This document discusses data visualization in a collaborative mixed reality space using Dynatrace. Key lessons learned include: 1) Data visualization in 3D can be quite challenging. 2) Using real data as early as possible is important, as real data is often beautiful. 3) Spatial environments can help create mental models for complex information by allowing fluid navigation through different data dimensions, with context being important.

1. DATAVIZ IN A COLLABORATIVE MIXED REALITY
SPACE

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@wassx
Stefan Wasserbauer

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Dynatrace explained to my parents

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Dynatrace „sees“what‘s the cause
when your page/web service/iot/infrastructure is:
veryslow
broken
notloading

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„Which line of code caused a
frustrating user experience
on an iOS 11
with LTE
in Indonesia
for our web checkout
at 11:15am
on which (virtual) host
hosted in which datacenter
....
“
Dynatrace

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Dynatrace
ApplicationPerformanceManagement
CloudInfrastructureMonitoring
Digital ExperienceManagement

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Credit:vladimirfloyd - Fotolia

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ChatOPs

10. Confidential 10© 2018 James Brocklebank. All rights reserve

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DesignChallenges

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DesignChallenges

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DesignChallenges

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DesignChallenges

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DesignChallenges

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DesignChallenges

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DesignChallenges

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First prototype

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Lessons learned
• Data viz in 3D quitechallenging

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Lessons learned
• Data viz in 3D quitechallenging
• Use real data as soon as possible

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Lessons learned
• Data viz in 3D quitechallenging
• Use real data as soon as possible
• Real data is beautiful

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Lessons learned –Real dataisbeautiful

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Lessons learned
• Data viz in 3D quitechallenging
• Use real data as soon as possible
• Real data is beautiful
• Usespace to create mental model for complex information

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DesignChallenges

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DesignChallenges

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Lessons learned
• Data viz in 3D quitechallenging
• Use real data as soon as possible
• Real data is beautiful
• Usespace to create mental model for complex information
• Fluid navigation throughdata dimensions.
Context is king.

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Lessons learned

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Lessons learned

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Lessons learned
• Data viz in 3D quitechallenging
• Use real data as soon as possible
• Real data is beautiful
• Usespace to create mental model for complex information
• Fluid navigation throughdata dimensions.
Context is king.
• High acceptance of holograms. Immersionindata.

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Lessons learned

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Lessons learned
• Data viz in 3D quitechallenging
• Use real data as soon as possible
• Real data is beautiful
• Usespace to create mental model for complex information
• Fluid navigation throughdata dimensions.
Context is king.
• High acceptance of holograms. Immersionindata.
• Collaboration for distributed teams

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Lessons learned

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Lessons learned
• Data viz in 3D quitechallenging
• Use real data as soon as possible
• Real data is beautiful
• Usespace to create mental model for complex information
• Fluid navigation throughdata dimensions.
Context is king.
• High acceptance of holograms. Immersionindata.
• Collaboration for distributed teams
• Drinkyour own champagne

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Infrastructure forMultiUser
Dynatrace MXR - API
User A
First client acts as „Master Client“. It can
be made responsible for handling logic
that should only be executed by one
client in a room.
Connects to cloudservice and opens room to sync
e.g. player and entity positions, events
Requests user details, workspace
list and details, triggers data query
PUN Voice
Connects to cloudservice and opens VoIP room
Requests user details (auth, tenant,...)
Requests data from Dynatrace API
via Dynatrace Assistant
User B
Joins the workspace as default client.
Requests user details, workspace list and details,
triggers data query
Joins VoIP room
Spatial Anchors
Microsoft Azure
Requests/Saves anchor features

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• Need of exception logging
• Tracinguseractions to understand/reproduce bugs
OpenKit – Monitoring multi user sessions topin point issues
Photo: GFDL, CC-BY-SA-3.0 granted by photographer

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https://www.microsoft.com/en-us/p/dynatrace-mxr/9n8w8mcjhzxx

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@wassx
StefanWasserbauer