This document provides an agenda for the SharePoint Saturday event in Ottawa on December 3rd, 2016. The agenda includes sessions on topics like The Graph, Delve, Microsoft Graph API, machine learning with ML Studio, and more. It also includes information about the speaker, Vincent Biret, and his contact details.
16. 17 |SharePoint Saturday Atlanta
Vincent
Desk: E43
Phone: 514 444 4444
Extension: 275
Negotium
Street Address: Montreal
Creation : 1/1/00
Technical Advisor
Must do: technical advising
Advantages: better business cards
Developper
Must do: development
Advantages: better keyboard
Works as
Since 1/7/14
Works as
Since 12/7/12
That among 3D printing, holographic vision, IOT and a few other stuffs
Bar chart, pie chart
Graph = connected objects by links (generic), graph theory is the study of graph, graph abstract data type implementing graph theory
Made for forms data but not really for connected data. That’s why we have to denormalize it which is a huge waste of resources.
Other paradigms, Hierachical, NoSQL Document/search, Cubes and Graphs
Hierarchical dbs ex : active directory, MMS… or old navigation databases from the 70’s
And because it’s trendy Facebook is doing it
LinkedIn too (connecting people)
Amazon too (IMDB)
Google (google knowledge)
One endpoint.
One auth flow (oauth 2/openid connect)
https://msdn.microsoft.com/office/office365/HowTo/query-Office-graph-using-gql-with-search-rest-api
Use main endpoint with regular data + insights, this is where Microsoft is going to invest.
GQL only for advanced graph people, + auth is not brokered…
Show the endpoints + resulting json
These ones use actors, edges and file types nodes, only 2 endpoints available right now (+/me + /users)
https://graph.microsoft.io/en-us/graph-explorer
No we don’t have AI robots yet. Yes that’d be awesome. Other last 15 years we’ve made lot of progress in robots, androïd, learning machine, semantic/photo analysis, expert systems… ML is only a small part of what we consider being « artificial thinking »
Ex machina
Post card systems (80’s), bank fraud detection patterns, insurances, loans….