Data Engineering includes best practices and technology capabilities to develop
engineered data workflows and pipelines to and between operational and analytic
data management infrastructures.
The 2025 report explores market requirements and priorities for data
orchestration, integration, and transformations including advanced analytics in the
data engineering pipeline workflow. According to the study, 81 percent of
respondents indicate data engineering is critical or very important, up from 77
percent in the 2024 survey.
The top use case for data engineering products is for data integration, cleansing, and
transformation workflows for a data warehouse supporting dashboards and
reporting, followed supporting data flows between operational systems.
“Year over year, we see an increased use of data engineering for data science and
augmented analytics use cases and replatforming/replication of an existing data
warehouse,” said Howard Dresner, founder and chief research officer. “However,
those still lag behind the bread-and-butter use cases such as data integration and
transformation for ad hoc query, discovery, and exploration analysis.”