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Content for User Group Meetings and Call for Presenters

Summary: Danny Bryant is seeking community input on topics for future Snowflake User Group meetings, inviting members to share areas of interest and volunteer as presenters. Andy Brown expressed interest in topics like populating Iceberg tables and using Snowflake with data lakes, offering to present on various topics, including Data Mesh and optimization in Snowflake. Kamalakannan Boovaragavan is interested in discussing Lakehouse models, while Prabhuraj Soliah at Johnson Controls is interested in Medallion Architecture and moving to AWS. Venkata Mutnuri seeks insights on data quality in Snowflake, and Sarah Shackley offers to present on building high-trust pipelines with Orbit Analytics. The feedback highlights a diverse range of topics and expertise that community members want to share or learn about.
AI Summary

As we plan our upcoming Snowflake User Group meetings, we want to ensure our sessions are as engaging and beneficial as possible. We would love to hear from you, our community members. What topics would you like to see covered in future meetings? Are there specific areas of Snowflake or data challenges that you're currently facing and would like more insight on? Additionally, if you have a success story or knowledge you'd like to share, we're inviting volunteers to present at our future events. Please share your thoughts, ideas, and volunteer interests below!

5 comments

I'm interested in hearing more on populating iceberg tables and how companies are connecting/leveraging snowflake with their data lakes.

I can also present on a few topics if anyone is interested, including our journey implementing Data Mesh at ESO, commercial uses of Snowflake Reader accounts for self-service data access, dynamic tables in ELT, and optimization of relational models in Snowflake.

Exploring how Snowflake supports Lakehouse models - keen to learn from others approaches and experiences.

In Johnson Controls, we are implementing Medallion Architecture from the scratch. I want to hear from experts, the approach to implement Silver Layer in Snowflake. (also best orchestration tool) We are also exploring the option of adopting AWS moving away from Azure for compute and storage. Like to hear from ESO and other clients the pitfalls and pain points of AWS adoption.

Any experiences on Data Quality and data metrics functions in Snowflake?

Hi Danny,

We would love to present on the following topic if people are interested:

From Raw to Ready: Building High-Trust Pipelines on Snowflake with Orbit


Snowflake makes storage and compute simple; the challenge is building reliable, cost-aware, and observable pipelines on top. In this session, we’ll show how Orbit Analytics Data Pipelines orchestrate ingestion, transformations, and data products natively on Snowflake—using Streams & Tasks, Snowpipe, and Snowpark—while giving teams lineage, quality gates, and cost controls out-of-the-box. We’ll walk through a live demo that ingests event data, runs incremental ELT, enforces tests, and serves a governed, query-ready model—then we’ll open the hood to see how it’s wired and how to run it at scale.

We can present this presentation in person as we are headquartered in Atlanta . You an email me at sarah.shackley@orbitanalytics.com if you have more questions. Thanks, Sarah