Deep Dish Data Virtual Series
2 Year Anniversary Special | State of Data Engineering
April 29, 2025 | 8 AM PT / 11 AM ET / 4 PM GMT

Thursday, June 6 | 9:30 AM - 2:00 PM CAT | Workshop17, Johannesburg

Deep Dish Data - 2 Year Anniversary - Streaming Live from Denver

Join us for a special edition of Deep Dish Data as we celebrate our 2-year anniversary with a power-packed live discussion on the State of Data Engineering!

Date: April 29, 2025
Time: 8 AM PT | 11 AM ET | 4 PM GMT

What to expect:

Data engineering has evolved significantly in recent years, and we’re bringing in experienced industry practitioners to discuss where we are today—and where we’re headed next. Expect an engaging, fully loaded discussion on data workflows, modern data orchestration, and the biggest trends shaping the field—diving deep into the latest trends and serving up fresh insights you can actually use!

Joining us for this milestone event is our host, Mark Balkenende, leading the conversation alongside our resident co-host and data aficionado Joe Reis, who was the very first guest to ever grace Deep Dish Data. Also making her debut is Carly Taylor, a true data rebel pushing the boundaries of data science, technology strategy, and innovation in the gaming industry.

Key topics:

The current state of data engineering
The evolution of data workflows and automation
How data orchestration is changing modern data teams
Where the industry is headed next

Why attend?

Gain insights from seasoned pros in data engineering
Engage with a live audience through Q&A and polls
Walk away with actionable takeaways for your data strategy

Can’t make it live? No worries! Sign up now and we’ll deliver a fresh recording straight to your inbox!

Register Now

Our live product demos include:

Connecting any data source to Snowflake or your cloud data warehouse
Creating no-code batch and change data capture pipelines
Orchestrating complex business logic via visual patterns in a low-code tool
Speeding up development with a live sample of your data at design-time
Taking advantage of Snowflake's native features with modern ELT and how that is faster than traditional ETL patterns

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