Across the globe, companies are leveling up their data capabilities and analytics maturity. While organizations have become increasingly aware of the copious new technologies at our disposal, it’s now about how we can use these in a thoughtful, efficient, and strategic way. We understand the nuances and capabilities, but how do we apply them to our own teams, workflows, and business requirements? The focus is on consolidation and optimization — companies are scrutinizing costs, monitoring performance, and leveraging orchestration more deeply than ever before. A constantly maturing data stack means regular shifts across teams, tooling, and processes. In this year’s Data Engineering Key Research Findings, DZone explores the evolved capabilities and use cases in modern data engineering, including the rise of generative AI, trends in data warehouse, lake, and lakehouse usage, data pipeline architecture and integration, and more.