3. Who are we?
- 4. Playing on the Edge
- 5. AWE-2009 Neo4j – graph database ● extremely high performance on deep traversals and mining of complex data, ● rapid schema evolution for changing business requirements, and ● simplified development through perfect match between domain model and database schema.
- 6. AWE-2009
- 7. Splash-Neo4j = a1 + ' ' + a2 = sum(a1..a3)
- 11. Graph Data Models ● Cellular Network Topology Tree ● Geographic/Spatial Index ● OpenStreetMap ● User Access Management ● Event Log Correlation ● Network Management / Critical Infrastructure ● Business Intelligence / Statistics
- 13. Cellular Network Topology ID Site Latitude Longitude 1 ABC 55.678 12.567 2 XYZ 55.890 12.123 3 PRQ 55.543 12.890 ID Sector SiteID Azimuth Beamwidth 1 1 1 0 100 2 2 1 120 100 3 3 1 240 100 4 1 2 0 90 5 2 2 120 110 6 3 2 240 90 7 1 3 0 180 8 2 3 180 180 O(N) O(ln(N)) O(1)
- 17. = a1 + ' ' + a2 = sum(a1..a3)
- 18. Spatial Index
- 19. Spatial Index
- 20. Spatial Index
- 21. OpenStreetMap
- 22. OpenStreetMap
- 23. OpenStreetMap
- 25. Data Mining OSM timestamp > 1207014810000 and timestamp < 1208310810000 and ( user = 'Zenon' or user = 'tomasCY' or user = 'muffu' or user = 'dcp' or user = 'cartOMike' or user = 'djanda' or user = 'Peter14' or user = 'toaster' or user = 'user_7363' or user = 'lyx' )
- 30. Network / Critical Infrastructure
- 34. Performance Implications ● Know your domain ● Know your queries ● Examples
Editor's Notes
- Two and a half years ago I was on safari in South Africa and I took this photograph. This is my nephew standing on the edge of a 100m high cliff Why is he doing that? The view is great! You can see families of giraffe in the valley. It is exciting, kids are attracted to excitement. My talk is about finding excitement in development by playing on the edge. Taking risks and thereby finding a more efficient route. Unless you fall off the edge, that is! (Two types of edge – cliffs and interfaces)
- We made a key, revolutionary change. Look, the map is still there and the scripting console is still there, but what is that ferris wheel to the top right? Ported the data structures onto the graph database, Neo4j, made by Neo Technologies right here in Malmö. This is one of the very first screenshots of the prototype results of getting the network data onto neo4j.
- The addition of neo4j lead to a revolution in thinking. Instead of data and analysis and reporting being different levels or different structures, they are all just graph structure in the database. This means you can analyse the results of previous analyses. Just keep adding structure to the database. All the views are direct maps onto the database: GIS traverses gis-next edges Tree traverses child edges Charts traverse aggregation-child edges Property tables display node properties Neo4j has added a whole new angle to the use of the word &apos;EDGE&apos; :-)