PASSMN is a forum to exchange knowledge and ideas to better understand, develop, implement and support existing and future Microsoft data technologies. Our technical sessions provide a professional, fun and educational environment for all levels of expertise.

We typically meet on the third Tuesday of the month in the afternoon at the Microsoft offices in Edina, MN. Please sign up on Meetup.

Executive Board – PASSMN

Code of Conduct

All group members should follow

Be friendly and welcoming
- Listen with purpose and create space for others’ communication preferences.
- Ask yourself how you can make someone life easier.
Be patient
- Remember that people have varying communication styles and preferences.
- Recognize that not everyone is using their native language. Meaning and tone can be lost in translation.
Be thoughtful
- Think about how others will interpret your words. Aim for clear and productive communication.
- Remember that sometimes it is best to refrain from commenting.
Be respectful and inclusive
- Respect differences of opinion.
- Seek to understand and build bridges, not condemn or criticize.
- Make a conscious effort to include people who differ from you.
Be open and curious
- Assume good intent and interpret others’ statements or questions in good faith.
- Ask questions to understand, not denounce.
- Focus on continuous learning. Improve upon the things you already know, tackle new things, and ask others about their expertise to deepen your own knowledge.

Summary

Treat everyone with respect, kindness, and empathy.
Use welcoming and inclusive language.
Be thoughtful in how you communicate in person and online.
Don’t be destructive or inflammatory.
Gracefully accept constructive criticism.
Listen with purpose and create space for others’ communication preferences.
Reach out to the organizers if you need anything.

Reporting

Please report any concerns, suspicious activity, or disruptive behavior to the Azure Tech Groups team at Board@PASSMN.com.

Contact the host of PreCon: Governed Finance AI on Databricks - From Data to Variance Agents