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Vincent Biret
Make Graph Data useful for your company
2 | SharePoint Saturday Calgary – 23 APR 2016
Sponsors
CalSPOUG
3 | SharePoint Saturday Calgary – 23 APR 2016
About MeVincent BIRETOffice Servers And Services MVP@baywetbit.ly/vince365
Products Team Tech Lead
Montreal
4 | SharePoint Saturday Calgary – 23 APR 2016
Why Should you care? Graph and Machine learning are
going to be game changers for businesses in next 10 years
IOT is the next big wave
Not caring now would be like not caring about the cloud back in 2008
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Who’s that session for?
Users who are tired of “stupid” and isolated applications
Developers who want to ship awesome apps!
Deciders who want to make something out of their data
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Today’s objective (s) Understand what’s a/the graph Understand what are MS Graph and
Delve Understand why it’s a game changer
for your business Learn how to use it in your
applications Understand what’s Azure Machine
learning Learn how to use it in your
applications
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Agenda Graph Theory MS Graph Delve MS Graph API Machine learning theory MS Azure ML Conclusion
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Ready?
Graph Theory
WHAT IS THE GRAPH?
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Is that a graph?
Category 1 Category 2 Category 3 Category 40
1
2
3
4
5
6
Title
Series 1 Series 2 Series 3
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And that?Sales
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
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That’s a Graph!
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Why Graphs?
RDBMS’s Suck!......
At doing what they are not meant for.
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The property graphVincent
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 asSince 1/7/14
Works asSince 12/7/12
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Why are computers so good with Graphs? Graphs can be represented by
matrices Very easy to compute by CPU’s Low memory usage
The Microsoft Graph
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Why A Microsoft Graph?
Data is in silosAccessing different workloads is hard
Search doesn’t workPoints out new things
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What’s Microsoft’s Graph? Unified API’s to:
Authentication Files Groups Sites Mails…
Search The Office Graph
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Resources
Graph.microsoft.io
Demo
DELVE
MS Graph API
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Structure Data
Nodes Actors Edges
Some Edges Modified Viewed TrendingAround WorkingWith OrgManager OrgColleague
Edges properties ActorId ObjectId Action Type Time Weight
Node properties SharePoint Search
Schema Object model
Demo
MS Graph API
Machine Learning Theory
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State of the art
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Hightlights
Machines can be trained to “guess stuff”
“They” can get better at doing it Not AI but a step towards it Not that new to the business
world
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Supervised learning You have training data with expected
results
You have control data with expected results
Build the experiment with a feedback loop
Train it
Put it in prod
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Classification Used to predict outcomes with few possible
values
Eg “married”, “divorced”…. Eg “rev > 50K”, “rev < 50k”…
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Regression Used to predict continuous
values
Eg Potential profit of something Eg Potential time to achieve
something
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Unsupervised learning You have data without expected
results
Build the experiment with a feedback loop
Train it
Put it in prod
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Clustering Used to detect natural grouping
patterns of data (ie: data that might be related together)
Produces groups of data and puts the data in it
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« Matchmaker » Ideal to match data together
Things like Movies you might like Items others bought Online dating (matching you with another person) …
Azure Machine Learning
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Why So important to dev’s?
Now your applications can become “clever” !!!
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Highlights Machine Learning* as a service
* Mostly predictive and semantic analytics
ML Studio
Not an Expert System
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Methodology Get data Make an experiment Test it Generate a model Publish an API Integrate with your App
Demo
ML Studio
Conclusion
TIME TO SAY GOODBYE
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Conclusion Better integration between apps/workloads
(Graph)
Better understanding of the data by apps (and predictive) (ML)
Better user experience/productivity
Happier users
Money saved for the company
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Questions & Answers / Thanks
Vincent Biret, @baywet, bit.ly/vince365 vbiret@outlook.com
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Sponsors
CalSPOUG
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