- Start Time:12:15PM
- End Time:12:25PM
- Day:Day 2
Are your analytics priorities bottlenecked by performance and capacity constraints? Does your team struggle with the conflict between a vision of business impact and the realities of systems fatigue and long wait times? While transformational software platforms like Spark and Presto have leveled-up data teams’ ambition to drive enterprise growth and innovation, data processing for analytics remains both the largest workload in the data center and the most limited and underperforming.
In this talk, we’ll explore the new criteria for data engineering and analytics modernization, starting with the data center. We’ll cover how a domain-specific approach to planning and design refreshes and expands the scope of data and unblocks use cases that were previously unfeasible. And we’ll describe how picking the right tools across the analytics value chain accelerates performance, increases resource availability, improves compliance, and reduces cost for everyone.