Are your Snowflake credits working smarter — or harder? Misconfigurations, bad queries and idle compute waste budget fast. CDW’s Warehouse Optimization and Analysis (WHOA) helps maximize cost efficiency, performance and insights — without live agents or intrusive monitoring. Learn to spot waste, optimize usage and see real results — and do better things with your credits!
Partners
CDW
Blue Square
Overview
1218
Sponsored Sessions
Advanced
Theater Session
Technical Executive
Business Executive
IT / DBA
BI / Analyst
Data Scientist
Software Developer
Security Practitioner
Marketing Practitioner
Product Manager
DevOps
Data Engineer
MLOps
2:00pm - 3:00pm
Not industry-specific
2943
Cost Governance
Platform Migrations
Powered by Snowflake
Observability
Streaming
Compliance
Machine Learning
Privacy
Snowflake on Snowflake
MLOps
Upskilling, learning and certification
BI and Analytics
Cybersecurity
Data Engineering & Pipelines
Data Mesh / Data Fabric
Governance
Data Sharing & Collaboration
AI & GenAI
Snowflake Notebooks
Snowpark for Python or pandas
Snowflake Native Apps
Wed, Jun 4
All Days
Theaters are first come, first seated
Not department-specific
Other (Industry-A)
AI & GenAI (Topic)
Application Development (Topic)
BI & Analytics (Topic)
Collaboration & Marketplace (Topic)
Data Architectures, including Lakehouse, Mesh, Lake and Warehouse (Topic)
Data Engineering & Streaming (Topic)
DevOps & Observability (Topic)
Governance, Privacy & Security (Topic)
Machine Learning (Topic)
Open Source & Research (Topic)
Platform Migrations (Topic)
BI / Analyst (Role)
Business Executive (Role)
Data Engineer (Role)
Data Scientist (Role)
IT / DBA (Role)
Marketing Practitioner (Role)
Product Manager (Role)
Security Practitioner (Role)
Software Developer (Role)
Technical Executive (Role)
General Theaters
2:00 p.m. Wednesday, Jun 04
Wednesday, Jun 04
Intermediate
Breakout Session
Technical Executive
Business Executive
IT / DBA
BI / Analyst
Data Scientist
Software Developer
Security Practitioner
Marketing Practitioner
Product Manager
DevOps
Data Engineer
MLOps
Governance, Security and Discovery
3:00pm - 4:00pm
Not industry-specific
2942
Cost Governance
Data Lakes
Platform Migrations
Powered by Snowflake
Customer 360
Observability
Snowflake Native Apps
Streaming
Compliance
Machine Learning
Privacy
Snowflake on Snowflake
MLOps
Upskilling, learning and certification
BI and Analytics
Cybersecurity
Data Mesh / Data Fabric
Governance
Data Sharing & Collaboration
AI & GenAI
Snowflake Notebooks
Snowpark for Python or pandas
Iceberg Tables
Hybrid Tables
Snowflake Native Apps
Snowpark ML
Marketplace
Data Clean Rooms
Snowflake Horizon Catalog
Wed, Jun 4
All Days
Not department-specific
Other (Industry-A)
AI & GenAI (Topic)
Application Development (Topic)
BI & Analytics (Topic)
Collaboration & Marketplace (Topic)
Data Architectures, including Lakehouse, Mesh, Lake and Warehouse (Topic)
Data Engineering & Streaming (Topic)
DevOps & Observability (Topic)
Governance, Privacy & Security (Topic)
Machine Learning (Topic)
Marketing & Customer 360 (Topic)
Open Source & Research (Topic)
Platform Migrations (Topic)
BI / Analyst (Role)
Business Executive (Role)
Data Engineer (Role)
Data Scientist (Role)
IT / DBA (Role)
Marketing Practitioner (Role)
Product Manager (Role)
Security Practitioner (Role)
Software Developer (Role)
Technical Executive (Role)
OnDemand
Wednesday, Jun 04
3:00 p.m. Wednesday, Jun 04
AI is only as smart as the data it learns from. Without trusted, governed, accessible data, AI fails. Enter Minimum Viable Data Governance (MVDG) — the foundation of AI success. This session covers why AI fails without MVDG, how Snowflake enables scalable, automated governance, and real-world examples. Learn how lightweight governance removes friction and fuels AI — not a checkbox, but a necessity. MVDG ASAP!
Speakers
Jay Brophy
Principal Consultant
CDW
Jay Brophy is a distinguished data architect, data engineer, and data scientist with over 20 years of experience in creating and leveraging analytics platforms for AI, data science, data engineering, and analytics and enabling $1B in ROI. His mission is to drive business value and product innovation through data-driven solutions that enable low-friction, high-volume data ingest for producers and off-the-shelf data products for consumers.
Ben Castleton
Data Quality Principal
CDW
Ben Castleton is the Data Quality Principal for CDW's Data and Analytics Practice. Along with leaders Rex Washburn and Paul Zajdel, Ben helped coin the term Minimum Viable Data Governance. He has been helping clients and industry groups understand its benefits for the past year. Ben has spent over 15 years in data and analytics, from healthcare and finance to tech and AI startups. Ben was one of the cofounders of the team at Great Expectations Labs, Inc. That experience gave him insights into hundreds of companies implementing data quality profiling, monitoring, and reporting at enterprise scale. Ben's pragmatic approach to data quality focuses on making data valuable for stakeholders.